Department of Electrical Engineering, Indian Institute of Science Department of Electrical Engineering, Indian Institute of Science Indian Institute of Science

Events and Seminars Archieve

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Department Student Seminars list

Other seminars list

Thesis Colloquium/Defence List

  • PhD
    • Colloquium
      Sl.No. Name of the student Date of Colloquium Title of the Thesis
      7 Vijay H. Bhosale 26/10/2016 Developmental Studies On Ultra-Wide Band Type High Power Electromagnetic Radiating System Guide:
      6 K V Vijay Girish 28/09/2016 Sparse representation and acoustic-phonetics knowledge for speech analysis Guide : Prof. A G Ramakrishnan
      5 Basty Ajay Shenoy 15/09/2016 Phase Retrieval and Hilbert Integral Equations -- Thinking Beyond Minimum Phase Guide: Prof. Chandra Sekhar Seelamantula
      4 Satish Mulleti 25/08/2016 Sub-Nyquist Sampling of Structured Signals and Applications to Imaging Guide: Prof. Chandra Sekhar Seelamantula
      3 Aniruddha Adiga 18/08/2016 Sparsity Motivated Auditory Wavelet Representation and Blind Deconvolution Guide: Prof. Chandra Sekhar Seelamantula
      2 Shantanu Chakrabarty 29/07/2016 Algorithms for Adjusted Load Flow Solutions using the Complementarity Principle Guide: Prof. P S Nagendra Rao
      1 Sunil Kumar P.R. 31/05/2016 Design and Analysis of Real-time Message Scheduling under FlexRay Protocol
    • Defence
      Sl.No. Name of the student Date of Defence Title of the Thesis
      16 Anirudh Guha 10/03/2017 Dead-time induced oscillations in voltage source inverter-fed induction motor drives Guide: G. Narayanan
      15 Sachin Srivastava 05/12/2016 Behavior of Distance Relay Characteristics on Interconnecting Lines Fed from Wind Farms Guide: Dr. U. J. Shenoy
      14 S P Manivannan 07/10/2016 DSA Image Registration and Respiratory Motion Tracking using Probabilistic graphical Models. Guide: Prof. K. R. Ramakrishnan
      13 Avishek Chatterjee 27/06/2016 Geometric Calibration and Shape Refinement for 3D Reconstruction, Guide: Venu Madhav Govindu
      12 Tukaram Moger 20/06/2016 Reactive Power Planning and Operation of Power Systems with Wind Farms for Voltage Stability Improvement, Guide:Prof. D. Thukaram
      11 V.Seshadri Sravan Kumar 03/06/2016 Modeling and Analysis of Grid Connected Variable Speed Wind Generators, Guide:
      10 A. Ibrahim 27/05/2016 Effective Characterization of Sequence Data through Frequent Episodes, Guide: Prof. P. S. Sastry
      9 Mr. Pritam Mukherjee 26/05/2016 ,A Novel Generalized Framework to Diagnose True Radial and Axial Displacements in an Actual Transformer Winding Guide: Prof. L. Satish
      8 Mr.Manoj K.Mandlik 23/04/2015 Moisture Aided Degradation of Oil Impregnated Paper Insulation in Power Transformers, Guide:
      7 Abhijit K 18/04/2016 Design and Control of Power Converters for Renewable Energy Systems, Guide: Prof. Vinod John
      6 Binoj Kumar A.C 17/03/2016 Experimental Studies on Acoustic Noise Emitted by Induction Motor Drives Operated with Different Pulse Width Modulation Schemes, Guide:Prof. G. Narayanan
      5 Ms.Anusuya Bhattacharyya 20/11/2015 Discharge plasma based NOx abatement in engine exhaust assisted by industry wastes: A parametric evaluation with diesel fuels and corona electrodes, Guide: Prof. B.S. Rajanikanth
      4 Ms.N.S.Jyothi 29/06/2015 Thermal and Electrical Degradation of Resin Impregnated Insulation for High Voltage Transformer Bushings, Guide:
      3 Mr.A.P.Prathosh 24/06/2015 Temporal Processing for event-based Speech Analysis with Focus on stop consonants, Guide: Prof. A. G. Ramakrishnan
      2 Mr.V. S. S. Pavan Kumar Hari 28/03/2015 Space-Vector-Based Pulse Width Modulation Strategies to Reduce Pulsating Torque in Induction Motor Drives, Guide: Prof. G. Narayanan
      1 Mrs.Sunitha K 25/07/2014 Coupling of Electromagnetic Fields from Intentional High Power Electromagnetic Sources with a Buried Cable and an Airborne Vehicle in Flight, Guide:
  • MSc(Engg)/ MTech(Res)
    • Colloquium
      Sl.No. Name of the student Date of Colloquium Title of the Thesis
      7 Dibakar Das 27/02/2017 Control Strategies for Seamless Transition between Grid Connected and Islanded modes in Microgrids Guides : Dr. U Jayachandra Shenoy & Dr. Gurunath Gurrala
      6 Adhip 06/02/2017 Real power flow tracing for preventive control in deregulated power systems. Guides : Prof. D Thukaram and Dr. GurunathGurrala
      5 Subash Chandran K S 04/10/2016 Analysis of LFP Signal and gamma Rythm using Matching Pursuit Algorithm Guide:
      4 S. D. Yamini Devi 19/09/2016 Fractal Encoding for Inpainting and Secure Image Sharing. Guide: Prof. K. R. Ramakrishnan
      3 A. Santosh Kumar 25/07/2016 Voltage Stability Analysis of Unbalanced Power System Guide: Prof. D. Thukaram
      2 Daniel Sanju Antony 21/07/2016 Performance Analysis of Non Local Means Algorithm using Hardware Accelerators Guide : Dr. G N Rathna
      1 Ms. Ann G Sarah 30/03/2016 Discharge plasma supported mariculture and lignite waste for NOx cleaning in Biodiesel exhaust: Direct and Indirect methods lignite waste for NOx cleaning in Biodiesel exhaust: Direct and Indirect methods,
      Guide: Prof.B.S. Rajanikanth.
    • Defence
      Sl.No. Name of the student Date of Defence Title of the Thesis
      17 K.S.Subhash Chandran 27/03/2017 Analysis of Local Field Potential and Gamma Rhythm Using Matching Pursuit Algorithm. Guide :Dr. Supratim Ray, Prof. Chandre Sekhar Seelamantula
      16 Narmada Naik 14/02/2017 Real Time Face Recognition on GPU using OPENCL Guide: Dr. G. N. Rathna
      15 A. Santosh Kumar 31/01/2017 Voltage Stability Analysis of Unbalanced Power Systems, Guide: Dr.Gurunath Gurrala
      14 Daniel Sanju Antony 13/01/2017 Performance Analysis of Non Local Means Algorithm using Hardware Accelerators Guide G. N. Rathna
      13 Mr.K.Chennakeshava 30/12/2016 Adaptive Sampling Pattern Design Methods for MR Imaging Guide: Prof. K Rajgopal
      12 S.Navin 09/12/2016 New Algorithms for some Economic Dispatch Problems, Guide: Prof. P. S. Nagendra Rao/ Prof. A. G. Ramakrishnan
      11 Deepak G Skariah 14/06/2016 Improved Regularization and Optimization Methods for Image Restoration,
      Guide: Dr. Muthuvel Arigovindan
      10 G.Manoj Kumar 23/03/2016 Accurate Estimation of Frequency and Phasor for wide Area Monitoring and control,
      Guide:
      9 Mr.Siva Kumar Balibani 14.08/2015 Small Signal Stability Analysis of a Power System with a Grid Connected Wind Powered Permanent Magnet Synchronous Generator(PMSG),
      Guide:
      8 Mr.P.R.Rakesh 31/07/2015 PWM Techniques For Split-phase Induction Motor Drive,
      Guide:
      7 Mr.Sreeram.V. Menon 20/05/2015 Savitzky-Golay Filters And Application To Image And Signal Denoising,
      Guide:
      6 Mr.M. Gokul Deepak 27/04/2015 Motion Estimation from Moments of Projection Data for Dynamic CT,
      Guide:
      5 Ms.Harini Kishan 20/03/2015 On Maximizing the Performance of the Bilateral Filter for Image Denoising,
      Guide: Chandrasekhar Seelamantula
      4 Mr.Ashish Kumar 20/02/2015 Hall-Effect Current Sensors for Power Electronic Applications: Design and Performance Validation,
      Guide:
      3 Ms. Lakshmi S 03/12/2014 Adjusted load flow solutions using complementarity framework
      Guide :
      2 Ms. N.S. Jyothi 07/08/2014 Thermal and Electrical Degradation of Resin Impregnated Paper Insulation for High Voltage Transformer Bushings,
      Guide: Prof. T.S. Ramu and Prof. Udaya Kumar
      1 Mr.B.Abhiram 08/08/2014 Characterization of the voice source by the DCT for speaker information,
      Guide:

Title : Time Scales in Control of Wind Energy Systems
Speaker : Prof. D. Subbaram Naidu
Date : 23/03/2017
Venue : C 241 MMCR, EE
Abstract: An overview of the author's journey of research experiences in the field of Singular Perturbations and Time Scales (SPaTS) in Control Theory and Applications (CTA) from Indian Institute of Technology (IIT), Kharagpur to University of Minnesota is presented. The SPaTS methodologies focus on the analysis of decoupling of high-order dynamical systems with slow and fast phenomena and the synthesis (design) of controllers for slow and fast subsystems. The research covers both theory and applications to a wide spectrum of fields in engineering such as aerospace, electrical, mechanical, and in sciences such as biology and ecology with particular emphasis to wind energy conversion systems.
Speaker bio: Desineni “Subbaram” Naidu received MTech and PhD degrees in Electrical Engineering (Control Systems Engineering), from Indian Institute of Technology (IIT), Kharagpur. Dr. Naidu taught, visited and/or conducted research at IIT; Guidance and Control Division at NASA Langley Research Center; Old Domain University; Measurement and Control Engineering Research Center at Idaho State University; Center of Excellence in Advanced Flight Research at United States (US) Air Force Research Laboratory; Center of Excellence for Ships and Ocean Structures at Norwegian University of Science and Technology; Measurement and Control Laboratory at Swiss Federal Institute of Technology; Nantong University, China; the University of Western Australia in Perth, Center for Industrial and Applied Mathematics at the University of South Australia in Adelaide; Jiangsu College of Information Technology, Jiangsu, China; Center for Applied and Interdisciplinary Mathematics at East China Normal University, Shanghai, China; Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China; Shanghai Jiao-Tong University, Shanghai, China. Since August 2014, Professor Naidu has been with University of Minnesota Duluth as Minnesota Power Jack Rowe Endowed Chair. Professor Naidu received twice the Senior National Research Council Associateship award from the US National Academy of Sciences, and is an elected (Life) Fellow of the Institute of Electrical and Electronic Engineers (IEEE), USA and an elected Fellow of the World Innovation Foundation, UK. He has over 200 publications including 8 books. He has been on the editorial boards of several journals including the IEEE Transactions on Automatic Control and Optimal Control: Applications and Methods.

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Title : Modeling, Control and Analysis of Wound Rotor Induction Machines
Speaker : Ramu Nair
Advisor : Prof. G. Narayanan
Date : 17/03/2017
Venue : C 241 MMCR, EE
Abstract: Wound Rotor Induction Machines (WRIM) are widely employed in wind energy conversion systems and in high power drives. Most of control techniques used in drives, are model based and hence machine parameter dependent. Therefore, to achieve better performance and control, accurate estimates of motor parameters are necessary. In this work, a method for studying parameter variation in WRIM is suggested and validated through experimentation.

Rotor position is inevitably required in the closed loop control of induction machines. A rotor position estimation technique based on Model Reference Adaptive Control will be presented with experimental results.

In wind energy conversion systems, the stator side is directly connected to grid, while the rotor side of WRIM is fed from a controlled power converter. Direct connection of WRIM stator to grid results in transfer of grid-voltage disturbances on to rotor side. A grid-voltage sag manifests as an over-voltage in rotor windings. A simulation study on the same is presented.

Speaker bio: Ramu Nair received the B.Tech. degree in Electrical and Electronics Engineering from Mar Athanasius College of Engineering, Ernakulam, India, in 2009 and M.Tech. degree in Energy Systems Engineering from Indian Institute of Technology Bombay, Mumbai, India, in 2012. He is currently working toward the Ph.D. degree in the Department of Electrical Engineering at Indian Institute of Science, Bangalore, India. His research interests include power electronics, drives and control systems.

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Title : Understanding the role of brain oscillations in cortical processing
Speaker : Dr. Supratim Ray
Date : 10/03/2017
Venue : C 241 MMCR, EE
Abstract: Brain signals often show oscillations at different frequencies, which are tightly coupled to different behavioral states. We are interested in a high-frequency oscillation called “gamma” (30-80 Hz), which is modulated by high-level cognitive processes such as attention, memory, and meditation. In the first part of my talk, I will discuss some characteristics of gamma oscillations, in particular how varying the color, size and contrast of the stimulus can modulate gamma oscillations, and how these oscillations can be disrupted by introducing discontinuities in the stimulus. In the second part of the talk, I will discuss signal-processing techniques that are used to study some properties of gamma rhythm, such as its duration.
Speaker bio: Dr. Supratim Ray received a B.Tech in Electrical Engineering from IIT Kanpur and a PhD in Biomedical Engineering from the Johns Hopkins University. His postdoctoral training was in the department of Neurobiology at Harvard Medical School. He joined the Center for Neuroscience in June 2011 and is an Associate Faculty in the Electrical Engineering Department since 2012.

His lab studies the mechanisms of attention, i.e., our ability to focus on behaviorally interesting and relevant stimuli while ignoring others. In particular, he is interested in particular brain rhythms thought to be associated with higher order cognitive functions such as attention.

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Title : Stability Analysis of Laurent Systems
Speaker : Dr. Chirayu D. Athalye.
Date : 02/03/2017
Venue : C 241 MMCR, EE
Abstract: goo.gl/eEtqUi
Speaker bio: Dr. Chirayu Athalye did bachelor's in Electrical Engineering from SP College in Mumbai University. He received MTech and PhD degrees from IIT-Bombay. His research areas of interest are dynamical systems, multidimensional systems, infinite dimensional systems, optimal control, multiagent systems, stability analysis, applied and numerical linear algebra, convex analysis and optimization, LMI, and matrix completion problem.

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Title : Bipedal robots: Bridging the gap between theory and experiment
Speaker : Dr. ShiShir N.Y. Kolathaya
Date : 20/02/2017
Venue : C 241 MMCR, EE
Abstract: Natural selection has enabled us to adapt to our environments and achieve complex tasks with relative ease, especially in the area of legged locomotion. These abilities have not yet been translated to bipedal robots, despite the use of complex models, computing power, and novel actuators and sensors. This gap between simulated and observed behavior gets wider with more dynamic tasks like running. Therefore, this talk focuses on a mathematical framework that formalizes the process of implementation in real world systems, i.e., that bridges the divide between theory and experiment. Specifically, the notion of input-to-state stability (ISS) is applied for the construction of robust controllers for a class of hybrid systems that characterize bipedal robots. By treating uncertainties (modeling, model parameter, measurement), or functions of uncertainties as inputs to a system, the talk will describe how to reduce this to a form amenable for input-to-state stability analysis. With this analysis, robust controllers are realized, with the goal of realizing dynamic locomotion behaviors like walking and running, thereby bridging the gap between theory and experiment. This will be demonstrated on multiple robotic platforms including a humanoid robot and running robot.
Speaker bio: Dr. Shishir is a Postdoctoral scholar working for AMBER Lab in the California Insitute of Technology. He received his PhD degree in Mechanical Engineering (2016) from the Georgia Institute of Technology, M.S. degree in Electrical Engineering (2012) from Texas A & M University, and B. Tech degree in Electrical & Electronics Engineering (2008) from the National Institute of Technology Karnataka, Surathkal, India. Prior to pursuing his Master's degree, he also worked for two years as a power supply designer in Tejas Networks Ltd., Bangalore. Shishir has been an integral part of AMBER Lab for more than six years working with Dr. Aaron Ames across three different institutions from 2011-2017. He is interested in nonlinear control, dynamical systems, hybrid dynamical systems, robotics, and particularly in bipedal locomotion.

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Title : Applications of Fourier transform for computing the signed Euclidean distance function and its gradient density function
Speaker : Karthik Gurumoorthy
Date : 17/02/2017
Venue : C 241 MMCR, EE
Abstract: In this presentation, I will present a fast convolution-based technique for computing an approximate, signed Euclidean distance function. The solution stems from first solving for a scalar field in a linear differential equation and then deriving the solution by taking a negative logarithm. The linear formalism results in a closed form solution expressible as discrete convolution and hence efficiently computable using the fast Fourier transform. Computing the winding number and topological degree aid in determining the sign of the distance function whose computations can also be performed via fast convolutions. The complex wave representation (CWR) converts unsigned 2D distance transforms into their corresponding wave functions. Here, the distance transform appears as the phase of a wave function. I will demonstrate using the higher-order stationary phase approximation the convergence of the normalized power spectrum (squared magnitude of the Fourier transform) of the wave function to the density function of the distance transform gradients as a parameter approaches zero. In colloquial terms, spatial frequencies are gradient histogram bins. Some applications of the density of the orientations, known as HOGs (histogram of oriented gradients) include human and object detection and sketch based image retrieval. Towards the end of my talk, I will provide a unified representation from which both the distance function and its gradient density function can be simultaneously retrieved.
Speaker bio: Karthik Gurumoorthy graduated with a dual masters degree in Mathematics and in Computer Science in 2009 and 2010 respectively and earned a doctorate degree in Computer Science in 2011 from the University of Florida, Gainesville. He continued at the same institution for a year in the capacity of a post-doctoral researcher and later joined GE Global Research, Bangalore as a Research Scientist in 2012 pursuing research in the field of medical image analysis. After completing a year and 3 months at GE, he accepted an AIRBUS post-doctoral fellowship position at International Center for Theoretical Sciences, Tata Institute of Fundamental Research (ICTS-TIFR), Bangalore where he conducted research in data assimilation and filtering theory for over a year and 6 months. He currently works at Amazon Development Center, Bangalore as a Machine Learning Scientist in the core Machine Learning Group and is also an Associated Faculty at ICTS-TIFR. He has worked on a wide gamut of problems covering domains like signal processing, computer vision, machine learning, density estimation, filtering theory and image compression and is motivated by problems which are mathematical in nature.

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Title : A Primer on Blockchain Technologies
Speaker : N S Amarnath
Date : 03/02/2017
Venue : C 241 MMCR, EE
Abstract: This talk will cover, briefly, the history of blockchain technology and provide a brief description and rationale for some of the more popular blockchain technologies in the market today. A blockchain is a distributed, secure ledger of transactions which are easy to read, and hard to write or modify. Each block in a blockchain represents a collection of transactions.

The focus of the talk will be on blockchains for contracts and ledgers, with an example from power contracts. Along the way, some encryption algorithms and techniques will be covered, explaining how blockchains work, and why they are considered secure. At the end of the talk, a sample application on Chain, an open source implementation of blockchains, will be presented.

Keywords: Blockchains, contracts

Speaker bio: Amarnath has had a versatile career over 30 years where he has managed people, technology and large, critical programs. He has worked in areas ranging from computer vision, software engineering tools, online advertising, payment services and enterprise mobility. He’s worked in senior positions in organisations like Amazon Web Services, Yahoo! and Samsung Electronics. His last corporate position was Sr. VP in Samsung Electronics. His strengths are in using technology, especially large, distributed, secure services to achieve business goals. He is an alumnus of dept. EE, IISc, having obtained both BE and ME degrees from there. LinkedIn profile is https://in.linkedin.com/in/n-s-amarnath-72b1ba4”

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Title : Ancillary from renewables
Speaker : Sukumar Mishra
Date : 31/01/2017
Venue : C 241 MMCR, EE
Abstract: With the enhanced controllability of Renewable energy sources (RES) in the domain of microgrid and distribution networks, several tasks can be accomplished over the conventional constant active and reactive power (P-Q) dispatch. While the RES are mostly inertia-less sources, modifications in the control loop can be made for attaining the services which are predominant at the transmission level. Such services include voltage and frequency regulation, response based services such as the short term frequency and voltage response, and addressing power quality issues at a distribution level. The RES can be controlled to operate the corresponding inverter in the grid forming, grid feeding and the grid supporting modes. In the isolated mode of operation, when there are no rotating generators (diesel generator), the RES is responsible for the voltage and frequency regulation. This can be achieved using a centralized or a decentralized approach. The decentralized approach is more popularly known as the droop based approach. Droop control enables the proper power sharing as per their droop setting and power rating. Further, a secondary control aids in the efficient voltage and frequency regulation of microgrids in the absence of DG. Even in the presence of a DG, a modification in the droop control strategy to mimic an inertial control to work in consensus with the conventional DG can be achieved providing the inertial support to existing DG. The droop controlled inverters with an inherent synchronization loop are generally known as grid forming inverters and a complete set of the droop and the synchronization control can enable of seamless mode transition between the isolated and the grid connected modes. The grid feeding RES behave mostly as constant power sources. Such controllers, when enabled with inertial and voltage control in the grid connected modes can aid in the ancillary services such as the provision of frequency and voltage response. In addition to the aforementioned ancillary services, the RES in the grid supporting mode can provide enhanced power quality control by modification in the current controller using the sequence components and virtual impedance. Further, single phase RES can be used for three phase balancing, by properly choosing current injection in response to the voltage unbalances.
Speaker bio: Dr. Sukumar Mishra is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Delhi. His interest lies in the field of Power Systems, Power Quality Studies, and Renewable Energy. He has published over 100 research articles (inclu ding papers in international journals, conferences and book chapters). He is currently holding the position of Vice Chair of Intelligent System Subcommittee of Power and Energy society of IEEE. He is a recipient of the INSA medal for young scientist, the INAE young engineer award, and the INAE silver jubilee young engineer award. He is also a Fellow of IET (UK), NASI (India), INAE (India) and IETE (India). He is working as the NTPC Chair professor and has previously worked as the Power Grid Chair professor. He is also serving as an Independent Director of the Cross Border Power Transmission Company Ltd. and Industry Academic Distinguish Professor. He is currently serving as an Associate Editor for the IET Generation, Transmission & Distribution journal.

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Title : Discriminative Pose-Free Descriptors for Face and Object Matching
Speaker : Soubhik Sanyal
Advisor: Dr. Soma Biswas
Date : 27/01/2017
Venue : C 241 MMCR, EE
Abstract: Matching faces and objects across pose is a very important area of research in the field of computer vision with many applications. For example, in surveillance setting, the face of a person captured by the overhead cameras may be in any uncontrolled pose and resolution as opposed to the frontal image under high resolution that is typically captured during enrolment. For object matching, the images captured during testing can be taken from a different viewpoint compared to the images stored in the database which again requires comparing objects present in different poses. In this talk, we will discuss about a discriminative pose-free descriptor (DPF-SPR) which can be used to match faces/objects across pose variations.
Speaker bio: Soubhik Sanyal completed his Bachelor’s from Jadavpur University, Kolkata in the year 2013. He is currently pursuing his M.Sc(Engg.) from Dept. of Electrical Engineering, Indian Institute of Science, Bangalore. His research interests are in computer vision, machine learning and image processing.

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Title : Polymeric Insulators for High Voltage Transmission Line
Speaker : Alok Ranjan Verma
Advisor: Dr. Subba Reddy B
Date :20/01/2017
Venue : C 241 MMCR, EE
Abstract: In modern era of upcoming industrialization, with the high consumption of electric energy it is very much important to achieve the required demand in power sector for the uninterrupted operation. The continuous availability of electric power is a major factor to fulfill the requirement, which can be achieved by the efficient, safe and reliable power transmission system supported by an effective insulation system. The insulation in over head transmission line (OHTL) is provided by porcelain and glass insulators conventionally but now a days recent advancement in materials lead to polymeric or non ceramic insulating materials. These polymeric insulators are composed of Polydimethylsiloxane (PDMS) as base polymer with different fillers like silica or Alumina trihydrate (ATH) to improve their material properties. There are several advantages of using polymeric insulators like easy manufacturing process, light weight, better mechanical properties, better hydrophobicity, better short term pollution performance etc., but major disadvantage is the penetration of moisture, also being organic in nature it is sensitive to environment and degrades with time by itself. In the present work, efforts are made to understand the behaviour of polymeric insulators material degradation under different environmental conditions (including acid rain condition) and their electrical behaviour against tracking and erosion using Inclined plane tracking method and accelerated aging studies using rotating wheel and dip test arrangement. Some preliminary results are discussed.
Speaker bio: Alok Ranjan Verma born in Aligarh, Uttar Pradesh, India in 1991. He received his B.Tech (Electrical Engineering) from Aligarh Muslim University, Aligarh, Uttar Pradesh and M.E. (Electrical Engineering) from Indian Institute of Science, Bangalore, Karnataka in 2012 and 2014 respectively. He is currently working towards his Ph.D. in High Voltage Engineering from Indian Institute of Science, Bangalore , Karnataka. His areas of interest includes, High Voltage Engineering, Polymeric Insulators for Outdoor Applications, , Computational Electromagnetism, Numerical Techniques in Electrostatics, Lightning Induced disturbances, Over-voltages in power systems.

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Title : Convolution Neural Network(CNN) applications in computer vision, tracking, and rotation invariant classification
Speaker : Prof. Deepak Mishra
Date :13/01/2017
Venue : C 241 MMCR, EE
Abstract: This lecture is aimed to discuss two recent work in application of CNN for computer vision tracking and rotation invariant classification. In the first part of talk I will discuss the CNN application to fast robust visual tracking. In the year 2015 at visual object tracking (VOT) challenge 2015 MultiDomain Network (MDNet) tracker stood as the first tracker in most of the real world challenges and this novel application of CNN/deep learning motivated us to attempt some improvements in the existing MDNet and We had modified the fine tuning part of the guided MDNet by reducing the number of samples used for the fine tuning. This had helped us in decreasing the time to a good extent. In second part I will discuss the work on Convolutional neural networks for rotational invariance classification. are one of the most widely applied deep learning architectures. They extract deep, hierarchical features from the input image, which are robust to scale changes and small distortions in the input, but are sensitive to rotations. We put forward an architecture which provides rotational invariant classification, even when it is trained only with data of single orientation. The proposed idea is then applied to three tasks, namely: handwritten digit classification, captcha recognition and texture classification. Moreover, along with rotational invariant classification, without any additional computational complexity, the proposed architecture is able to determine the approximate orientation of the object in the image.
Speaker bio: Prof. Deepak Mishra received his B.E., in Electrical Engg. (2000) and M Tech in Instrumentation (2003) from Devi Ahilya University Indore, Dr. Mishra pursued his PhD at IIT Kanpur (2007) in the Electrical Engg. Department. His Thesis title was “Novel Biologically Inspired Neural Network Models”. Later He joined as a postdoc researcher at University of Louisville, KY, USA in the field of signal processing and system neuroscience. After a brief stint 2009-2010 as a senior software engg at CMC limited Hyderabad. He opted to work as a academic faculty at Indian Institute of Space Science and Technology Trivandrum in 2010 and continued to work as Associate Professor in the department of Avionics. He is responsible for both research and teaching UG and PG students moreover he was coordinator for Mtech program in Digital Signal Processing and developed a Virtual Reality center of excellence during his stay at IIST. He was also awarded Young Scientist award from System Society of India for his research work in the year 2012. His research interest includes Neural networks and Machine learning, Computer vision and Graphics, Image and Video processing. He has published research papers both in International and National Journal of repute and presented his research work in various international and national conferences.

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Title : Cross-scale predictive dictionaries
Speaker : Vishwanath Saragadam
Date :10/01/2017
Venue : C 241 MMCR, EE
Abstract: Sparse representation, where a signal is represented using a linear combination of a few basis elements presents a promising framework for various image processing and computer vision tasks such as denoising, compression, and recognition. Sparse representation is also used for compressive sensing, where a signal is recovered from far fewer measurements than the signal dimension. Though analytical bases for sparse representation for arbitrary signals is hard to find, over-complete bases or dictionaries, which have more basis elements than the signal dimension are good alternatives. However, for high dimensional signals such as videos, very large dictionaries are needed which take significant time for computation. We propose a novel signal model, based on sparse representations, that captures cross-scale features, particularly for visual signals. We show that cross-scale predictive model enables faster solutions to sparse approximation problems. This is achieved by first solving the sparse approximation problem for the downsampled signal and using the non-zero indices of the solution to constrain the non-zero entries at the original resolution. The speedups obtained are especially compelling for high-dimensional signals that require large dictionaries to provide precise sparse approximations. We demonstrate speedups in the order of 10 − 20× for denoising and up to 15× speed-ups for compressive sensing of images and videos.
Speaker bio: Vishwanath is a third year PhD student in the ECE department at Carnegie Mellon University, Pittsburgh. He holds B.Tech (Hons.) From Indian Institute of Technology Madras in electrical engineering. Vishwanath works on compressive sensing and computational photography. His work is directed at reducing sensing and computational load of various cameras through novel signal models and algorithm design.

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Title : High Speed Solutions for Power System Operation
Speaker : R. Gnanavignesh
Advisor: Dr. U. Jayachandra Shenoy
Date :06/01/2017
Venue : C 241 MMCR, EE
Abstract: With increasing dependency on electricity for day to day activities, reliability of the electric power system has become imperative. The talk starts with a brief discussion on blackouts and an intuitive explanation of power system security. The role of Supervisory Control and Data Acquisition/Energy Management System (SCADA/EMS) will be highlighted. Subsequently, the challenges in operating the system in a secure manner will be looked upon. Finally, the on-going work regarding speeding up of power flow - an essential component of SCADA/EMS will be presented.
Speaker bio: R.Gnanavignesh completed his Master's from National Institute of Technology, Tiruchirapalli. He is currently pursuing his PhD from the Dept. of Electrical Engineering, Indian Institute of Science, Bangalore. His research interests are Power System Analysis, Dynamics and Control, High performance computing for power system applications.

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Title : A Deconvolution Based Approach for Feature Enhancement in Cryo Scanning Transmission Electron Tomograms
Speaker : Barnali Waugh
Date : 11/01/2017
Venue : C 241 MMCR, EE
Abstract: Electron tomography is a technique of choice for 3D imaging of subcellular objects. Recently it was demonstrated that scanning transmission electron microscopy (STEM) could be combined with cryo tomography to image whole unstained bacteria and human tissue culture cells, providing fine contrast and detail. However, tomograms contain only partial information about the specimen. This leads to characteristic distortions in the 3D reconstruction. Prior knowledge of the image formation mechanism, which is particularly simple in STEM permit amelioration of these distortions. In this talk I will describe a deconvolution based feature enhancement technique for cryo STEM tomograms and a few case studies with gold nano beads and biological specimens.
Speaker bio:

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Title : REAL VIRTUALITY: SPACE TRAVELERS
Speaker :Caecilia Charbonnier
Date :16/01/2017
Venue : C 241 MMCR, EE
Abstract: Real Virtuality is a multi-user immersive platform combining a 3D environment – which can be seen and heard through a VR headset – with a real life stage set. Users are tracked by a motion capture system allowing them to see their own bodies and move physically in the virtual environment. The experience offered by Real Virtuality brings a once in a lifetime experience. Unlike other static position VR systems, Real Virtuality allows users to become immersed in a VR scene by walking, running, interacting with physical objects and meeting other people. Because user’s movement exactly match their avatars movements in the 3D environment and are streamed to the users with very low latency, there is no discomfort or interface required. The bodies of the visitors become the interface. This ground breaking technology is issued from fundamental research undertaken in the last four years by the Artanim Foundation. It is the only solution available today offering a “matrix-like” degree of immersion over a large area, up to hundreds of square meters. This work was selected among the three finalists of the Immersive Realities (AR/VR) contest at SIGGRAPH Los Angeles 2015, awarding the best augmented/virtual reality experiences possible using today’s technologies. It was selected at the Sundance film festival and presented at Cannes Festival in 2016. This project was also awarded the Laval Virtual 2016 award in the category “3D game and entertainment”. VIDEO LINKS: “Space Travelers” https://www.youtube.com/watch?v=kxW5H4xj1kA
Speaker bio: Caecilia Charbonnier obtained a Master of Advanced Studies (MAS) in Computer Graphics at EPFL and a PhD degree in Computer Science at MIRALab - University of Geneva. She is currently President and Research Director at Artanim. Her work focus on the interdisciplinary use of motion capture from 3D animation, VR applications, live performances to movement science, orthopedics and sports medicine. (Paralinguistics/Cognitive Load) and in 2015 (Non-nativeness detection). She has published over 700 papers and has been granted 17 U.S. patents.


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Title : Glottal source modeling in text to speech synthesis
Speaker :Achuth Rao M V
Advisor: Dr. Prasanta Kumar Ghosh
Date : 30/12/2016
Venue : C 241 MMCR, EE
Abstract: One of the major factor which causes a deterioration in speech quality in text to speech synthesis is the use of a simple delta pulse signal to generate the excitation of voiced speech. There are several methods proposed to model the glottal source of speech like Liljencrants Fant and Rosenberg models. But these models has limitations such as non-convex estimation methods and higher synthesis time. We propose a new glottal models based on incomplete beta function. The objective scores shows that the proposed model is better than the Liljencrants Fant model and has few number of parameters.
Speaker bio: Achuth Rao MV received his BE degree in Electronics and Communication Engineering from RV college of Engineering Bangalore. He is currently a PhD student in Dept. Of Electrical Engineering at IISc. His research interests broadly include Speech processing, Pattern recognition and bio-medical signal processing.

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Title : Switched Reluctance Machine Drive
Speaker :Syed Shahjahan Ahmad
Advisor: Prof. G. Narayanan
Date :23/12/2016
Venue : C 241 MMCR, EE
Abstract: High speed electrical machines find applications in power generation, gas compressors and precision machining among others. The switched reluctance machine (SRM) is a potential candidate for high speed turbo-alternator, given its robust rotor with no permanent magnets or conductors. However, the machine is highly non-linear and challenging to control. In this presentation, the basic working of the SRM and its challenges will be described. Existing methods for current control along with proposed methods will be discussed and compared. Theoretical and experimental studies carried out on SRM in generating mode will be presented.
Speaker bio: Syed Shahjahan Ahmad received the B.E degree in Electrical Engineering from Indian Institute of Engineering Science and Technology, Shibpur in 2012, and M.E. degree in Electrical Engineering from Indian Institute of Science, Bangalore in 2014. He is currently pursuing his Ph.D. at the Indian Institute of Science, Bangalore, in the Department of Electrical ngineering. His research interests include design and control of switched reluctance machines, high speed electric drives, power electronic converters, and modelling and control of power electronic systems.

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Title : Motors for Electric Vehicles - Part II
Speaker :Prof. K. Ragavan, IIT-Gandhinagar
Advisor: Motors for Electric Vehicles - Part II
Date :15/12/2016
Venue : HV Seminar Hall
Abstract: This is continuation of the talk that was given on Dec 6, 2016. In Part-I, basics of vehicle load requirement were discussed. Further, it is well known that it is possible to alter the terminal characteristics of a motor by altering the supply characteristics. However, few aspects are to be considered while selecting a motor for electric vehicles. Those are: power density, maintenance, extended speed range, high performance, etc. With regard to power density, the preferred choice is a Permanent Magnet motor (popularly called brushless DC motor). Details about making this choice will be discussed.
Speaker bio: Dr Ragavan K, Associate Professor, Electrical Engineering, IIT Gandhinagar  did his B.Tech. in Electrical and Electronics Engineering (1993-1997) from Pondicherry Engineering College, Pondicherry and his M.E. in Power Electronics and Drives (2000-2002) from College of Engineering Guindy, Chennai. Later, he received his Ph.D. degree from Department of Electrical Engineering, Indian Institute of Science, in 2006. After completing Ph.D., he worked in GE India Technology Centre Private Limited, Bangalore as Research IP Professional and Research Engineer (Jan. 2007 – Feb. 2009). Then, he joined Indian Institute of Technology Gandhinagar (Electrical Engineering) in May 2009. His research interests are condition monitoring of transformer, design of rotating electrical machines and drives for electric vehicle applications.

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Title : Adaptive Sampling Pattern Design Methods for MR Imaging
Speaker :Chennakeshava K
Advisor: Prof. K Rajgopal
Date :16/12/2016
Venue : C 241 MMCR, EE
Abstract: Magnetic Resonance Imaging is a non-invasive and non-ionizing medical imaging modality having multiple utilities. The scan time involved with MRI is higher and there is necessity to reduce it to avoid the discomfort caused to the patients undergoing the scan. One of the methods to reduce the scan time has been to develop suitable sampling patterns. Sampling patterns represent the indices from which the k-space data is collected. The talk discusses the development of adaptive sampling patterns which consider the k-space behavior, by formulation of a Knapsack problem. A cost function indicative of the energy captured by the sampling patterns is defined, and comparison of reconstruction metrics at several undersampling ratios of different sampling patterns will be shown. A brief discussion explaining the unique patterns of k-space energy distribution in MR Images, and its utility will be discussed.
Speaker bio: Chennakeshava completed his Bachelor’s from Sri Jayachamarajendra College of Engineering, Mysore, worked with Robert Bosch Engineering Solutions, Bangalore and is currently pursuing his M.Sc (Engg.) from the Dept. of Electrical Engineering, Indian Institute of Science, Bangalore. His research interests include Medical Imaging, Machine Learning, and Image Processing.

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Title : Making Sense of Real life observations in the Indian Grid and Waveform Relaxation Method for in-situ testing of Power System/Power Electronic Controllers
Speaker : Prof. Anil Kulkarni
Date : 09/12/2016
Venue : C 241 MMCR, EE
Abstract: a) Making Sense of Real life observations in the Indian Grid: Classical power system dynamic phenomena like unstable swings, loss of synchronism and system frequency changes have been studied extensively in the past. The advent of synchronized wide-area measurement systems has made real-life observations of system wide dynamics easily accessible to the power system community. While many of these observations are a “mere” confirmation of what has been known in theory, some do require more than a cursory examination. In this talk, some interesting real-life observations will be presented and related issues will be discussed.

b) Waveform Relaxation Method for in-situ testing of Power System/Power Electronic Controllers: An alternative to real-time simulation for hardware-in-the-loop testing is presented. This involves system simulation, not necessarily done in real time, and real-time playback of the simulated output to the controller under test. The time-stamped controller output is stored and subsequently fed as an input to the simulation. This whole process is done iteratively as in the Waveform Relaxation method, till the waveforms converge. This method can be used for testing multiple and dispersed controller hardware and the associated communication equipment, e.g., wide-area measurement based control and system protection schemes. It also has the potential to be an alternative to real-time simulators which are expensive when large systems have to be simulated. The basic scheme and potential applications are discussed.


Speaker bio: Prof. Anil Kulkarni received B.E. degree in Electrical Engineering in 1992 from the University of Roorkee.Received M.E in 1994, and Ph.D degree in Electrical Engineering in 1997, from IISc Bangalore. He is currently working in Department of Electrical Engineering, IIT bombay. HIs research Interests are Power System Dynamics, Flexible AC Transmission Systems, HVDC Transmission Systems.

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Title : Standards and Their Impact on Future R&D in Electric Motors, Drives and Control
Speaker :Prof. Krishnan Ramu
Date :09/12/2016
Venue : C 241 MMCR, EE
Abstract: On going efforts in international and national standards agencies in the area of line operated electric motors and converter operated electric motors (also known as variable speed motor drives or simply as motor drives) have many impacts. They draw the attention of a handful of engineers in the world and, surprisingly, it is an understatement. The standards have immense impact on many practical aspects such as efficiency, testing and selection and application in the industries, offices and as well as in homes. Consider only efficiency standards, usually known as minimum energy performance standards (MEPS), and say their enforcement which results in very significant energy savings and hence in a reduction in operational costs to the consumer and industries.An inexorable march of the standards towards higher efficiencies requires continuous research and development efforts to deliver them. Higher efficiency electric motors come at the expense of additional cost due to redesign with much more materials than that of the lower efficiency motors. The presentation highlights the International Electro technical Commission’s (IEC) standards on electric motors both in force and evolving ones and their impact with concrete examples on the incremental initial investment in adoption of higher efficiency standard motors and their payback period, resulting energy savings, and life cycle operational cost savings. The benefits of higher efficiency standards are demonstrated. The key to all these developments is the basic and applied research in electric machines, converters and control. Newer opportunities to face these challenges are in the design and development of newer electric motors as well asknown class of machines in the newer configurations, converters and their operation, and finally in the software control integration of the motor and converter for high efficiency operation. Some possible directions are also identified here. Note that the R&D efforts lead the entrepreneurship that may follow when these areas of research result in innovation with cost effective ways to realize the motors, converters and control can be put to production and into the practice.
Speaker bio: R. Krishnan is a professor of electrical and computer engineering at Virginia Tech, Blacksburg, VA. He is currently the director of the Center for Rapid Transit Systems in linear and rotating motor drives. His research interests are in electric motor drives, electric machines, power electronics and control. Krishnan is a recipient of best paper prize awards from IEEE Industry Applications Society’s Industrial Drives committee (5 awards) and Electric Machines committee (1 award). In addition, he received the first prize from IEEE Transactions on Industry Applications for his paper and the 2007 Best Paper Award from IEEE Industrial Electronics Magazine. His co-edited book Control in Power Electronics won the best book award from Ministry of Education and Sport, Poland, in 2003. He was awarded IEEE Industrial Electronics Society’s Dr. Eugene-Mittelmann Achievement Award for Outstanding Technical Contributions to the field of Industrial Electronics in 2003. Krishnan is a Fellow of the IEEE and a Distinguished Lecturer of IEEE Industrial Electronics Society.

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Title : Motors for Electric Vehicles
Speaker :Prof. K. Ragavan
Date :06/12/2016
Venue : HV Seminar Hall, EE
Abstract: Pollutants from engine powered vehicles can be eliminated with the use of motor driven vehicles. The motor that was preferred for vehicle applications is now being replaced. This change has become possible due to developments in semiconductor devices. With the use of high energy density permanent magnets, the power density of the motors can be improved. For extending the speed-range of the motor beyond base-speed, the air-gap flux has to be reduced. Is it possible to achieve such flux weakening operation with permanent magnetmotors? Reluctance motors are preferred due to its simple constructional features. The torque produced by reluctance motors has higher ripple and produces more acoustic noise. Instead of dissipating kinetic energy by mechanical brake, it can be converted to electrical form and stored in the batteries (regenerative braking). All these aspects will be discussed.
Speaker bio: Dr Ragavan K, Associate Professor, Electrical Engineering, IIT Gandhinagardid his B.Tech. in Electrical and Electronics Engineering (1993-1997) from Pondicherry Engineering College, Pondicherry and his M.E. in Power Electronics and Drives (2000-2002) from College of Engineering Guindy, Chennai. Later, he received his Ph.D. degree from Department of Electrical Engineering, Indian Institute of Science, in 2006.After completing Ph.D., he worked in GE India Technology Centre Private Limited, Bangalore as Research IP Professional and Research Engineer (Jan. 2007 – Feb. 2009). Then, he joined Indian Institute of Technology Gandhinagar (Electrical Engineering) in May 2009. His research interests are condition monitoring of transformer, design of rotating electrical machines and drives for electric vehicle applications.

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Title :Advanced Approaches to Renewable Energy Integrated Power System Modeling and Energy Management
Speaker :Dr. Sudipta Ghosh, Shiva Nadra University, Delhi
Date :28/11/2016
Venue : C 241 MMCR, EE
Abstract: Modern power grid is more complex and shows unforeseen dynamics. Rapid control decisions have to be taken on the basis of multiple contingency evaluations using limited computational resources. Such analyses are time consuming, exceeds computational limits and difficult to accomplish in faster time frames. Model order reduction (MOR) is one such tool in control engineering which can simplify system formulations while retaining phenomena of interest. This work shows 1) a new approach for coherency identification that captures dynamic behavior of the power grid, 2) a new methodology for scalable power system coherency grouping based on mathematical (BT & Krylov subspace) MOR of larger power grid including online PSS tuning methodology. Further the work explains reduced order modeling of wind turbines & wind farms. The work also describes 1) a new wind farm control framework for inertial and primary frequency response for a high wind integrated power system, 2) an energy function based optimal control strategy for output stabilization of integrated DFIG-flywheel energy storage architecture to avoid voltage and power fluc­tuations, 3) a new dynamic reactive power estimation based coordinated control of grid integrated DFIGs to improve network stability. Further a real-time model reduction of large power grid into an equivalent network while preserving low and high frequency behavior of the original system will be presented.
Speaker bio: Sudipta Ghosh received his Ph.D. degree from Indian Institute of Technology, Delhi in 2013 in Power Systems. From 2013-2014, he worked as Assistant Professor at IIT, Dhanbad. In 2014 he came to USA as a Research fellow at the University of North Carolina (UNCC), at Charlotte. He was a lead researcher for the Hybrid real time simulator based advance modeling of the Southern California Edison grid. He also worked as a lead researcher for the NSF funded project on power system on new methods of optimal control designs integrating renewable energy systems research. Next year, he was appointed as Graduate Associate Faculty at UNCC. In this context he was assisting PhD and Master’s students and also working on a NSF project. He has just joined Shiv Nadar University as an Assistant Professor. He has 7 years teaching/research experience and 3 years industrial experiences. He is a member of the IEEE and IEEE PES. He was in Student Program Committee for NAPS (North American Power Symposium) 2015. His publication record consists of nine journals and seven conference papers (total 292 google scholar citations). He received the National Scholarship in 1995 and POSCO power system Award from Power Grid in 2014.

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Title :Principles and Design of a system for Academic Information Retrieval based on Human-Machine Dialog
Speaker :Prof. Hiroya Fujisaki
Date :24/11/2016
Venue : C 241 MMCR, EE
Abstract: This talk describes the outcome of a successful national project led by Fujisaki under the “Research-for-the-Future” program, The system is based on the following three original features: (1) Use of “Key Concepts” in information retrieval (including processing of polysemy, homonymy, and unknown words), (b) Dialogue Management based on both User and System Modeling (by introducing a novel type of interacting automaton), and (c) Optimization of Retrieval Performance through Relevance Score Estimation.
Speaker bio: HIROYA FUJISAKI is a Professor Emeritus at the University of Tokyo and a Professor in the Department of Applied Electronics at the Science University of Tokyo. In 1991, he retired as a Professor of Electrical Engineering from the Univ. of Tokya and took on his current appointments. His research in speech and language processing covers a broad range of topics, including production, perception, acquisition, impairment, analysis, synthesis, coding, and recognition. His work on mathematical and physical modeling has led to the development of models of language use, models for perceptual processes in speech identification and discrimination and models for the process of fundamental frequency control in speech. He also developed a model of road traffic flow which has been applied to road traffic control since the 1970s. Among his many honors, Professor Fujisaki is an Honorary Member of the Acoustical Society of Japan (ASJ) and a Fellow of the Acoustical Society of America (ASA) and of the Institute of Electronics, Information and Communication Engineers (IEICE). He has been honored by the Mayor of Tokyo as a "Person of Merit in Science and Technology", and has received The Third Millennium Medal from the Institute of Electrical and Electronics Engineers (IEEE).

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Title : Problems and Prospects of spoken Language Processing
Speaker : Prof. Hiroya Fujisaki
Date :24/11/2016
Venue : C 241 MMCR, EE
Abstract: Instead of the conventional distinction between “Speech” and “Language”, Fujisaki introduced the concepts of “Spoken Language” as contrasted to “Written Language”, pointing out that speech contains certain linguistic information that is not in the written language. He also made clear that what has been traditionally called “Natural Language Processing” is actually “Written Language Processing”, and defined the field of “Spoken Language Processing,” dealing with both the aspects of speech as a signal and its aspects as a code. This talk describes the rationale that led to this conceptual turn, and shows the progresses, unsolved problems and future prospects of the field.
Speaker bio: HIROYA FUJISAKI is a Professor Emeritus at the University of Tokyo and a Professor in the Department of Applied Electronics at the Science University of Tokyo. In 1991, he retired as a Professor of Electrical Engineering from the Univ. of Tokya and took on his current appointments. His research in speech and language processing covers a broad range of topics, including production, perception, acquisition, impairment, analysis, synthesis, coding, and recognition. His work on mathematical and physical modeling has led to the development of models of language use, models for perceptual processes in speech identification and discrimination and models for the process of fundamental frequency control in speech. He also developed a model of road traffic flow which has been applied to road traffic control since the 1970s. Among his many honors, Professor Fujisaki is an Honorary Member of the Acoustical Society of Japan (ASJ) and a Fellow of the Acoustical Society of America (ASA) and of the Institute of Electronics, Information and Communication Engineers (IEICE). He has been honored by the Mayor of Tokyo as a "Person of Merit in Science and Technology", and has received The Third Millennium Medal from the Institute of Electrical and Electronics Engineers (IEEE).

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Title : Microgrids-Operation and Control Issues
Speaker : Dibakar Das
Advisor: Dr U Jayachandra Shenoy & Dr Gurunath Gurrala
Date : 25/11/2016
Venue : C 241 MMCR, EE
Abstract: With the increased popularity of non-conventional energy sources like wind, solar, etc, the conventional electrical grid has undergone some major transformations in the past few years. This talk discusses one such transformation, the microgrids. A microgrid is a collection of distributed sources along with loads which can operate with the main grid as well as in the absence of grid. This talk discusses some of the recent developments in the field and some of the major control challenges. The operating modes of the microgrids will be discussed in detail. Finally, the concept of seamless transfer will be introduced and a linear quadratic regulator theory based seamless transfer algorithm will be briefly discussed.
Speaker bio: Dibakar Das completed his Bachelor’s from National Institute of Technology, Durgapur in the year 2014. He is currently pursuing his M.Sc (Engg.) from Dept. of Electrical Engineering, Indian Institute of Science, Bangalore. His research interests are power electronics, renewable integration and microgrids.

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Title :Brain and Health
Speaker :Prof. A. G. Ramakrishnan
Date :18/11/2016
Venue : C 241 MMCR, EE
Abstract: The talk will start with an interesting demo of a crystal ball, that can receive the intentions of the holder and make linear and circular movements. It will also cover the largely unknown fact of the intimate connection between oxygen shortage and cancer (Nobel Prize work of Otto). By demonstrating that we have conscious control over our blood flow (biofeedback), the strong connection between one’s thoughts and health will be made clear. How we can make use of the miraculous mechanisms of the body for self-healing. How to prevent cancer with simple antiangiogenic fruits & vegetables? How our genes are NOT our fate and DNA is NOT our identity (epigenetics). The 4 golden rules for a disease-free life. How we can we make use of the non-visual photoreceptors in our retina. The final aim of the talk is to establish that it is possible for anyone to accelerate towards great positive health, by following rather simple steps of eating, breathing and sleeping: more than what to eat, focus on how to eat. The speaker himself is a demonstration of the ideas he is forwarding: After being dependent on medicine for keeping his hypertension under control for over nine years, he has been able to bring back normal blood pressure by following some of these steps and is completely free of his medicine for the past six months, with no diet control !
Speaker bio: A G Ramakrishnan obtained his Ph D in Biomedical Engineering from IIT Madras. For his work on nerve conduction in leprosy, he received the Sir Andrew Watt Kay Young Researcher’s Award from the Royal College of Physicians and Surgeons, Glasgow. He has collaborated and jointly published with Padmashri Dr. H R Nagendra (Director of Sri Vivekananda Yoga Anusandhana Samsthana), Prof. B N Gangadhar, Director of NIMHANS and Dr. S Suresh, Director of Fetal Care Research Foundation. He has graduated 25 research students so far. He was the President of Biomedical Engineering Society of India. Blind students are using over 600 Braille books in Tamil, converted from printed books using his OCR, Mozhi Vallaan. This work earned him the Manthan Award 2014 - South Asia and Asia Pacific in the category e-inclusion and accessibility. He has developed unrestricted vocabulary, handwritten word recognition system in Tamil, for which he received Prof. M Anandakrishnan award from INFITT in 2013. He has also developed Thirukkural and Madhura Vaachaka - good quality text to speech conversion software for Tamil and Kannada, used by blind students, for which he received the Manthan Award 2015 in the e-education category. He conceived of Linguistic Data Consortium for Indian Languages, currently managed by CIIL, Mysore.

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Title :Large-scale Sensor Network Localization
Speaker :Rajat Sanyal
Advisor: Dr. Kunal Narayan Chaudhury
Date :11/11/2016
Venue : C 241 MMCR, EE
Abstract: Recent developments in wireless communications and electromechanics have proliferated the deployment of wireless sensor networks. While such networks are typically used to monitor different physical quantities over a region, they are also used in surveillance and disaster management. A fundamental computational problem in this regard is to estimate the distribution of the entire sensor network from the available inter-sensor distances (estimated using local communication links). In this talk, I will give an overview of our recent work on large-scale sensor network localization.
Speaker bio: Rajat Sanyal (GM’ 16) received the B.Tech. in electronics and communication engineering from National Institute of Technology, Durgapur, WB, India, in 2014. He is currently pursuing his M.Sc. (Engg.) in electrical engineering from Indian Institute of Science, Bangalore, KA, India. He is working on large-scale sensor network localization problem. His research interests broadly include convex optimization, wireless communication and machine learning.

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Title : Hybrid grid-tie inverters for back-up power applications
Speaker : Venkatramanan D
Advisor: Prof. Vinod John
Date : 04/11/2016
Venue : C 241 MMCR, EE
Abstract: Energy demand increases continually. Renewable energy based distributed generation (DG) systems are gaining popularity today as they address the growing energy demand. Particularly, solar photo-voltaics (PV) based grid-tie inverters (GTI) are available in the market for a range of power levels. However, the GTI system, by design, would function only in the presence of power grid and would remain idle in the event of a power outage. In this work, a hybrid GTI configuration is presented, which by applying appropriate control, would function even in the absence of grid and cater to local power needs, thus providing back-up power while accessing renewable energy.
For realizing such a hybrid GTI functionality, a flexible power converter system is required. Hence, focus is laid on design of power converters, where a procedure suggested that is both simple and state-of-the-art. Details of the hardware platform developed in laboratory are presented that can cater to a variety of power conversion applications. Experimental results are presented that illustrate the high performance that is achieved with the power converter.

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Title : Stability of Electric Gird: Challenges and Solutions
Speaker : Ajit Kumar
Advisor: Dr. G. Gurrala and Dr. I. Sen
Date : 28/10/2016
Venue : C 241 MMCR, EE
Abstract: Power systems are large complex systems which are highly nonlinear and high order system. Security of a power system is affected by characteristics of the physical systems. It is mainly affected by integrated generation, transmission and distribution. Different form of instability includes rotor angle, voltage and frequency instability.

In this talk, we will focus on rotor angle instability of electric grid. This form of instability is mainly caused by inter-area and local modes of oscillations among generators. Inter-are modes are of low frequency and involve large geographical areas, limiting the transmission capacity of tie-line between two large areas. Since power equipment’s are manufactured to operate in a specified range, voltage regulation (AVR) is required for system operation. Since AVR action affects local and inter-area modes damping. Traditionally, damping controllers are used to enhance the damping performance of these modes.

We will present damping controller design using local measurements. Furthermore, a nonlinear AVR design is discussed based on differential geometric theory. We will show that the nonlinear AVR damp inter-area modes better than conventional AVRs, paving the way for more power transfer across areas.

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Title : Dictionary Learning for Matching Data Under Cross-Modal and Privileged Information Scenarios
Speaker : Devraj Mandal
Advisor: Dr. Soma Biswas
Date : 21/10/2016
Venue : C 241 MMCR, EE
Abstract: Cross-modal recognition and matching with hidden information are important challenging problems in the field of computer vision. The cross-modal scenario deals with matching across different modalities and need to take care of the large variations present across and within each modality. The hidden information scenario deals with the situation that all the information available during training may not be available during the testing stage and hence algorithms need to leverage the extra information from the training stage itself. Though separate algorithms have been designed to specifically handle the two situations efficiently, there is a lack of single joint framework which is able to handle the two problems concurrently. We show that for multi-modal data, either one of the above situations may arise if one modality is absent during testing. Here, we propose a novel joint framework which can handle both these scenarios seamlessly with applications to matching multi-modal data. The proposed approach jointly uses the data from the two modalities to build a canonical representation which encompasses the information from both the modalities. We explore three different types of canonical representation for different types of data. The algorithm computes dictionaries for the data from both the modalities and the canonical representation, such that, the transformed sparse coefficients of both the modalities are equal to that of the anonical representation. The sparse coefficients are finally matched using a metric learning algorithm. Extensive experiments on different datasets, involving RGBD, text-image, audio-image data show the effectiveness of the proposed framework.
Speaker bio: Devraj Mandal received the B. Tech degree in Electronics & Communication Engineering from West Bengal University of Technology, Kolkata, in 2011 and the M. Tech degree from Jadavpur University, Kolkata, in 2014. He is currently a doctoral student in the Department of Electrical Engineering, Indian Institute of Science, Bangalore, India. His research interests are in image processing, computer vision, and pattern recognition.

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Title :Detection of significant transitions and estimation of glottal closure instants in a speech signal
Speaker :K V Vijay Girish
Advisor: Prof. A G Ramakrishnan
Date :14/10.2016
Venue : C 241 MMCR, EE
Abstract: A unsupervised acoustic-phonetics knowledge based approach is used to detect transitions between broad phonetic classes in a speech signal. This has applications such as landmark detection and segmentation. A rule-based approach using relative thresholds learnt from a small development set is devised to detect transitions of silence to non-silence, sonorant to non-sonorant and vice-versa. This approach does not require significant training data for determining the parameters of the proposed approach. When tested on the entire TIMIT database for clean speech, 93.6% of the detected transitions are within a tolerance of 20 ms from the hand-labeled boundaries. The proposed method is also tested on the test set of the TIMIT database for robustness with respect to white, babble and Schroeder noise, and about 90% of the detected transitions are within a tolerance of 20 ms at a SNR of 5 dB. As another part of my work, I have proposed subband analysis of linear prediction residual (LPR) to estimate the Glottal Closure Instants (GCIs). It is evaluated using 6 different databases and compared with 3 state-of-the-art LPR based methods. The proposed method is comparable to the best of the LPR based techniques for clean and noisy speech.
Speaker bio: K V Vijay Girish graduated from National Institute of Technology Karnataka, Surathkal in 2008 with a B.Tech in Electrical and Electronics Engineering. He joined Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, India in 2010 and is pursuing PhD in the field of Machine Listening since then as a research student. His research interests include Machine Listening, Audio Source Separation, Speech Signal Processing, Audio and Speech Analysis, Image Processing and Pattern Recognition.

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Title :Industrial Plasma Technology: An Overview
Speaker :Anusuya Bhattacharyya
Advisor: Prof. B. S. Rajanikanth
Date :7/10/2016
Venue : C 241 MMCR, EE
Abstract: Plasmas make up more than 99% of the visible matter in the universe, and it mainly consists of positive ions, electrons and neutral particles. Whereas natural plasmas have been the object of scientific studies right from the 17th century, the twentieth century has witnessed rapid progress in the development, diagnostics and applications of plasma. This talk will include an introduction to low temperature plasma technology and various types of plasma discharges such as pulsed corona discharge, dielectric barrier discharge, surface discharge, glow discharge (low pressure discharge) and their properties. The latter part of the talk will discuss some case studies where these technologies have contributed, namely pollution control from diesel engines, wastewater treatment, biological applications and surface treatment of materials.
Speaker bio: Anusuya Bhattacharyya obtained her PhD from the Department of Electrical Engineering, Indian Institute of Science, Bangalore, India. Her research interests include application of electric discharges for pollution control in cascade with adsorbent/ catalytic materials and other plasma technology

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Title :Photovoltaic Energy Conversion Systems
Speaker :Pallavi Bharadwaj
Advisor: Prof. Vinod John
Date : 23/09/2016
Venue : C 241 MMCR, EE
Abstract: This talk covers several aspects of photovoltaic (PV) energy conversion, namely: irradiation measurement, static and dynamic modelling, and characterization of PV panels. The development of an electronic PV panel output characterisation hardware setup that offers the advantage of both static and dynamic panel measurements is presented. After system modelling, a case study on the effect of storage on the cost of grid-connected PV systems is analysed. Based on this study, given a grid outage scenario, a method to choose between grid-tied and dual mode PV systems is presented.
Speaker bio: Pallavi Bharadwaj is working towards her PhD degree in the department of Electrical Engineering at the Indian Institute of Science, Bangalore, India. Her research interests include development and control of power electronic systems for renewable energy applications and grid integration.

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Title :A Fast Approximation of the Bilateral Filter
Speaker : Sanjay Ghosh
Advisor: Dr. Kunal Narayan Chaudhury
Date :16/09/2016
Venue : C 241 MMCR, EE
Abstract: The bilateral filter is an edge-preserving smoother that has applications in image processing, computer vision, computer graphics, and computational photography. The direct implementation of the bilateral filter requires O(w^2) operations, where w is the width of the spatial kernel. In this talk, we will discuss a fast approximation of the bilateral filter which can cut down the complexity to O(1), without appreciably compromising the filtering quality.
Speaker bio: Sanjay Ghosh is working toward his PhD degree in electrical engineering at the Indian Institute of Science, Bangalore, India. His research interests broadly include inverse problems in imaging, computational photography, and computer vision.

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Title : Voltage Stability Analysis in Power Systems
Speaker : A Santosh Kumar
Advisor: Prof D. Thukaram
Date :09/09/2016
Venue : C 241 MMCR, EE
Abstract: This presentation gives a brief look at Voltage stability Analysis in power systems. Voltage instability has led to severe grid failures in recent past. Voltage instability is a phenomenon usually observed in heavily loaded systems. Maintaining a stability margin is very crucial for the system in case of any disturbance, to study this voltage stability analysis is done. This presentation will cover the following points briefly:
• Voltage stability causes and effects.
• Methods for voltage stability analysis: PV curves, VQ curves, Thevenin equivalent based and L-Index.
• Ways in which voltage collapse can be mitigated: VAR compensation.
• Using synchrophasors (PMU) for stability analysis.
• Issues with renewables integration from voltage stability point of view.
Speaker bio: Santosh is doing MSc(Engg) under Prof D. Thukaram at Dept. of Electrical Engineering, IISc Bengaluru. His research work is in the field of power systems voltage stability.

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Title : Braids of partitions
Speaker : Dr B Ravi Kiran
Date : 02/09/2016
Venue : C 241 MMCR, EE
Abstract: In this talk we focus on the problem of extracting an optimal partition from a hierarchy of partitions by dynamic programming. We look at conditions under which the dynamic programming (DP) gives an optimal solution, firstly by defining the conditions on the energy define over the partial partitions of the subset of the space, and secondly describing the partial ordering between partitions necessary to preserve the DP substructure. The talk further identifies various possible braids in literature and how this structure relaxes the segmentation problem. We shall show demonstrative examples of optimal cuts in the context of image segmentation. Given that there could be many solutions possible, we impose unique solutions and we define the necessary conditions for its existence. This uniqueness induces an ordering relation between partitions, and in this case a lattice structure (family of partitions with unique extremal elements). In this talk we shall also briefly review decision trees, decision forests and decision jungles and the creation of the partially ordered partitions of the feature spaces when creating these classifiers.
Speaker bio:
B Ravi Kiran has finished a PhD in computer science and mathematical morphology from Université Paris-Est, A3SI-LIGM in Oct 2014. Following this he worked in hyperspectral image processing for tumor detection at Mines ParisTech as Post-doctoral researcher in the European project Helicoid. Currently he is a Postdoctoral researcher at the DATA lab in ENS Paris, France, working on unsupervised time series anomaly detection.

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Title : Recurrent Neural Network and its Applications in Sequence Predictions
Speaker : Vidyadhar Upadhya
Advisor: Prof. P. S. Sastry
Date : 02/09/2016
Venue : C 241 MMCR, EE
Abstract: Numerous learning tasks which deal with sequential data cannot be modeled using standard feed forward neural networks because they assume that the training samples are independent. In such tasks, the dynamics of sequential data should be modeled explicitly. The recurrent neural networks (RNNs), however, can model the sequential data well by retaining a state that represents information from an arbitrarily long context window. In this talk, I will discuss briefly about different RNN architectures, issues involved in training them and some existing solutions. In addition, I will also present an application of RNN in medical diagnostics. Specifically, diseases such as pneumonia are characterized by abnormalities in respiratory signal, which is a physiological time series. In this context, I will explain the extraction of the respiratory signal, from videos acquired through a regular camera, using RNN.
Speaker bio: Vidyadhar received his MS degree in Electrical Engineering from the Indian Institute of Technology Madras. He is currently a PhD student in the Dept. of Electrical Engineering at IISc. His research interests broadly include Pattern Recognition, Deep Learning.

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Title : Image Restoration using Inverse Correlation based Roughness Minimization
Speaker : Mr. Sanjay Viswanath
Advisor:
Dr. Muthuvel Arigovindan
Date : 26/08/2016
Venue : C 241 MMCR, EE
Abstract: Image Restoration using regularization is highly popular topic of research in image processing. While the focal point of innovation has been general image priors as regularization functions, dictionary learning algorithms have shown the advantage of using training samples to build better priors for specific classes of images. However these techniques are generally based on sparsity prior and are computationally expensive. Inverse Correlation (IC) is proposed as a novel regularization method which incorporates learning in Total Variation(TV) prior through an IC matrix. The IC matrix is built from derivatives computed at each pixel of training images and consequently adapts to the structure for that class of images. The IC matrix is then used to formulate a convex non-quadratic IC cost function which retains the simplicity of derivative filter based general regularization schemes. We also propose a reconditioned gradient descent algorithm to minimize the IC cost function. The simulation results show that the IC regularization can adapt to training samples and yield better performance than general priors like TV.
Speaker bio:
Sanjay V. received his M Tech degree in Electronics and Communication Engineering (Signal Processing) from Indian Institute of Technology Guwahati. He is currently a PhD student in the Dept. of Electrical Engineering at IISc. His research interests broadly include Image Processing, Compressive Sensing, and Pattern Recognition.

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Title : Microgrid Energy Manager - A Platform for Plug-and-Play Management of AC/DC/Hybrid Microgrids
Speaker : Mr. Ashray G Manur
Date : 25/08/2016
Venue : C 241 MMCR, EE
Abstract: With the emergence of microgrids, deploying small-scale (micro) grids in homes, buildings and communities for reliable electricity access is becoming a viable option. This research introduces the concept of grid management at a home/building level called homegrids, managed by Homegrid Energy Manager (HEM) which works towards meeting local constraints and requirements. A group of homegrids are managed by a Microgrid Energy Manager (MEM) which takes care of overall grid management at a community level. Both HEM and MEM adapt a Plug-and-Play model and work with existing storage systems, inverters, appliances and other loads/energy sources. Capable of working with AC/DC or hybrid microgrids, MEM/HEM use a multi-layer approach to provide real-time control and intelligent management of energy sources and loads using embedded sensing and computing, wireless networks, internet-of-things and cloud-computing technologies.
Speaker bio: Ashray Manur is a PhD student at University of Wisconsin-Madison and a member of Wisconsin Electric Machines and Power Electronics Consortium (WEMPEC). He is advised by Prof. Giri Venkataramanan. Ashray’s research interests include microgrid management, cyber physical energy systems and IoT/cloud computing technologies for energy systems.

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Title : Manipulation and Interrogation of Matter at the Small Scale: A Control Systems Perspective
Speaker : Dr. Murti V. Salapaka
Date :19/08/2016
Venue : C 241 MMCR, EE
Abstract: New temporal and spatial regimes of exploration enabled by nanoscience and nanotechnology have led to significant insights into fundamental processes that govern dynamics at the small scale of matter including bio-matter at the molecular scale. These abilities were enabled by breakthroughs in instrumentation that had to overcome fundamental sources of uncertainty such as thermal noise. In this talk, the primary challenges to nanoscale interrogation and manipulation will be presented in a systems perspective. Here, solution methodologies enabled by a modern control approach will be highlighted. With the exploration of biological processes at the molecular and cellular scale using nano-interrogation tools, it has become evident that evolution has endowed biology with remarkable machinery to perform and achieve precise functionality at the small scale in the presence of a highly uncertain environment. Understanding these bio-molecular systems, apart from providing key insights into biology and the related therapeutic impact, holds the promise for strategies to engineer material and systems at the small scale. Recent efforts into probing and understanding transport at the molecular scale and key proteins that provide structural integrity will be detailed to showcase the power of a control systems perspectives.
Speaker bio:
Murti V. Salapaka was born in Andhra Pradesh, India, in 1969. He received the B.Tech. degree in Mechanical Engineering from the Indian Institute of Technology, Madras. He received the M.S. and Ph.D. degrees in Mechanical engineering from the University of California, Santa Barbara, in 1991, 1993, and 1997, respectively. From 1997-2007, he was with the Electrical Engineering Department at Iowa State University, From 2007 to 2010, he was Associate Professor at University of Minnesota (UMN), Twin-Cities, where he currently holds the Vincentine Hermes-Luh Chair in Electrical Engineering. He is the Director of Graduate Studies in the Electrical and Computer Engineering Department at UMN. Dr. Salapaka was the recipient of the 1997 National Science Foundation CAREER Award, and the 2001 Iowa State University Young Engineering Faculty Research Award. His research interests are in control and systems theory, nanotechnology and molecular biology. His research is supported by numerous grants form National Science Foundation, Google, and ARPA-E.

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Title : Power Divider
Speaker : Dr.Sairaj Dhople
Date : 05/08/2016
Venue : C 241 MMCR, EE
Abstract: This talk presents analytical closed-form expressions that uncover the contributions of nodal active- and reactive-power injections to the active- and reactive-power flows on transmission lines in an AC electrical network. Paying due homage to current- and voltage-divider laws that are similar in spirit, we baptize these as the power divider laws. Derived from a circuit-theoretic examination of AC power-flow expressions, the constitution of the power divider laws reflects the topology and voltage profile of the network. We demonstrate the utility of the power divider laws to the analysis and control of power networks by highlighting applications to transmission-network allocation, transmission-loss allocation, tracing the flow of power, and identifying feasible injections while respecting line active-power flow set points.
Speaker bio: Sairaj Dhople received the B.S., M.S., and Ph.D. degrees in electrical engineering from the University of Illinois, Urbana-Champaign, IL, USA, in 2007, 2009, and 2012, respectively. Currently, he is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, Minneapolis, MN, USA, where he is affiliated with the Power and Energy Systems Research Group. His research interests include modeling, analysis, and control of power electronics and power systems with a focus on renewable integration. Sairaj received the National Science Foundation CAREER award in 2015, and he currently serves as an Associate Editor for the IEEE Transactions on Energy Conversion.

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Title : Bayesian Nonparameric Modeling of Temporal Coherence for Entity-driven Video Analytics.
Speaker : Dr. Adway Mitra
Date : 05/08/2016
Venue : C 241 MMCR, EE
Abstract: Due to the advent of video-­sharing sites like Youtube, online user­-generated video content is increasing very rapidly. To simplify search of meaningful information from such huge volume of content, Computer Vision researchers have started to work on problems like Video Summarization and Scene Discovery from videos. People understand videos based on high­-level semantic concepts. But most of the current research in video analytics makes use of low­ level features and descriptors, which may not have semantic interpretation. We have aimed to fill in this gap, by modeling implicit structural information about videos, such as spatio­-temporal properties. We have represented videos as a collection of semantic visual concepts which we call “entities”, such as persons in a movie.To aid these tasks, we have attempted to model the important property of “temporal coherence”, which means that adjacent frames are likely to have similar visual features, and contain the same set of entities. Bayesian nonparametrics is a natural way of modeling all these, but they have also given rise to the need for new models and algorithms.
A tracklet is a spatio­temporal fragment of a video­ a set of spatial regions in a short sequence of consecutive frames, each of which enclose a particular entity. We first attempt to find a representation of tracklets to aid tracking entities across videos using region descriptors like Covariance Matrices of spatial features making use of temporal coherence. Next, we move to modeling temporal coherence at a semantic level. Each tracklet is associated to an entity. Spatio­-temporally close but non­overlapping tracklets are likely to belong to the same entity, while tracklets that overlap in time can never belong to the same entity. The aim is to cluster the tracklets based on the entities associated with them, with the goal of discovering the entities in the video along with all their occurrences. We represented an entity with a mixture component, and proposed a temporally coherent version of Chinese Restaurant Process (TC­CRP) that can encode the constraints easily. TC­CRP shows excellent performance on person discovery from TV ­series videos. We also discuss semantic video summarization, based on entity discovery. Next, we consider entity­-driven temporal segmentation of the video into scenes, where each scene is modeled as a sparse distribution over entities. We propose EntScene: a generative model for videos based on entities and scenes, and also an inference algorithm based on Dynamically Blocked Gibbs Sampling. We experimentally demonstrate significant improvements in terms of segmentation and scene discovery compared to alternative inference algorithms.
We briefly turn to modeling temporal coherence in hierarchically grouped sequential data, such as word-tokens grouped into sentences, paragraphs, documents etc in a text corpus. We attempt Bayesian modeling for such data, with application to multi-layer segmentation of a set of news transcripts- into broad categories (like politics, sports etc) and individual stories. We consider a Markovian and explicit-duration (semi-Markov) approach for this purpose, and provide an efficient inference algorithm for both.
Speaker bio: Adway Mitra has completed his PhD in Machine Learning and Computer Vision from CSA Department, Indian Institute of Science. Before that, he earned a Masters' Degree in Computer Science from the same department, and Bachelors' Degree from Jadavpur University, Kolkata. He is currently working on modeling complex spatio-temporal processes such as climatic processes as a postdoctoral fellow in International Center for Theoretical Sciences, Bangalore.


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Title : HV SiC Power Devices – A Panacea for Enabling MV Power Conversion Application
Speaker : Dr.Subhashish Bhattacharya
Date : 22/07/2016
Venue : C 241 MMCR, EE
Abstract:The advent of WBG (SiC and GaN) devices is poised to revolutionize the power electronics applications – both in the low power and low voltage applications, as well as the Medium Voltage (MV) and High Voltage (HV) applications at high power levels. This talk outlines opportunities for HV SiC devices for MV Power Converters and utility applications and the challenges to apply these HV SiC devices successfully. The talk will focus on SiC devices based power electronics applications with SiC device voltage ranges from 1200 V to 1700 V MOSFETs and JBS diodes, through HV 10 kV - 15 kV MOSFETs, JBS diodes, and 15 kV SiC IGBTs. The talk will develop understanding of the high frequency switching characteristics of these SiC devices and their potential application areas. The potential and challenges of the HV 10-15 kV devices to enable MV power conversion systems, including the large market space of MV motor drives will be discussed. The utility applications area of FACTS and VSC based HVDC and in particular MVDC systems can be enabled by these HV SiC devices. Challenges in adopting these HV SiC devices for MV power conversion in terms of magnetics, capacitors, insulation materials, etc. will be discussed.
Speaker bio:Subhashish Bhattacharya received his B.E. (Hons), M.E. and PhD degrees in Electrical Engineering from University of Roorkee, India in 1986, Indian Institute of Science (IISc), Bangalore, India in 1988, and University of Wisconsin-Madison in 2003, respectively. He worked in the FACTS (Flexible AC Transmission Systems) and Power Quality group at Westinghouse R&D Center in Pittsburgh which later became part of Siemens Power Transmission & Distribution, from 1998 to 2005. He joined the Department of Electrical and Computer Engineering at North Carolina State University (NCSU) in August 2005, where he is the ABB Term Professor, and also a founding faculty member of NSF ERC FREEDM systems center (www.freedm.ncsu.edu), Advanced Transportation Energy Center [ATEC] (www.atec.ncsu.edu) and the newly established DOE initiative on WBG based Manufacturing Innovation Institute – PowerAmerica - at NCSU. His research interests are Solid-State Transformers, MV power converters, FACTS, Utility applications of power electronics and power quality issues; high-frequency magnetics, active filters, and application of new power semiconductor devices such as SiC for converter topologies.
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Title : Height Information Extraction from Speech Data
Speaker : Dr. Deepu Vijayasenan
Date : 22/07/2016
Venue : C 241 MMCR, EE
Abstract: Physical parameter estimation from human speech is a very important task that finds its application in forensics. Eg., such systems would be able to derive some information about anonymous callers. In this talk, height estimation of a person from speech data is addressed. Support Vector regression models are derived from various different features.. Conventional short term spectral features such as Mel filter bank energies as well as prosodic features like formant locations, harmonic features and their statistics are explored.
Speaker bio: He is an assistant professor at NITK, Surathkal since Jan 1, 2013. Prior to that he spent two years at University of Saarbreucken, Saarland as Post doctoral researcher. He did his PhD at EPFL, Lausanne. His main interests include machine learning and speech signal processing.
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Title : Advanced Power Electronics and Motor Drives for Transportation Electrification: Opportunities and Challenges
Speaker : Dr. Sheldon S. Williamson
Date : 15/07/2016
Venue : C 241 MMCR, EE
Abstract: This presentation will largely showcase the launch and current status of UOIT’s new research program on transportation electrification and electric energy storage systems. The new, one-of-a-kind Advanced Storage Systems and Electric Transportation (ASSET) research facility will also be introduced. UOIT’s novel research initiatives within the newly established Smart Transportation Electrification and Energy Research (STEER) group has the potential of providing a significant link for future progress with regards to efficiency and performance improvement of electric transportation and personal e-mobility vehicles.
The main areas of research focus within the STEER group includes:
• Advanced electric energy storage systems: Lithium-ion battery management; improvement of battery cycle life; increasing driving range of electric vehicles (EVs); high-power ultracapacitor power management for electric mass transit vehicles – buses, trains, and trams.
• Smart EV charging infrastructures: Fast charging of EVs; charging from renewable energy (solar-photovoltaics); integration with the smart grid.
• Mass transit electrification: Fast charging of buses, trains, and trams using wireless power transfer; powering buses and trams using high-power ultracapacitors, including new power management strategies; electric machines and motor drives.
• E-mobility: Electric bikes (e-bikes), e-golf carts, UOIT campus vehicle electrification plans. The above mentioned research initiatives will be briefly described in the presentation and industry-specific projects within the STEER group will be highlighted. The high-level goals of the presentation will be focused on advanced power electronics solutions for EV traction batteries and ultracapacitors as well as plugged and wireless charging/inductivepower transfer (IPT) technologies. Novel motor drive technologies and controller designs for high-voltage DC power on board electric mass transit buses, trains, and trams will also be presented. UOIT’s new Canada Research Chair (CRC) program incl udes several novel initiatives in the areas of transportation electrification, and is built upon the expertise and know-how of the STEER group in a number of promising interdisciplinary areas related to power electronics and motor drives solutions for e-mobility and e-transportation.
Speaker bio: Sheldon S. Williamson received his Bachelors of Engineering (B.E.) degree in Electrical Engineering with high distinction from University of Mumbai, Mumbai, India, in 1999. He received the Masters of Science (M.S.) degree in 2002, and the Doctor of Philosophy (Ph.D.) degree (with Honors) in 2006, both in Electrical Engineering, from the Illinois Institute of Technology, Chicago, IL, specializing in automotive power electronics and motor drives, at the Grainger Power Electronics and Motor Drives Laboratory. From June 2006 to May 2011, Dr.Williamson held a Tenure-track Assistant Professor position in the Department of Electrical and Computer Engineering, at Concordia University, in Montreal, Canada. Also, from June 2011 to June 2014, Dr. Williamson held a tenured Associate Professor position at Concordia University. Currently, Dr. Williamson is an Associate Professor at the Smart Transportation Electrification and Energy Research (STEER) group, within the Department of Electrical, Computer, and Software Engineering, at the University of Ontario-Institute of Technology (UOIT), in Oshawa, Ontario, Canada. He also holds the prestigious NSERC Canada Research Chair position in Electric Energy Storage Systems for Transportation Electrification, at UOIT, since Sept. 2015. His main research interests include advanced power electronics and motor drives for transportation electrification, electric energy storage systems, and electric propulsion. Dr. Williamson has offered numerous conference tutorials, lectures, and short courses in the areas of electric transportation, electric energy storage systems, as well as automotive power electronics, and motor drives. He is the principal author/co-author of over 150 journal and conference papers. He is also the author/co-author of several books and b ook chapters on electric transportation and energy storage systems. He has been selected as the General Chair for the IEEE International Conference on Industrial Technology, to be held in Toronto, Ontario, in May 2017. In addition, Dr. Williamson has also served on the technical program committees of several IEEE conferences in the past. Dr. Williamson is the beneficiary of numerous awards and recognitions. He was the recipient of the prestigious “paper of the year” award, for the year 2006, in the field of Automotive Power Electronics, from the IEEE Vehicular Technology Society (IEEE VTS). In addition, he has also received several “best paper” awards for papers he has co-authored with his graduate research students in major IEEE conferences. He was awarded the prest igious Sigma Xi/IIT Award for Excellence in University Research, for the academic year 2005-2006. In 2006, he also received the “Best Research Student” award, Ph.D. category, within the ECE Department, at the Illinois Institute of Technology, in Chicago, IL. Dr. Williamson is a Senior Member of the IEEE and is a Member of the IEEE Power Electronics Society (IEEE PELS) and the IEEE Industrial Electronics Society (IEEE IES). He also currently serves as a Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS). He is an Associate Editor for the IEEE Transactions on Industrial Electronics, IEEE Transactions on Power Electronics, IEEE Transactions on Transportation Electrification, and the IEEE Journal of Emerging and Selected Topics in Power Electronics. He is a Member of the prestigious IEEE Transportation Technologies. Title : Multimodal behavioral informatics for health applications
Speaker : Prof. Shrikanth (Shri) Narayanan
Date : 07/07/2016
Venue : C 241 MMCR, EE
Abstract: The confluence of sensing, communication and computing technologies is allowing capture and access to data, in diverse forms and modalities, in ways that were unimaginable even a few years ago. These include data that afford the analysis and interpretation of multimodal cues of verbal and non-verbal human behavior to facilitate human behavioral research and its translational applications in health. These data not only carry crucial information about a person’s intent, identity and trait but also underlying attitudes, emotions and other mental state constructs. Automatically capturing these cues, although vastly challenging, offers the promise of not just efficient data processing but in tools for discovery that enable hitherto unimagined scientific insights, and means for supporting diagnostics and interventions. Recent computational approaches that have leveraged judicious use of both data and knowledge have yielded significant advances in this regards, for example in deriving rich, context-aware information from multimodal signal sources including human speech, language, and videos of behavior. These are even complemented and integrated with data about human brain and body physiology. This talk will focus on some of the advances and challenges in gathering such data and creating algorithms for machine processing of such cues. It will highlight some of our ongoing efforts in Behavioral Signal Processing (BSP)—technology and algorithms for quantitatively and objectively understanding typical, atypical and distressed human behavior—with a specific focus on communicative, affective and social behavior. The talk will illustrate Behavioral Informatics applications of these techniques that contribute to quantifying higher-level, often subjectively described, human behavior in a domain-sensitive fashion. Examples will be drawn from mental health and well being realms such as Autism Spectrum Disorders, Couple therapy, Depression and Addiction counseling.
Speaker bio: Shrikanth (Shri) Narayanan is Andrew J. Viterbi Professor of Engineering at the University of Southern California, where he is Professor of Electrical Engineering, and jointly in Computer Science, Linguistics, Psychology, Neuroscience and Pediatrics, and Director of the Ming Hsieh Institute. Prior to USC he was with AT&T Bell Labs and AT&T Research. His research focuses on human-centered information processing and communication technologies. He is a Fellow of the Acoustical Society of America, IEEE, and the American Association for the Advancement of Science (AAAS). Shri Narayanan is Editor in Chief for IEEE Journal on Selected Topics in Signal Processing, an Editor for the Computer, Speech and Language Journal and an Associate Editor for the IEEE Transactions on Affective Computing, the Journal of Acoustical Society of America, and the APISPA Transactions on Signal and Information Processing having previously served an Associate Editor for the IEEE Transactions of Speech and Audio Processing (2000-2004), the IEEE Signal Processing Magazine (2005-2008), the IEEE Transactions on Signal and Information Processing over Networks (2014-2015) and the IEEE Transactions on Multimedia (2008-2012). He is a recipient of several honors including the 2015 Engineers Council’s Distinguished Educator Award, the 2005 and 2009 Best Transactions Paper awards from the IEEE Signal Processing Society and serving as its Distinguished Lecturer for 2010-11, and as an ISCA Distinguished Lecturer for 2015-16. With his students, he has received a number of best paper awards including a 2014 Ten-year Technical Impact Award from ACM ICMI and Interspeech Challenges in 2009 (Emotion classification), 2011 (Speaker state classification), 2012 (Speaker trait classification), 2013 (Paralinguistics/Social Signals), 2014 (Paralinguistics/Cognitive Load) and in 2015 (Non-nativeness detection). He has published over 700 papers and has been granted 17 U.S. patents. Title : Enhancing clinical voice assessment with smartphone-based ambulatory voice monitoring
Speaker : Dr Daryush Mehta
Date : 01/07/2016
Venue : C 241 MMCR, EE
Abstract: An estimated 30% of the adult U.S. population suffers from a voice disorder at some point in their lives and often experience significant communication disabilities with far-reaching social, professional, and personal consequences. Most voice disorders are chronic or recurring conditions and result from inefficient and/or abusive patterns of vocal behavior, termed vocal hyperfunction. Thus, an ongoing clinical research goal is the prevention, diagnosis, and treatment of vocal hyperfunction through noninvasive, long-term monitoring of an individual’s daily voice use. During this talk, I will present my work investigating vocal hyperfunction in voice patients and matched healthy controls using smartphone-based ambulatory voice monitoring. Voice use and vocal function measures were derived from neck-surface acceleration recordings using vocal dose theory and novel impedance-based acoustic modeling to yield glottal airflow estimates. Results indicate that the clinical treatment of vocal hyperfunction would be improved by the ability to unobtrusively monitor and quantify detrimental voice use and simultaneously provide real-time biofeedback, thereby facilitating the learning of healthier vocal behaviors. Future research aims to enhance clinical voice assessment through integrating innovations in wearable sensor technology and laryngeal endoscopic imaging.
Speaker bio: Daryush Mehta is Assistant Biomedical Engineer at the Center for Laryngeal Surgery and Voice Rehabilitation at the Massachusetts General Hospital (MGH), Instructor in Surgery at Harvard Medical School, and Adjunct Assistant Professor at the MGH Institute of Health Professions. Daryush received his PhD in Speech and Hearing Bioscience and Technology from the Harvard–MIT Division of Health Sciences and Technology (2010), Master's degree in Electrical Engineering and Computer Science from MIT (2006), and Bachelor's degree in Electrical Engineering from University of Florida (2003). Daryush’s research interests include high-speed video imaging of vocal vibration, speech signal processing, and clinical voice disorder assessment. Read all about his work at http://web.mit.edu/dmehta/www.
Title : Detection and analysis of whispered speech
Speaker : Nisha Meenakshi G
Advisor:Dr. Prasanta Kumar Ghosh
Date : 24/06/2016
Venue : C 241 MMCR, EE
Abstract:Whispering is an indispensable form of communication that emerges in private conversations as well as in pathological situations. In conditions like laryngectomy and neurogenic disorders such as Vocal chord Paresis and Spasmodic Disphonia one or both of the vocal chords are affected, leading to the patient’s voice becoming a breathy and rough whisper. Thus, the conversion of whispered speech to neutral speech would be potentially beneficial for these patients. In this talk, two key components of such a conversion- the detection and analysis of whispered speech will be discussed. Whisper activity detection (WAD) detects whispered speech in the presence of noise. In this regard, a novel feature, that utilizes the long-term logarithmic energy variation (LTLEV) of the sub-band signal is proposed. It is found to be effective in distinguishing noisy whispered speech from noise, under eight different noise conditions and four different signal-to-noise ratios (SNR). In the second part of the talk, the discriminative analysis of the voiced and unvoiced consonants in whispered speech space, across six different Indian languages, will be discussed. Some key findings of this study include a reduction in the whispered consonant space, reduced discrimination between whispered voiced and unvoiced phonemes and some interesting language specific findings.
Whispering is an indispensable form of communication that emerges in private conversations as well as in pathological situations. In conditions like laryngectomy and neurogenic disorders such as Vocal chord Paresis and Spasmodic Disphonia one or both of the vocal chords are affected, leading to the patient’s voice becoming a breathy and rough whisper. Thus, the conversion of whispered speech to neutral speech would be potentially beneficial for these patients. In this talk, two key components of such a conversion- the detection and analysis of whispered speech will be discussed. Whisper activity detection (WAD) detects whispered speech in the presence of noise. In this regard, a novel feature, that utilizes the long-term logarithmic energy variation (LTLEV) of the sub-band signal is proposed. It is found to be effective in distinguishing noisy whispered speech from noise, under eight different noise conditions and four different signal-to-noise ratios (SNR). In the second part of the talk, the discriminative analysis of the voiced and unvoiced consonants in whispered speech space, across six different Indian languages, will be discussed. Some key findings of this study include a reduction in the whispered consonant space, reduced discrimination between whispered voiced and unvoiced phonemes and some interesting language specific findings.
Title : Synchrophasor Technology Applications to Power Stability Monitoring and Control
Speaker : Prof. S C Srivastava
Date : 20/06/2016
Venue : C 241 MMCR, EE
Abstract: Increased size and complexity of the electric power system networks pose various operating challenges in maintaining continuity, quality and security of the system. Several events of blackouts in recent past, worldwide, have necessitated the use of more intelligent and automated systems for online monitoring, protection and control of the power systems. Wide Area Monitoring, and Control System (WAMCS), employing synchrophasor technology, are being increasingly used in power system networks, which enhances system observability and facilitates use of several online decision tools for monitoring and control of the power system stability and security. This technology has been tried at pilot level and now being deployed in large number in Indian power networks.This talk will discuss some of the concepts of the synchrophasor measurements and its applications, specifically relevant to the system stability monitoring and control, along with an overview of plans for its deployment in the Indian power grid.
Speaker bio: Prof. Srivastava received B.Tech. degree in Electrical Engineering in 1976 from Institute of Technology, Banaras Hindu University, and Ph.D. from Indian Institute of Technology (IIT) Delhi. He worked at Engineers India Limited New Delhi, a consultancy organization, during Nov.1976-Nov.1988 in its Project Engineering and Engineering Technology Development divisions. Since November 1988, he is a faculty member in the Department of Electrical Engineering at IIT Kanpur, where he became ‘Professor’ in Dec. 1995. He also served as Head of Electrical Engineering Department during Jan. 2000 to Dec. 2002, Dean of Research and Development during Jan. 2005 to Jan. 2008, and Deputy Director during Sep. 2011 to Sep. 2014 at IIT Kanpur. During August 2008-July 2009, he was as a ‘Visiting Research Professor’ in the ECE Department at Mississippi State University, USA and also as a Faculty member at Asian Institute of Technology, Bangkok, Thailand during 1996-97, on leave from IIT Kanpur. He also held ‘P.K. Kelkar Chair Professor’ position at IIT Kanpur, and now holding ‘Ministry of Labour and Employment Chair Professor’ position. He has supervised 26 Ph.D. and 60 Masters theses in the Power Systems area. He has published about 300 papers in refereed journals and conference proceedings. His research interests include Power System Stability and Security Analysis, Synchrophasor Applications, Power System Restructuring and AC/DC Microgrid. He is a Fellow of the Indian National Academy of Engineering (INAE), Institution of Engineers (India) & IETE (India), and Senior member of the IEEE.
Title : Acoustic based speech rate estimation using data-driven approaches
Speaker : Mr.Chiranjeevi Yarra
Advisor : Dr. Prasanta Kumar Ghosh
Date : 17/06/2016, 4 pm
Venue : C 241 MMCR, EE
Abstract: Acoustic feature based speech (syllable) rate estimation is important problem in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for the problem consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, we address both the problems separately in a data-driven manner. For the first problem, temporal correlation selected sub-band correlation (TCSSBC) is often used as a feature contour for the speech rate estimation in which correlation within and across a few selected sub-band energies are computed. Instead of a fixed set of sub-bands, we learn them using a dictionary learning approach. Similarly, instead of the energy contours, we use the activation profile from the learned dictionary elements. We found that the peaks detected from the activation profiles significantly improve the speech rate estimation when combined with the traditional TCSSBC approach using a proposed peak-merging strategy. For the second problem, rule based approaches are often used for detecting the peaks of the feature contour. Instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem – mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora and the proposed methods outperform the best of the existing methods.
Title : Emerging trends in Computational Imaging and Displays
Speaker : Dr. Ram Narayanswamy
Date : 15/06/2016, 10.30Am
Venue : C 241 MMCR, EE
Abstract: In this talk we will explore how the evolution of photography and personal media has reached an inflection point in its evolution. Recent developments of imaging systems have created rich immersive data sets that allow for new forms of media and interaction with our digital environment. We will give a glimpse into research at Intel Labs that explores new computational imaging capabilities in the area of multi-camera systems and interactive visual experiences. We will highlight new imaging technologies that made their way from research into recent Intel products, and what capabilities these offer to the researchers and developers. In closing, we will give an outlook on where we see this trend going and the opportunities this offers for research in computational imaging.
Speaker bio: Ram Narayanswamy is currently part of Intel’s Computational Imaging Lab. He started his career at NASA Langley Research Center in the Visual Image Processing lab working on imaging system design and optimization. There he co-authored a paper titled “Characterizing digital image acquisition devices”, better known today as the “slanted-edge test” a de facto standard to measure camera MTF. He was one of the early members of CDM Optics, a Boulder start-up which pioneered Wavefront Coding and the field of computational imaging. Upon CDM’s acquisition by OmniVision Technologies, Ram led the effort to productize Wavefront Coding for the mobile phone segment. Later, he joined Aptina Imaging where he helped bring the world’s first performance 720p reflowable cameras modules with molded glass optics to market – a complete-camera that ships in tape and reel! While at Aptina, Ram also led their effort in Array cameras. He is a Program Chairman’s for The Optics Society’s Annual Congress on Imaging and Applied Optics to be held in Heidelberg, Germany July 2016. Ram has a PhD from the University of Colorado-Boulder and BS from the National Institute of Technology – Trichy. He has over 40 publications and loves this golden age of imaging and looks forward to ushering the platinum age.

Title: Networked and distributed CPS: control under network constraints and networked transportation systems
Speaker: Dr. Pavan Tallapragada
Date: 14/06/2016, 4 pm
Venue: C 241 MMCR, EE
Abstracts: With various enabling technologies, large scale distributed and pervasive control systems are becoming a reality, such as wireless automation networks in large industries, building HVAC systems, distributed smart energy grids, next generation cars and networked transportation systems. The complexity of such systems necessitates an integrated approach to the design of control, communication and computing components. The recognition of this fact has given rise to the paradigm of Cyber Physical Systems (CPS) in recent years.
A common problem in large scale networked and distributed systems is that of constrained or limited resources such as energy/power, communication and computational capabilities. In this presentation, I will talk about my work on opportunistic state-triggered control, which seeks to design controllers under communication constraints.
I will also talk about a CPS domain, namely networked transportation systems. Emerging technologies such as networked and computer controlled vehicles offer the opportunity to design novel systems of transportation and traffic control. Such systems have the potential to hugely improve safety, travel ease, travel times and energy consumption. I will illustrate this with the example of a hierarchical-distributed system for coordination of intersection traffic.
Speaker Bio : Pavan Tallapragada is a postdoc since 2014 at the University of California, San Diego. He received B.E. in 2005 from SGGSIE&T, SRTMU, Nanded and MSc. (Engg.) in 2007 from the Indian Institue of Science, Bangalore, both in Instrumentation. He received Ph.D. in Mechanical Engineering from the University of Maryland, College Park in 2013. He worked briefly as a Junior Research Fellow at the National Institute of Advanced Studies, Bangalore in 2007 and as a Technical Specialist at Panacea Medical Technologies, Bangalore in 2008.
His research interests include networked and distributed control systems and Cyber Physical Systems (CPS). Specifically, he is interested in topics such as control under communication constraints, privacy in CPS and networked transportation systems.

Title : A QR Decomposition Approach to Factor Modelling
Speaker : Dr. Bharath Bhikkaji
Date : 14/06/2016, 11.30 am
Venue : C 241 MMCR, EE
Abstracts : An observed K-dimensional series {y_{n}, n=1,....N} is expressed in terms of a lower p- dimensional latent series called factors f_{n} and random noise epsilon_{n}. The equation, y_{n}=Qf_{n}+ epsilon_{n} is taken to relate the factors with the observation. The goal is to determine the dimension of the factors, p, the factor loading matrix, Q, and the factors f_{n}. Here, it is assumed that the noise co-variance is positive definite and is allowed to be correlated with the factors. This paper proposes the use of QR decomposition instead of the standard Eigenvalue Decomposition (EVD) for determining the model order p and the loading matrix Q. Estimation of the model order p is formulated as a Numerical Rank determination problem. Rank Revealing QR (RRQR) decomposition is used for estimating the loading matrix Q. The asymptotic performances of the estimates of p, Q and f_{n} are analyzed by letting K, N tend to infinity. The asymptotic rates, and empirical results, suggests that the proposed technique is both computationally efficient and accurate.
Speaker Bio : Dr. Bharath Bhikkaji is currently working as an Assistant Professor in the Dept. of Elec, Engg in IIT Madras. He received his Ph.D. degree in Signal Processing from the Uppasla University, Uppsala, Sweden, in the year 2004, and M.E. degree from Electrical Communication Engineering, Indian Institute of Science, Bangalore. He worked as a Research Academic at the School of Electrical Engineering and Computer Science, University of Newcastle, Newcastle, Australia from 2004-2008. His research interests include System Identification, Robust Control and Active noise and Vibration control of Flexible structures.

Title : Understanding the Perception and Impact of Social Signals
Speaker : Dr Tanaya Guha
Date : 14/06/2016, 10 am
Venue : C 241 MMCR, EE
Abstracts : Understanding the diverse behavioral and social patterns that exist around us can improve our social experience and interaction in many ways. With this broader objective in mind, we focus on two important but different problems relevant to social signal processing. The first problem involves social perception and its impact on media. Here, we attempt to quantify a very subjective and often not-so-well-defined concept of gender representation and bias. Starting with content analyzing popular Hollywood movies, we show how gender representation can be objectively measured from multimodal cues. In the next part, we focus on the production and perception of social signals in autism. Our goal is to understand how behavioral signals, such as facial expressions, produced by children with autism are perceived by healthy observers. Methodologies, approaches, results and challenges related to both of these problems will be discussed.
Speaker Bio : Tanaya Guha is currently an Assistant Professor in the department of Electrical Engineering at IIT Kanpur. She is also a part of the computer vision group at IITK. Prior to joining IITK, she was a postdoctoral fellow at the Signal Analysis and Interpretation Lab (SAIL), University of Southern California, Los Angeles from 2013 to 2015. She has received her PhD in Electrical and Computer Engineering from the University of British Columbia, Vancouver in 2013. She was a recipient of Mensa Canada Woodhams memorial scholarship, Google Anita Borg memorial scholarship and Amazon Grace Hopper celebration scholarship. Her current research interests include human emotion and behavior analysis, multimodal signal processing, and image analysis.

Title : Introduction to Smart Grids
Speaker : Prof. S A Khaparde
Date : 03/06/2016, 4pm
Venue : C 241 MMCR, EE
Abstract: Smart  grids are evolving for the last two decades. Many countries, including India, are investing large funds in this technology. The talk will introduce the fundamentals of smart grids. Pilot project in India will be discussed. The research opportunities will be identified at the end of the talk.
Speaker bio: Prof. Shrikrishna A. Khaparde received the Ph.D. degree from IIT, Kharagpur in 1981. He is a Professor with the Department of Electrical Engineering, IIT Bombay. He was awarded the DSK Energy Award in 2009, for outstanding contribution in energy sector, by The Institution of Engineers (India), Pune Centre.
He is a Consultant to Maharashtra Electricity Regulatory Commission (MERC), Indian Energy Exchange, Power Grid Corporation of India Ltd., etc. He has coauthored the book "Computational Methods for Large Sparse Power Systems Analysis: An Object Oriented Approach" (Norwell, MA, USA: Kluwer, 2001). He has published over 200 research papers in leading journals and conferences.  His research interests include restructured power systems, distributed generation, renewable energy policies, and Common Information Model (CIM) implementation in India.
Prof. Khaparde is a member of advisory committees to Maharashtra Electricity Regulatory Commission and Indian Energy Exchange. He is an Editor of the International Journal of Emerging Electrical Power Systems. He is a member of IEC TC57 for working groups 13 and 16, representing India. He is a BIS LITD-10 Committee Member and Chair of the Working Group (WG3) on CIM.

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Title : Face Recognition in Unconstrained Environment
Speaker : Mr. Sivaram Prasad Mudunuri
Advisor : Dr.Soma Biswas
Date : 27/05/2016 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Unconstrained face recognition is an important area of research in the field of computer vision and pattern recognition. The increasing use of surveillance cameras for addressing security concerns has led to increased demand for robust face recognition systems. The images captured by the surveillance cameras usually have poor resolution, uncontrolled pose and illumination conditions which makes the task of recognizing these faces extremely challenging. Significant attention has been devoted to addressing one or more of the different challenges like poor illumination, non-frontal pose, expression, etc. But addressing all these challenges together is essential in many real world applications. In this presentation, an overview on recent state-of-the-art approaches and our algorithm of recognizing low resolution faces with variations in pose and illumination will be discussed. To be specific, our work assumes that, the faces are already detected and cropped from the given image. Though the motivation behind the proposed algorithm is to match the facial images captured under real outdoor surveillance scenario, we are able to match the faces captured under controlled environment and limited surveillance quality cameras only.
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Title : Innovative Applications from Analysis of Frequency Response of Transformer Winding
Speaker : Dr. Saurav Pramanik
Date : 25/05/2016 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract:Power transformers are vital links in an electrical network, whose normal working is paramount for uninterrupted operation of a power system. In the post-deregulated era, it emerges that condition monitoring of HV apparatus followed by meaningful diagnosis, is the ideal way to avoid unplanned outages, optimize assets, reduce operating costs and thus operate the plant efficiently. Over the years, many powerful tools have become available for assessing the status of transformers. Among them, frequency response measurement (also called FRA), is the most-sensitive to detect mechanical damage occurring to the windings and core. In spite of its existence for many years, FRA continues to remain as a monitoring tool. It has lot of untapped potential and inherent abilities but the relevant issues have not received the attention it deserves, and research groups working in these areas are also few. So, research efforts are essential to address these issues. In this talk the speaker will present few innovative methods to extract information embedded in the frequency/time domain response of the transformer winding and utilizes them for suggesting simple, but, yet impressive solutions to a few tasks which have until now been thought difficult, if not impossible, to resolve. Two such applications are (i) Investigate indirect measurement of the series capacitance of a transformer winding using the measured response, and (ii) A new diagnostic approach for fault detection in transformer winding using tank current measurement. Details will be presented in the seminar. In the end, speaker will also highlight his postdoctoral research on energy efficient transformers carried out at ABB Corporate Research, Sweden.
Speaker bio: Dr. Saurav Pramanik is currently working as a visiting assistant professor in the Department of Electrical Engineering, IIT Kharagpur. Earlier He had been working as a postdoctoral scientist in Corporate Research ABB in completed his Masters and Ph.D. from the Department of Electrical Engineering, IISc., Bangalore in 2010 and 2013 respectively. He has a B.E. degree in Electrical Engineering from Jadavpur University, Kolkata in 2006. His research area mainly includes monitoring and diagnostics of power transformers. He has also worked on problems related to core magnetics in power transformer with the objective to reduce the core loss, as well as, some other stray losses in transformer winding. He was conferred national and international awards for his research contribution.
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Title : Research Activities in High Voltage Laboratory @IITM
Speaker : Prof. R. Sarathi, Dept of Electrical Engineering, IIT Madras
Date : 25/05/2016 11.30 am
Venue : HV Lab, Seminar Hall

Title : A matrix free iterative reconstruction algorithm for Photoacoustic Tomography
Speaker : Rejesh N.A
Advisor : Dr. Muthuvel Arigovindan
Date : 20/05/2016 (4.00 pm - 5.00 pm)
Venue : MMCR (C241)
Abstract: Photoacoustic tomography (PAT) is an emerging biomedical imaging modality that shows great potential for preclinical research and clinical practice. PAT is a hybrid technique based on optical excitation and ultrasonic detection resulting from absorption of light. Absorption of photons by biomolecules thermoelastically induces pressures waves, which are received by acoustic detectors to form images. Because ultrasound scatters much less than light in tissue, PAT generates high-resolution images in both the optical ballistic and diffusive regimes. Existing approaches to image reconstruction in PAT are computationally intensive, and/or cannot effectively mitigate the effects of measurement data incompleteness and noise. In this presentation, an iterative reconstruction algorithm for PAT images, which is both computationally and memory efficient will be presented.
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Title: Graph Signal Processing (Lecture Video)
Speaker: Prof. K. R. Ramakrishnan
Venue: C 241 MMCR, EE
Date and time: 13th May 2016, 4:00pm - 5.00pm
Abstract:
In applications such as social, energy, transportation, sensor,and neuronal networks, high-dimensional data naturally reside on the vertices of weighted graphs. The emerging field of Graph signal processing draws the concepts from traditional DSP to process such signals on graphs. In this seminar we discuss ways to define graph spectral domains, which are the analogs to the classical frequency domain, and highlight the importance of incorporating the irregular structures of graph data domains when processing signals on graphs. We also generalize fundamental operations such as filtering, translation, modulation, dilation, and down sampling to the graph setting.

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Title: Google little box challenge
Speaker: Dr. Rajesh Ghosh
Venue: EE 217 (MMCR)
Date and time: 6th May 2016, 4:00pm - 5.00pm
Abstract:
Inverters convert DC from solar/battery into AC at home, automobiles, UPS drives and many other applications. Normal inverters are big in size (picnic cooler). Smaller inverters enable more solar-powered homes, more efficient distributed grids, compact automobiles and low cost, help bring electricity to the most remote parts of the planet. Little Box Challenge was a worldwide open competition to build world's first smallest 2kW inverter at $1,000,000 prize. It was jointly sponsored by Google and IEEE. From Schneider Electric, we participated into this contest, and secured the second position. Our achieved power density is 100W/cubic inch, which is just double the required power density set by Google. In this presentation, detailed technical challenges and how we address them will be discussed in detail. Also, the approaches used by others will be discussed.
Speaker bio: Rajesh Ghosh received the Ph. D degree in Electrical Engineering from The Indian Institute of Science Bangalore in 2007. He joined APC by Schneider Electric, Bangalore in 2007 as an Electrical Engineer. Currently he is a staff Electrical Engineer in the IT business of Schneider Electric. His interests include high-frequency power conversion and digital control. Prior to joining APC he worked with CESC Ltd. Calcutta, India and GE Global Research center Bangalore, India. He has published many journal and conference papers in IEEE and holds many US patents. His research interest includes High-frequency power conversion, application of wide band gap devices in future power converters, digital control and soft switching technique.

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Title: Machine Vision Applications: Challenges and Opportunities
Speaker: Dr. Dinesh Ramegowda
Venue: EE 217 (MMCR)
Date and time: 15th Apr 2016, 4:00pm - 5.00pm
Abstract:
Man from the beginning of time, tried to automate things for comfort, accuracy, precision and speed. Technology advanced from manual to mechanical and then from mechanical to automatic. Vision based applications are the products of the future. Today's high speed, complex manufacturing systems require the development of automation technologies that can be efficiently integrated into the systems and used in manufacture floors. Machine vision systems integrate electronic components with software systems to imitate a variety of human functions. This presentation gives overview on the recent developments in the area of Machine Vision with few case studies. The presentation also highlights the challenges and opportunities in the area of Machine Vision. The research and development work at Samsung Electro-Mechanics will be highlighted towards, the end of presentation.
Speaker bio: Dinesh is a Chief Engineer with Samsung Electro-Mechanics, India. Prior to joining Samsung, he worked for companies Amazon, Honeywell, HCL Technologies. He was a post doctoral researcher at Seoul National University, Seoul. His areas of research interest includes Image processing, Pattern Recognition, Computer Vision and Document Image Analysis. He has over 60 publications to his credit at both International and National Journals and conferences. He also has 12 awarded patents to his credit. He is serving in the editorial board of several journals. He has been identified as reviewer for several International Journals/conferences. He has served as program committee member for several National/International Conferences. He is presently guiding 5 Ph.D scholars. He has successfully guided many academic and research projects. He is a life member of IEEE, Computer Society of India and Society of Statistics, Compute and Applications, International Association of Engineers, Hong Kong.

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Title: CP-mtML: Coupled Projection multi-task Metric Learning for Large Scale Face Retrieval
Speaker: Dr. Gaurav Sharma
Venue: EE 217 (MMCR)
Date and time: 13th Apr 2016, 11:00am
Abstract:
I will present our recent work about a novel Coupled Projection multi-task Metric Learning (CP-mtML) method for large scale face retrieval. In contrast to previous works which were limited to low dimensional features and small datasets, the proposed method scales to large datasets with high dimensional face descriptors. It utilises pairwise (dis-)similarity constraints as supervision and hence does not require exhaustive class annotation for every training image. While, traditionally, multi-task learning methods have been validated on same dataset but different tasks, the method is tested on the more challenging setting with heterogeneous datasets and different tasks. Empirical validation on multiple face image datasets of different facial traits, e.g. identity, age and expression support the method. The experiments clearly demonstrate the scalability and improved performance of the proposed method on the tasks of identity and age based face image retrieval compared to competitive existing methods, on the standard datasets and with the presence of a million distractor face images.
Speaker bio: Gaurav Sharma is currently an Assistant Professor at the Department of Computer Science and Engineering of the Indian Institute of Technology Kanpur. He obtained his PhD in 2012 under the joint supervision of Cordelia Schmid (LEAR, INRIA Grenoble) and Frederic Jurie (GREYC, CNRS UMR 6072, University of Caen) and an Integrated Master of Technology in Mathematics and Computing in 2008 from the Indian Institute of Technology Delhi (IIT Delhi), India. He was, prior to his PhD, a Senior Engineer at the Technology Planning Group of Samsung R&D India and, after his PhD, a Researcher in the Exploratory Research Group of Technicolor R&I, France. and a Postdoctoral Fellow at the Max Planck Institute for Informatics, Germany. His research interests are Computer Vision and Machine Learning.

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Title: Overview of deep learning in Echo’s speech recognizer
Speaker: Dr Sivaram Garimella
Venue: EE 217 (MMCR)
Date and time : 11th Apr 2016, 5.00pm
Abstract:
Amazon Echo's high accuracy speech recognition system uses deep neural network (DNN) acoustic models. Such models are trained using in-house distributed Stochastic Gradient Descent (SGD) training framework. This talk provides an overview of speech recognition focusing on DNN based acoustic modeling and our distributed DNN training for building production models.
Speaker bio: Sri Garimella has been working as a machine learning scientist in Amazon Echo speech recognition team since September 2012. He has relocated to India and currently based in Amazon, Bangalore. He has obtained PhD from the Johns Hopkins University, Center for Language and Speech Processing, Baltimore in 2012, and Master of Engineering in Signal Processing from the Indian Institute of Science, Bangalore in 2006. His research interests include deep learning, statistical machine learning, and speech & speaker recognition. He has several publications in peer-reviewed journals and conferences in this area.

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Title: Computational Pathology:  Unlocking Tissue Content in Precision Medicine
Speaker: Dr. Chukka Srinivas
Venue: EE 217 (MMCR)
Date and time: 5th Apr 2016,11:30am - 1.00pm
Abstract:
Traditionally, pathologists detect, stage and grade cancer in patient tissue biopsies based on a microscopic manual evaluation of  small set of cellular and morphological features in Hematoxylin and Eosin (H&E) stained tissue slides.   This information along with an assessment of protein overexpression in the tumor, semi-quantitatively scored from multiple immunohistochemical (IHC) stained slides, is used to subtype the cancer for prognostic and precise treatment selection and planning.
Digital pathology refers to the technologies for digitization of tissue whole slides and image analysis algorithms for automated slide interpretation and precise quantification.  So far, the image analysis algorithm development has been focused on generating consistent interpretation and reproducible slide scores, accounting for the inherent challenges of wide biological and staining variability in a clinical setting, but primarily limited to mimicking the manual interpretation process of the pathologists.
There is ever increasing medical evidence that while there is potentially a large amount of prognostic information for a given patient in the tissue, today this information is being analyzed separately from a clinical standpoint without its holistic integration into a single comparative prognostic dataset.  Computational pathology is a data-driven pipeline, based on statistical and machine learning methods, for systematic extraction of multi-dimensional information in the digitized tissue slides at multiple scales, statistically combine these features and directly correlating against patient outcome, which is given in terms of patient survival or a response to a drug treatment, to discover discriminant features for prognostication and prediction to a drug response.
In this talk, we propose a computational pathology framework and showcase an end to end application to a specific example of prediction of risk of recurrence in early stage breast cancer patients.  Supervised learning based fully automated image analysis algorithms are used to analyze H&E and multiple IHC whole slides and extract an exhaustive set of image features.  Based on extracted image features and clinical outcome for a patient cohort, a L1-regularized logistic regression based prognostic model is constructed. We show here there are morphological, relational and co-expression image features, which are significantly associated with patient overall survival and could therefore be used to improve prognosis and guide follow-up treatment.
Speaker bio: Chukka Srinivas is a Scientific Fellow in Roche Tissue Diagnostics working on image analysis and machine learning solutions for cancer tissue diagnostics. He got his Bachelors in Electronics from Osmania University in ’83, Masters from the Indian Institute of Science in ‘85 and PhD from the Southern Methodist University, Dallas  in 1990.  He has worked before at GE Global Research, HP, Teradyne, Polaroid and Hologic.   As an imaging researcher, has worked on variety of topics in signal and image processing, computer vision and machine learning topics for medical, semiconductor, aerial and photographic  applications and contributed to the development of multiple products.

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Title : Studies on polymer insulators subjected to electrical and environmental stresses
Speaker : Shakthi Prasad D
Advisor : Dr. Subba Reddy B. and Prof. Rajanikanth B. S.
Date : 04/03/2016 (4.00 pm - 5.00 pm)
Venue : MMCR (C241)
Abstract: Corona is an unavoidable phenomenon in the high voltage power transmission system. It is a proven fact that the polymeric insulators subjected to continuous corona lead to severe degradation like surface rapture, hydroxylation, oxidation etc., Further; moisture has a positive influence on the corona activity. In the present study, a methodology has been developed to evaluate the corona performance of the silicone rubber housing material with simultaneous application of cold fog. Physico-chemical analyses like Fourier transform spectroscopy, scanning electron microscopy, contact angle measurements etc., were carried out on the treated samples. Experimental investigations conducted prove that moisture assists in accelerating the corona induced degradation on the polymeric insulators.
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Title: High Power Factor High-Current Variable-Voltage Rectifiers
Speaker: Dr.Jitendra Solanki
Venue: EE 217 (MMCR)
Date and time:26th Feb 2016,15:30 hrs
Abstract:
High-current variable-voltage (HCVV) rectifiers are used in the metal and chemical industries. Typical power ratings vary from tens of kW to hundreds of MW. Even with the advancement of the power factor correction rectifiers, accepted choices of high-current AC to DC converters remain 6, 12 or 24-pulse thyristor/diode rectifiers, because of high reliability, efficiency and availability of suitable semiconductor devices. The main issues with these rectifiers are poor input power factor, high current harmonic distortion, high-maintenance cost, high weight and large volume. The seminar highlights some of these issues and explains the remedial measures taken. Apart from this, the talk also (briefly) covers some of the other projects in fields of high-power high-frequency resonant inverter and switch-mode power-supplies.
Speaker bio: Jitendra Solanki received his B.-Tech. degree in electrical engineering from G.B. Pant University of Agriculture and Technology, Pantnagar and M.-Tech. degree in power electronics electrical machines and drives from IIT Delhi, New Delhi in 2004 and 2006, respectively. He received doctorate degree from University of Paderborn, Germany in 2015. Before joining Ph.D., from 2006-2009, he was working with GE Global Research, Bangalore. From 2009-2010, he was with Philips Research Asia, Bangalore. Since Nov. 2014, he is working with Corporate Research, Robert Bosch (SEA) Pte. Ltd., Singapore. Dr. Solanki is a recipient of the ‘innovative student project award' from the Indian National Academy of Engineering and the 'ISTE-L&T second best project award' from Indian Society of Technical Education for his work during master’s degree. His research interests include high-power rectifiers, power-quality compensators and DC-DC converters.

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Title: Exploiting latent reliability information for classification tasks
Speaker: Mr. Naveen Kumar
Venue: EE 217 (MMCR)
Date and time: 4th Feb 2016,11:30 hrs
Abstract:
Despite significant advances in machine learning techniques, we find that certain pattern recognition problems are intrinsically more difficult. For example, in a classification task certain classes may be more ``noise-like" or difficult to model compared to others. The challenge in these tasks often lies in adequately modeling the variability in observations within a given data set. In theory, we would be interested to isolate and learn from only those aspects of this variability that are useful for the classification task. This information could be either in the form of knowledge of certain useful features or training samples that are more informative than others. In this work, I shall use the attribute “reliable” to refer to such aspects that are informative in the context of a pattern recognition task. In practice, this reliability information is usually latent and must be jointly estimated during learning. I shall propose techniques to account for and exploit this inherent heterogeneity in reliability associated with samples during training of classification models. Reliability is modeled as a latent factor that governs the dependence between observed features and the corresponding annotated class label. In addition to augmenting classification models, the reliability scores also lend themselves to interpretation in other contexts, such as for multiple annotators in a crowd-sourcing task.
Speaker bio: Naveen Kumar received his B.Tech. in Instrumentation Engineering from the Indian Institute of Technology, Kharagpur. He is currently an Electrical Engineering Ph.D. candidate at the University of Southern California, Los Angeles. His research focuses on models for exploiting latent reliability information associated with features or labels in pattern recognition tasks. His broad interests lie in statistical signal processing, speech and audio processing, machine learning and robust multimodal recognition. He is a recipient of the USC Dean's Fellowship and was part of the USC team that won the Interspeech-2012 Computational Paralinguistics Challenge.

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Title: On Risk-Sensitive Reinforcement Learning: Algorithms, Analysis and Applications
Speaker: Dr. L.A. Prashanth
Venue: EE 217 (MMCR)
Date and time: 22nd January 2016, 4:00-5:00 pm
Abstract:

In many sequential decision-making problems, one may want to manage risk by minimizing some measure of variability in rewards in addition to maximizing a standard criterion. Variance related risk measures are among the most common risk-sensitive criteria in finance and operations research. While the theory of risk-sensitive Markov decision processes (MDPs) is relatively well-understood and that we know many of such problems are computationally intractable, not much work has been done to solverisk-sensitive MDPs in a typical reinforcement learning (RL) setting.
In this talk. I will describe a few important steps that I took to approximately solve risk-sensitive MDPs - both discounted and average reward. For each formulation, I will first define a measure of variability for a policy, which in turn gives us a set of risk-sensitive criteria to optimize. For each of these criteria, I derive a formula for computing its gradient and then devise actor-critic algorithms that operate on three timescales - a temporal difference (TD) critic on the fastest timescale, a policy gradient (actor) on the intermediate timescale, and a dual ascent for Lagrange multipliers on the slowest timescale. In the discounted setting, I will point out the difficulty in estimating the gradient of the variance of the return and then present a simultaneous perturbation approach to alleviate this problem. The average setting, on the other hand, allows for an actor update using compatible features to estimate the gradient of the variance.
The analysis of the aforementioned risk-sensitive RL algorithms involves statistical aspects of the popular TD algorithm with function approximation and I will present concentration bounds that I derived in a recent work for the latter algorithm. These bounds help in establishing the convergence of risk-sensitive RL algorithms using the ordinary differential equations (ODE) method to locally risk-sensitive optimal policies.
Finally, I will demonstrate the usefulness of the risk-sensitive RL algorithms in a traffic signal control application. In particular, the empirical results show that risk-sensitive RL algorithms exhibit lower variance in the delay experienced by road users, as compared to corresponding risk-neutral RL variants.
Speaker bio: Prashanth L.A. is currently a postdoctoral researcher at the Institute for Systems Research, University of Maryland - College Park. Prior to this, he was a postdoctoral researcher at INRIA Lille - Team SequeL from 2012 to 2014. From 2002 to 2009, he was with Texas Instruments (India) Pvt Ltd, Bangalore, India. He received his Masters and Ph.D degrees in Computer Science and Automation from Indian Institute of Science, in 2008 and 2013, respectively.  He was awarded the third prize for his Ph.D. dissertation, by the IEEE Intelligent Transportation Systems Society (ITSS). He is the coauthor of a book entitled `Stochastic Recursive Algorithms for Optimization: Simultaneous Perturbation Methods', published by Springer in 2013.His research interests are in reinforcement learning, stochastic optimization and multi-armed bandits, with applications in transportation systems, wireless networks and recommendation systems.

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Title: Signal Processing and Machine Learning for Carnatic Music
Speaker: Prof. Hema Murthy
Venue: EE 217 (MMCR)
Date and time: 21st January 2016, 3:30 pm-5:00 pm
Abstract:
Carnatic Music is based on a particular genre of Indian Music belonging to the South India. Similar to HindustaniMusic, Carnatic Music is also based on the oral tradition and, therefore hardly any music annotated accurately. The purpose of the research is to develop signal processing and machine learning algorithms that can be used to characterise and organise Carnatic Music to enhance listener experience. In Carnatic Music, a composition is based on a “r¯a ga” or melody. Each melody is based on a scale. But a scale is inadequate to represent the melody completely. Owing to the extensive use of gamak¯as two melodies may be identical in terms of scale but completely different in terms of gamak¯as. R¯a gas are characterised by signature phrases. The phrase is essentially a melodic motif. Therefore the first task was to characterise and identify the melodic motifsthat can characterise “r¯a gas”. This is not trivial since a “r¯a ga” is defined with respect to the tonic (shadja) of the performer (vocal or instrumental). Any meaningful analysis would first require that we first normalise the music with respect to the tonic. A number of different signal processing and dictionary based algorithms are developed for tonic identification from the compositions. Success rates between 90-100% have been obtained for both Carnatic music and Hindustani music. To understand what a motif is, a motif database was first created by musicians. Since motifs can be characterised by pitch contours, the basic idea in motif recognition was to arrive at a set of basic primitives, in terms of which signature phrases of a r¯a ga can be defined. Owing to the differences in schools of music, it was observed that a motif is a T-F trajectory and should not be quantised further. Using a musician in the loop, a variant of the rough longest common subsequence algorithm is developed to query motifs defined by musicians. Next automatic identification of motifs is attempted. In Carnatic music compositions are rich in motifs. Using tonic normalised spectral features, a composition is first segmented in lines. Longest common subsequence set is used to determine the common motifs across compositions. A cohort set of phrases for every r¯aga is also determined. R¯aga verification is performed using the motifs of a r¯aga and its cohorts. In Carnatic Music, percussion has a very important role. There are 108 talas and each tala can be characterised by different nadais. The number of strokes used by a musician vary from a mere 10 to about 41. Every stroke is made up of an onset, attack and decay. Considering the mridagam stroke as an AM-FM signal, the waveform is segmented at the stroke level using syllable-based segmentation algorithms. As there can be variants in the strokes HMM-based models are built for every stroke and recognised. Language models derived from the training data are used to reduce the error in transcription. Finally, Carnatic music concert recordings are continuous recordings. Using applauses as a cue, the concert recordings are segmented into items. Using informal reviews available from the web, the items that make up a concert are archived.
Speaker bio: Prof. Hema Murthy is a Professor at the Department of Computer Science and Engineering, Indian Institute of Technology (IIT), Madras. She obtained a Masters from McMaster, Canada in 1985 and PhD from IIT Madras in 1992. She held visiting positions at SRI International, Menlo Park, TIFR Bombay. Her research interests include Speech and music processing, speaker and language recognition, network traffic analysis, machine learning, data mining, etc. She has supervised 68 Masters theses and 42 research students. She is well known for her contributions to group-delay analysis in speech. She received the IBM Faculty award in 2006, Prof. Rais Ahmed Memorial Lecture Award from the Acoustical Society of India in 2012, and GE innovation award in 2012.

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Title: Developments in Power Sector – An overview of System Analysis, Planning and Operation
Speaker: Prof. Thukaram
Venue: EE 217 (MMCR)
Date and time: 1st January 2016, 4:00-5:00 pm
Abstract:
Electric Energy is the most versatile form of energy. It can be generated in large quantities, transmitted over long distances and utilized efficiently. It has flexibility and most amenable to effective control. The per capita consumption of energy has become the symbol of a country’s progress. The first DC generating station at Pearl Street, New York city was commissioned by Thomas Alva Edison in 1882. In India Hydro power stations were commissioned at Darjeeling, West Bengal in 1898, and at Shivasamudram, Karnataka in 1902. Since that time the developments in power generation, transmission and distribution have been phenomenal. Present day Power Systems are growing in size and complexity with interconnections of regional grids, introduction of EHV/UHV AC, High Voltage Direct Current (HVDC) transmission systems and also the induction of sophisticated control devices such as Flexible AC Transmission Systems (FACTS). Worldwide there exists a serious concern with dwindling fuel reserves and the potential impact of conventional energy systems on the environment. The increasing rate of depletion of conventional energy sources, escalation in electric energy costs associated with fossil and nuclear fuels, and enhanced public awareness of potential environmental impacts of conventional energy systems has created an increased interest in the development and utilization of alternate Renewable sources, such as wind and solar energy Recent trends in the Electric Power utility industry in developed and developing countries have been towards increased un-bundling of the services provided by the utilities. Indian Power Systems are also under going the restructuring process. The planning, operation and control of these systems pose complex technical challenges. Researchers are working to address these challenges. The lecture covers some of the milestones in the development of the Indian Power Sector and also provides a brief overview of planning and operational studies intended to prevent catastrophic accidents and major blackouts.

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Title: Power System Operation and some Stability issues
Speaker: Prof. Indraneel Sen
Venue: EE 217 (MMCR)
Date and time: 18th December 2015, 3:30-4:30 pm
Abstract:
Modern power systems are interconnected, non linear, time varying systems. Such a system which is continuously subjected to large and small impacts must provide acceptable quality of power at all times. The system must be able to meet the continually changing load demands for active and reactive powers to maintain the voltage and frequency within reasonable limits. The system must operate with a high degree of reliability without major interruptions. This requires three distinct areas of operation and planning. 1. Power system planning 2. Operation planning and 3. Real time operation In spite of considerable efforts in planning and operation Blackouts do happen. The proposed talk will address some of these issues and include, * A historical perspective of worldwide development of power system including in India * The Indian power system operational and control structure * The reasons blackouts occur * Analyses of major blackouts in India * Power system stability and its categorizations * The concept of Damping and Synchronizing restoring torques * The missing link of ‘damping torque’ during planning * The concept of Power System Stabilizers * Some of the design methodologies of Power System Stabilizers developed in our lab. The Future?

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Title : Hand segmentation using 3D pointclouds for Hand gesture recognition
Speaker : Mr. Shome Subhra Das
Advisor : Prof. K. R. Ramakrishnan
Date : 11/12/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Hand gesture recognition is an important part of Human Computer Interaction(HCI)systems. Hand gesture estimation is a challenging problem due to complexity in articulations of the hand, self occlusions and variation in hand shapes. Due to availability of cheap depth sensors research on hand gesture recognition has received a great boost. Reliable identification of the hand region is an important step for hand gesture recognition. We propose a method for hand region segmentation with accurate wrist detection from depth data. This method converts depth data to 3D pointcloud to use techniques in 3D. Area estimation, 3D edge recognition & anthropometric calculations are used to accurately determine the location of wrist thereby enabling correct segmentation of hand region. The method is not restricted to frontal views & works even for deformed hand shapes & with small objects in hand. Preliminary experiments with real hand depth data in various poses, orientations & with objects demonstrate the accuracy and robustness of our hand segmentation system.

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Title : Fixed Frequency Static Phase Converter For Single-Phase Power Grids
Speaker : Mr.Anil Kumar Adapa
Advisor : Prof. Vinod John
Date : 4/12/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract:Single phase grids are commonly used to power the communities with low power demand and sparsely located load centers due to low cost feature. Single phase microgrid is a first choice to provide electricity to the aforementioned places with no access to the electric grid. In either case, usage of three-phase motors as well as generators is limited, which calls for double conversion using power electronic converters.
An attractive feature of grid interactive static phase converters is the ability to deliver a fraction of total load power directly from the source. This talk presents a reduced switch, fixed frequency static phase converter that not only reduces the size and cost of the system but also results in better efficiency. This presentation covers (1) control strategy for the proposed static phase converter with active front end converter that leads to improved dc bus utilization and (2) a simple inverter control to provide balanced three-phase voltage. The presentation ends with simulation results of powering three-phase loads from a single-phase grid as well injecting power from a three-phase machine to single-phase grid using the static phase converter which endorses the controller design.

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Title : Better Electromagnetic Shielding using Polymer Composites
Speaker : Joseph Vimal Vas
Advisor : Dr. M. Joy Thomas
Date : 20/11/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Electromagnetic waves are used routinely for a variety of applications to improve the quality of life. This has led to an increased electromagnetic pollution in the environment. These EM waves can adversely interact with many sensitive electronic devices leading to temporary or permanent damage of these devices or even loss of life. The interference thus caused by electromagnetic fields is extremely difficult to identify and control especially in the automobile sector where the use of on board electronics is continuously on the rise. Other industries are also heavily relying on sensitive electronic circuitry for various applications. Reducing the ambient fields by smart design of electronics is no longer a viable option and electromagnetic shielding has become very important in the design and fabrication of sensitive electronic systems. Traditionally used metallic shields may be less attractive because of their large metal content and lack of flexibility. The advent of conducting polymers has brought an interesting alternative for electromagnetic shielding materials. Intrinsically Conducting Polymers and conducting polymer composites have very low metal content and being polymeric they can be easily processed. Another problem is the estimation of the shielding effectiveness in anisotropic materials. Theoretical estimation of the shielding effectiveness becomes difficult especially when the characteristics vary with the frequency of interest. ASTM D 4935 standard provides a method for measuring the shielding effectiveness of thin samples in the 30 MHz – 1.5 GHz frequency range. In my work, the conductivity and shielding effectiveness of silicone rubber filled with carbon nanofibers (CNF) and Multiwalled carbon nanotubes (MWCNT) are studied. A test jig as per ASTM D 4935 has been developed for the measurement of shielding effectiveness. The filler loading required to turn the polymer conducting, depends on the percolation threshold. For fillers with large aspect ratio, the percolation threshold is very low which was seen for both the fillers. The conductivity beyond the percolation threshold is majorly governed by the electron tunnelling between the filler particles and this puts a restriction on the conductivity. In order to overcome this problem, the fillers were functionalised with nano- Ag fibers to create wafers of extremely high conductivity. The polymer was then adsorbed into the wafer matrix to achieve the required mechanical properties. The talk will also present some of the theoretical studies carried out to understand the influence of the type of fillers and their orientation inside the polymer matrix on the shielding effectiveness.

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Title : Processing RGB-D Data for Entertainment Systems
Speaker : Suraj K
Advisor : Prof. K. R. Ramakrishnan 
Date : 13/11/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Thanks to the advances in research in display systems, various new forms of entertainment systems are now being created. Unlike conventional devices such as televisions that provide minimal realistic experience to the viewer along with no scope for any engagement, these systems create an "immersive" experience, a more realistic experience. Further, these systems also allow the user to be more engaging, the user "walk through" the scene. However, creating content and processing data to facilitate the usage of such systems is still an open problem. Video streams are captured from standard cameras that are coupled with depth sensors, which is also called RGB-D Video. In this talk, we discuss about two such entertainment systems, the Virtual Reality and Free Viewpoint Television. We discuss about the challenges posed when RGB-D video are used to create contents for these systems. Finally, we discuss about an application of RGB-D data i.e., synthesizing a virtual video using RGB-D video streams captured from multiple cameras.

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Title: Automatic Video Mashup Techniques for Multimedia Systems
Speaker: Dr. Mukesh Saini
Venue: EE 217 (MMCR)
Date and time: 9th November 2015, 3:30-4:30 pm
Abstract:
In a video mashup system, multiple videos are combined to produce a single representative video. The output video can be built based on different criteria depending on the application requirement. I will present three mashup techniques in this talk. In the first technique, we combine different mobile recorded videos of live performances to produce MTV style videos for broadcasting and sharing. The shot transitions are learned from professionally edited videos. In the second approach, we create video mashups for security operators for dynamic load sharing in a multi-camera and multi-operator scenario. Finally, I will present a technique to create low resolution mashup from single high definition video for surveillance through handheld devices.
Speaker bio: Dr. Mukesh Saini is Postdoctoral Associate at New York University in Abu Dhab.

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Title: SMART GRIDS: An Overview
Speaker: Prof. P. S. Nagendra Rao
Venue: EE 217 (MMCR)
Date and time: 6th November 2015, 4:00-5:00 pm
Abstract:
The concept of Smart grids has been attracting the interest of not only many stake holders in the Electrical Power Industry but also of the general public , in the recent past. The aim of this talk is to give a broad view of the various issues in the development of such systems. The core idea of smart grids is about exploiting the phenomenal progress the in communication and computer technologies, to modernise all aspects of the power systems. In this talk we first look at the evolution of the concept of Smart Grids in the context of the history of application of computer and communication technologies in Power Systems and understand the contemporary vision for Smart Grids. Various technologies- hardware, software and materials that are expected to help in building the smart grids of the future are introduced and their novelty as well as potential are assessed. We look at the efforts in India in adopting the Smart Grids technologies and also some experiences gained from a pilot project-the Pondicherry Smart Grid Project. Some key smart grid technologies such as Demand Response/Consumer participation, Self healing technologies, Cyber security, micro grids etc are assessed in the Indian context. Finally, I share my ‘crystal ball’ view of the Power Systems of the future.

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Title:Transmission Power Control Using CTMC Based Interference
Speaker: K. Srilatha
Advisor: Prof. Lawrence Jenkins and Prof. P.S. Sastry
Venue: EE 217 (MMCR)
Date and time: 30th October 2015, 4:00-5:00 pm
Abstract:
Transmission power control (TPC) considers the fixing of the transmission power level. TPC is an important problem in energy constrained networks like wireless sensor networks. The existing methods of power control vary the power level for every node or use the same power level (uniform) across the nodes. We consider uniform power control with carrier sense multiple access (CSMA) protocol. Interference signals from nodes add to the desired signal at the receiver and affect the performance indices such as bit error rate (BER). Hence, characterization of interference is crucial. The conventional models of interference either consider transmissions as Poisson distributed or approximate interference with Gaussian noise. In our work, we model the interference from nodes using continuous time Markov chain. The stationary probabilities of the Markov chain gives the probability of interference from the interfering transmitters. The model is verified using simulations.

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Title: Study of Propagation of Ultra-Wide Band Electromagnetic Pulse through a Dispersive Soil Medium for the Detection of Buried Unexploded Ordnance
Speaker: Vijayakumar Solaiselvam
Advisor: Dr. Joy Thomas
Venue: EE 217 (MMCR)
Date and time: 22nd October 2015, 4:00-5:00 pm
Abstract:
Buried Unexploded ordnance (UXO) poses a serious humanitarian problem. At Present, there is no single equipment/system available to detect the unexploded buried ordnance (UXO), which fully satisfies the United Nations Mine Action Standard (UNMAS) requirements for safe removal and disposal of such ordnance. Due to the attenuation characteristics of electromagnetic wave in moist soil, it is difficult to detect UXO using low power electromagnetic waves. So there is a need for using pulsed Ultra Wide band (UWB) high power electromagnetic waves to detect the buried UXO. Objective of this thesis is to carry out detailed parametric study of the high Power EM wave landmine detection system.

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Title: A class-specific speech enhancement for phoneme recognition
Speaker: Nazreen P.M
Advisor: Prof. A. G. Ramakrishnan
Venue: EE 217 (MMCR)
Date and time: 16th October 2015, 4:00-5:00 pm
Abstract:
The performance of speech recognizer degrades significantly in the presence of noise. Noise distorts the spectrum of speech and hence degrades the performance. In this work, we analyze the impact of dictionary based speech enhancement on phoneme recognition. The improvement in recognition performance after enhancement with class-specific dictionaries is examined over that with a class-independent dictionary. All experiments in this study are performed in a speaker independent manner with speech data from TIMIT corpus and noise samples from NOISEX-92 database. Using KSVD, the following four types of dictionaries have been learned: class-independent, manner-of-articulation-class, place-of articulation-class and 39 phoneme-class. Initially, a set of labels are obtained by recognizing the speech enhanced using the class-independent dictionary. Using these approximate labels, the corresponding class-specific dictionaries are used to enhance each frame of the original noisy data, and this enhanced speech is recognized further. The results show that in most cases, the 39 phoneme-class based enhancement outperforms the mannerof-articulation and place-of-articulation class based enhancement, in terms of the recognition accuracy.

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Title: Electrically Triggered Thyristor based Solid State Crowbar
Speaker: Subhash Joshi T G
Advisor:
Prof. Vinod John
Venue: EE 217 (MMCR)
Date and time: 9th October 2015, 4.00 PM
Abstract: High Voltage Power Supplies (HVPS) are used in many application like (i) Radar (ii) X-rays (iii) Plasma applications (iv) Electrostatic precipitator (v) Corona generators (vii) Particle accelerators etc. In most of these applications the HVPS feeds power to Micro Wave (MW) tubes. The cost of MW tubes are multiples of the cost of the HVPS. Hence MW tubes are to be protected from various fault conditions, like over voltage, short circuit or any other event which trigger protection circuits.
Crowbar are mainly used as a protection for MW tubes. Conventionally it is build with ignitron or thyratron or spark gap. Ignitron and thyratron are restricted now a days due to use of mercury gas where spark gap demand frequent maintenance even after each crowbar operation. The research is now to replace these devices with semiconductor switch called solid state crowbar (SSC).
The presentation is on the development of Solid State Crowbar having high reliability, fast operation, wide operational voltage range, high peak pulse power rating and low cost. The presentation details various research outcomes made during the development of Solid State Crowbar.

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Title: Developments in Power Sector – An overview of System Analysis, Planning and Operation
Speaker:Prof. D. Thukaram
Venue:
EE 217 (MMCR)
Date and time: 18th September (Friday) 2015, 4.00 PM
Abstract: Electric Energy is the most versatile form of energy. It can be generated in large quantities, transmitted over long distances and utilized efficiently. It has flexibility and most amenable to effective control. The per capita consumption of energy has become the symbol of a country’s progress. The first DC generating station at Pearl Street, New York city was commissioned by Thomas Alva Edison in 1882. In India Hydro power stations were commissioned at Darjeeling, West Bengal in 1898, and at Shivasamudram, Karnataka in 1902. Since that time the developments in power generation, transmission and distribution have been phenomenal. Present day Power Systems are growing in size and complexity with interconnections of regional grids, introduction of EHV/UHV AC, High Voltage Direct Current (HVDC) transmission systems and also the induction of sophisticated control devices such as Flexible AC Transmission Systems (FACTS). Worldwide there exists a serious concern with dwindling fuel reserves and the potential impact of conventional energy systems on the environment. The increasing rate of depletion of conventional energy sources, escalation in electric energy costs associated with fossil and nuclear fuels, and enhanced public awareness of potential environmental impacts of conventional energy systems has created an increased interest in the development and utilization of alternate Renewable sources, such as wind and solar energy Recent trends in the Electric Power utility industry in developed and developing countries have been towards increased un-bundling of the services provided by the utilities. Indian Power Systems are also under going the restructuring process. The planning, operation and control of these systems pose complex technical challenges. Researchers are working to address these challenges. The lecture covers some of the milestones in the development of the Indian Power Sector and also provides a brief overview of planning and operational studies intended to prevent catastrophic accidents and major blackouts.

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Title : Dual Comparison One Cycle Control for single phase AC-DC power converters
Speaker : Nimesh V
Advisor : Prof. Vinod John
Date : 11/09/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Classical control and one cycle control of current are popular methods used to generate PWM pulses in active rectifiers for ac-dc power conversion. One cycle control has lower control complexity and can be implemented using simple analog circuits and digital circuits, when compared with the classical approach. However, it also suffers from distortion in input current when the converter is lightly loaded and steady state dc offset in input current under all load conditions. In this paper a new dual comparison one cycle control is proposed which overcomes the above limitations. The proposed control strategy makes use of two comparators which compares sensed input current and inverted sensed input current with a saw-tooth carrier to generate gating signals for switching devices.

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Title : Algorithms for Learning Sparsifying Transform
Speaker : Mr. Subhadip Mukherjee
Advisor : Prof. Chandra Sekhar Seelamantula
Date : 4/09/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: The sparsity of signals and images in a suitable transform domain or in a dictionary has been exploited extensively in numerous signal processing applications. Recently, learning sparsifying synthesis dictionary has received considerable attention in applications, such as denoising, image inpainting, super-resolution etc. However, the idea of learning a sparsifying transform has been relatively less explored. In this talk, we will address the problem of learning a well-conditioned sparsifying transform adapted to the data and develop efficient algorithms for solving the problem. We will illustrate the computational advantage of learning a transform over learning a synthesis dictionary and show that the approach holds promise for efficient signal sparsification and denoising, using experimental results on synthesized and real signals.

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Title : Control of Ultracapacitor based Bidirectional DC-DC Converters for Ride Through Applications
Speaker : K. Saichand
Advisor : Prof. Vinod John
Date : 21/08/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Ultracapacitor based bidirectional DC/DC converters find applications in hybrid electric vehicles, traction and transport systems, power-quality, and in micro-grids for energy backup provision. Ultracapacitor based DC/DC converters essentially handle critical loads in case of momentary power main failures and for addressing peak power demands. The conventional control techniques which ensure seam-less mode transition for the Ultracapacitor (UC) based bidirectional DC/DC converters such as duty-ratio based control or unified control strategy are well established for current control based applications. But these control techniques does not allow different control structures for both charging and discharging modes which is crucial for the UC based ride-through applications where the charging and discharging times are critical. To address these issues, a separate switch control strategy using PWM block method is proposed which not only ensures seam-less transition between charging and discharging control modes, but also identifies control modes accurately which is key to the separate switch control. The advantages of such a switch control using PWM block method compared against conventional controls is elucidated. The advantage of using PWM block method as a mode change logic is also presented. The proposed control strategy has been verified in simulations and experimentation and the mode identification algorithm proposed is found to work well.

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Title: Self-organizing Power-electronic Systems
Speaker: Prof. Sairaj Dhople, University of Minnesota, Minneapolis
Venue: EE 217 (MMCR)
Date and time: 18/08/2015, 4.00 PM
Abstract: Next-generation power systems are expected to be sustainable in composition, distributed in operation, and resilient to extenuating weather conditions. A compelling framework to seek these goals is provided by low-inertia microgrids. These are a heterogenous collection of renewable-energy resources and energy-storage devices that are interfaced to an AC electrical distribution system through power-electronic inverters. In this talk, we focus on islanded microgrids that are controlled and operated independently from the bulk power system. We introduce a control method called Virtual Oscillator Control for synchronizing and regulating a collection of islanded power-electronic inverters without communication. The premise of virtual oscillator control is to program power-electronic inverters to emulate the dynamics of Lienard-type nonlinear oscillators. A system with virtual oscillator control is self-organizing in that the inverters synchronize their AC outputs, share the load, and collectively maintain voltage and frequency within regulatory limits without any supervisory control. A stable power system emerges innately by design, and the only form of communication is that provided by the physical electrical network that couples the inverters (oscillators). The proposed technique is developed using concepts from nonlinear control theory and experimental results are presented to validate the concept. The system-theoretic methods that will be outlined in this talk are relevant to the broad domain of synchronization phenomena in complex networks of coupled nonlinear oscillator circuits; a pervasive research topic in various scientific disciplines including neuroscience, physics, systems biology, social networks, and engineering.
Speaker bio: Sairaj Dhople received the B.S., M.S., and Ph.D. degrees in electrical engineering, in 2007, 2009, and 2012, respectively, from the University of Illinois, Urbana-Champaign. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Minnesota in Minneapolis, where he is affiliated with the Power and Energy Systems research group. Dr. Dhople received the NSF CAREER Award in 2015. He currently serves as an Associate Editor for the IEEE TRANSACTIONS ON ENERGY CONVERSION. His research interests include modeling, analysis, and control of power electronics and power systems with a focus on renewable integration.

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Title: Indian Buffet Process for vision applications
Speaker: Suresh Kirthi K
Advisor: Prof. K R Ramakrishnan
Venue: MMCR, EE
Date & Time: 14/08/2015, 4 pm
Abstract: Indian Buffet Process(IBP) is a Bayesian Non-parametric prior used for latent feature analysis. It tries to model a case where an observation is modeled to be composed of unlimited latent features. The most popular and reasonably computable model of IBP is Linear Gaussian model, where the latent features are estimated using random sampling and variational inference under Gaussian assumption.
As an application to computer vision we have tried to explore the possibility of using IBP for some of the vision problems like: scene recognition, object recognition and canonical views.

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Title: High Frequency response of windings.
Speaker: Santosh J
Advisor: Prof. Udaya Kumar
Venue: MMCR, EE
Date & Time: 07/08/2015, 4 pm
Abstract: Power transformer forms one of most critical and expensive equipment in the electric power network. About 29% of its failure is traced on to the electrical disturbances and the consequential insulation failures in the winding and bushings. Classically, the electric stress distribution on the winding under normal operating voltages, as well as, the switching and lightning surges is analyzed through distributed circuit models.
The transformer in a gas insulated substation is subjected to Very Fast Transient Overvoltages (VFTO). These surges can have a rise time less than 20 ns and significant frequency ranging up to 100 MHz. The associated wavelengths are much smaller than the actual length of the winding thereby the use of distributed circuit model or its variant is put into a serious question.
Similarly, the Partial Discharges (PD) occurring in the insulating system involves a local current pulse of rise time less than few nanoseconds. The propagation of such current pulses in the winding would invoke a similar question.
Apart from the above two, even the penetration of very fast rising lightning surge through an ultra high voltage class power transformer is found to be inadequately simulated by the routinely employed distributed circuit model.
Transformers are subjected to various stresses, our concern being electrical stresses due to very fast transient overvoltages (VFTOs) in transformer connected to GIS and Partial discharge (PD) propagation in windings.
In order to primarily address the above issue, the present work is taken up. The goal of the present work is to investigate on to the propagation characteristics of VFTO and possibly the PD pulses through the representative winding configuration and quantify the resulting stress levels for the former. Subsequently, it aims to draw the upper frequency limit for the variants of the distributed circuit model for the transformer winding.
To study the propagation characteristics, time-domain thin-wire formulation of the electric field integral equation will be employed. Suitable modification to accommodate the cross section of the conductor is planned. The in-house code can be switched to a quasi-static domain and this will be employed to derive the upper frequency limit for the distributed circuit modeling approach.

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Title: Multiview Video + Depth Data Acquisition, Compression and Application.
Speaker: Hemanth S
Advisor: Prof. K. R. Ramakrishnan
Venue: MMCR, EE
Date & Time: 31/07/2015, 4 pm
Abstract: Advances in display and camera technology have enabled 3D scene communication, stereoscopic displays are an example. But for display systems such as Auto-stereoscopic displays necessitates multi-camera scene acquisition along with depth information for each view. Depth information can be used to generate views from virtual viewpoints at the decoder. In this talk we present our work on Multiview Plus Depth data acquisition and compression.

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Title: Adjusted Load Flow Solutions in Complementarity Framework
Speaker: Shantanu Chakrabarty
Advisor: Prof. P S Nagendra Rao
Venue: MMCR, EE
Date & Time: 24/07/2015, 4 pm
Abstract: Under Normal Conditions, electrical transmission networks work in their steady state and the calculations required to determine the characteristics of this state is termed as load flow or power flow.The solution is expected to provide information on the voltage angles and magnitudes,power flows across the individual transmission lines and losses.The network is represented by linear, bilateral and lumped elements but due to power and voltage constraints, the problem is non-linear.The solutions of the load flows are adjusted to incorporate the generator reactive power constraints, on load tap changing transformers,phase shifters, area interchange control and provision can also be made to include the constraints due to FACTS devices.This research work is concerned with the incorporation of complementarity framework to model the constraints due to devices mentioned above and incorporate them in the conventional load flow in matrix vector as opposed to solving it as an optimization problem.

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Title: Integrating Dynamic Data for Predictive Operations in Power Systems
Speaker: Prof. Le Xie, Texas A&M University, USA.
Venue: MMCR, EE
Date & Time: 15th July 2015, 4 pm
Abstract: This talk concerns the handling and utilization of streaming data (such as synchrophasors and smart meters) for enhancing power system real-time physical and market operations. The first part of the talk analyzes the dimensionality of the phasor measurement unit (PMU) data under both normal and abnormal conditions. We observe that the underlying dimensionality is extremely low despite the high dimensions of the raw PMU data. Justification of this observation is proposed using linear dynamical systems theory. A novel early anomaly detection algorithm based on the switch of core subspace at the occurrence of an event is proposed. The second part of the talk presents our work of quantifying benefits of incorporating look-ahead dispatch with responsive demand from Electric Reliability Council of Texas (ERCOT) data. Demand elasticity at ERCOT is estimated, and the market price behavior with price responsive demand is analyzed. This talk concludes with several open interdisciplinary opportunities that would synergistically contribute towards a low-carbon smart grid.
Speaker bio: Le Xie is an Associate Professor (Sep 2015) in the Department of Electrical and Computer Engineering at Texas A&M University. He received B.E. in Electrical Engineering from Tsinghua Universityin 2004, S.M. in Engineering Sciences from Harvard in 2005, and Ph.D. from Carnegie Mellon in 2009. His industry experience includes internshipsat ISO-New England and Edison Mission Energy Marketing and Trading. His research interest includes modeling and controlin data-rich large-scale systems, grid integration of low-carbon energy resources, and electricity markets. Dr. Xie received the National Science Foundation CAREER Award,and theDepartment of EnergyRalph E. Powe Junior Faculty Enhancement Award. He was Texas A&M Engineering Select Young Fellow in 2013. He is an Editor of IEEE Transactions on Smart Grid, and the founding chair of IEEE Power and Energy SocietyWorking Group on Big Data Analytics for Grid Operations. He and his students received the Best Paper awards at North American Power Symposium and IEEE SmartGridComm2012. He is the founding faculty advisor of A&M Energy Club.

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Title: Exact Phase Retrieval for Certain Classes of Signals
Speaker: Basty Ajay Shenoy
Advisor: Prof. Chandrasekhar Seelamantula
Venue: MMCR, EE
Date & Time: 03/07/2015, 4 pm
Abstract: The Fourier transform (spectrum) of signals are complex functions and are characterized by their magnitude and phase spectra. Phase retrieval is the reconstruction of the phase spectrum from the measurements of the magnitude spectrum of a signal. Such problems are encountered in imaging modalities such as frequency-domain optical coherence tomography (FDOCT), quantitative phase microscopy, digital holography, etc., where only the magnitudes of the wavefront can be detected by the sensors. The phase retrieval problem is a priori ill-posed, since an infinite number of signals can have the same magnitude spectrum. Typical phase retrieval techniques rely on certain prior knowledge about the signal, such as its support or sparsity, to reconstruct the signal. We consider two classes of signals, one being the two-dimensional parametric signals, the other being signals in shift-invariant spaces. In each of these cases, we develop phase retrieval methods that guarantee exact reconstruction when the measurements are noiseless. Further, we show applicability of the proposed methods for FDOCT image reconstruction.

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Title: Discovering compressing serial episodes from event sequences
Speaker: Ibrahim A
Advisor: Prof. P. S. Sastry
Venue: MMCR, EE
Date & Time: 19/06/2015, 4 pm
Abstract: Frequent pattern mining is an important subfield of data mining with lots of important applications. It is the process of extracting interesting patterns in the data, where a pattern could signify, depending upon the type of the data, some local inherent structure or dependencies among certain variables or attributes of the data. Even though, there are many efficient algorithms for discovering frequent patterns, the number of frequent patterns could be very huge to make any use of these patterns. In this talk, we look at the problem of selecting a small subset of non-redundant episode patterns from a sequence data, that best represents the data. We propose a scheme for finding a small set of non redundant serial episodes, that summarizes and represents a given data sequence, using the Minimum Description Length (MDL) principle. The effectiveness of the selected serial episodes by our method over other summarization based schemes is shown with respect to three criteria: the interpretability of the patterns with respect to the data, the compression achieved while encoding the data using the selected serial episodes and the accuracy achieved in classification when the selected serial episodes are used as features.
In the second part of the talk, we propose a similarity measure to compare two sets of patterns. We prove that the similarity measure satisfies the conditions of a kernel. The measure is highly useful to find the degree of similarity between different datasets, which can be represented using sets of summarizing patterns. We show the effectiveness of our kernel based similarity measure in detecting changes in streams and also in classification.

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Title : Control and Design of Power Converters for Renewable Energy Systems
Speaker : Abhijit K
Advisor : Prof. Vinod John
Date : 12/06/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Renewable energy sources such as photovoltaic, wind are increasingly used to reduce the dependence on conventional energy sources. Renewable energy sources normally require a power converter to convert their energy into standardized form of electricity. Power converters form the interface between the source and the grid or load. They must be designed and controlled to ensure very good power quality, efficiency and reliability. In this work, two power converter topologies with transformers are developed for renewable energy systems such as photovoltaic (PV) system with low input dc voltage. Control and modulation methods are proposed to improve power quality and efficiency in these power converter topologies.
Control of grid connected power converters requires grid synchronization. This is achieved by using phase-locked loops (PLLs). PLLs can have impact on the power quality of the power converters when the grid voltage contains harmonics, unbalance and dc offsets. Detailed analysis and designs of low-complexity PLLs such as synchronous reference frame PLL (SRF- PLL) and second-order generalized integrator (SOGI) based single-phase PLL is discussed. The proposed designs ensure that the control references generated using the PLLs will have minimal distortion and dc offsets to satisfy grid interconnection standards such as IEEE 1547-2003.

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Title : Low-switching-frequency pulse width modulation techniques for high-power and high-speed induction motor drives
Speaker : Avanish Tripathi
Advisor : Prof. G. Narayanan
Date : 29/05/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Inverters based on semiconductor switches are employed now-a-days, to convert fixed-amplitude DC voltage into variable-amplitude variable-frequency AC voltage for electric motor drives and other applications. Pulse width modulation (PWM) is well known technique for operating these inverters. Sine-triangle PWM, space-vector PWM, selective-harmonic-elimination PWM and optimal PWM are some of the common PWM techniques used.
Depending upon the ratio of switching frequency and fundamental frequency (Pulse number, P), PWM techniques can be broadly divided into two streams i.e. high-switching-frequency PWM (P>21) and low-switching-frequency (LSF) PWM (P<21). LSF PWM techniques are employed for high-power electric motor drives (> 1 MW) due to constraints on switching losses. Further, due to limitation on maximum switching frequency of semiconductor switches, high speed drives (>10,000 rpm) also employ LSF PWM techniques. Due to low pulse number, the output PWM voltage contains dominating lower-order voltage harmonics. These lower-order voltage harmonics arise two major issues in the motor drives namely high total-harmonic-distortion (THD) in line current and high pulsating torque. An optimal PWM is proposed to minimize THD in line-current for complete range of operation considering a set of pulse numbers. Further, based on the optimal PWM, a hybrid PWM is proposed with maximum switching frequency of 250 Hz. The proposed PWM is compared with sine-triangle PWM with 450 Hz switching frequency. Another, optimal PWM to minimize pulsating torque is proposed for a set of pulse numbers. The proposed optimal PWMs are validated through simulations and experiments.

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Title : Scattered Data Approximation by Regular Grid Smoothing
Speaker : Bibin Francis
Advisor : Dr. Muthuvel Arigovindan
Date : 22/05/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Scattered data approximation refers to techniques which estimates the value of the underlying function from the given non-uniform measurements. Non-uniform sampling introduces rapid variations in sampling density throughout the imaging region with severe under sampling in certain regions and oversampling in some other regions. So the scattered data approximation technique must take care of these variations in sampling densities and the measurement noise to produce meaningful results. In the present work, we have adopted a variational framework in which the reconstruction problem is posed as an unconstrained optimization problem. The weighted least square term in the problem measures the accuracy of the fit and a regularization term measures the smoothness of the reconstructed function. The solution of the above optimization approach involves solving a sparse system of linear equation which can be effectively implemented by using digital filtering.

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Title : Localization of mechanical damages in a transformer winding
Speaker : Pritam Mukherjee
Advisor : Prof. L. Satish
Date : 15/05/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Localization of mechanical damage viz. displacement or deformation in a transformer winding poses many challenges. The measured frequency response is undoubtedly the most sensitive means of detecting it. Even though it is well-known that the frequency response has embedded in it relevant information pertaining to the damage, there exists no generalized method to extract and utilize it, say e.g., draw inference about location of the damage or its severity. With this motivation, a method has been developed which, at present, is able to locate any radial displacement based on terminal measurements. Theoretical formulation and experimental verification will be presented.

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Title : Machine Listening: Making sense of sounds in the environment
Speaker : K V Vijay Girish
Advisor : Prof. A G Ramakrishnan
Date : 08/05/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Machine listening is the latest research area in the field of audio. Getting useful information about sounds in the environment is the first step in machine listening. A dictionary learning based algorithm is proposed to classify a sample audio signal as one amongst a finite set of different environmental audio sources. Cosine similarity measure is used to select the atoms during dictionary learning. Based on three objective measures proposed, namely, signal to distortion ratio, the number of non-zero weights and the sum of weights, a frame-wise source classification accuracy of 98.2% is obtained for twelve different sources.

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Title : Correlation between Corona and RIV in Substation Hardware
Speaker : Debasish Nath
Advisor : Prof. Udaya Kumar
Date : 01/05/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Transmission of Electric Power from Generating stations to the load centers are done at very high voltages. Due to the inherent geometry, the line and substation hardware of EHV and UHV class can generate high Electric fields. This results in local ionization of air leading to a visual discharge called Corona. In addition, it also produces a hissing noise and leads to problematic Electromagnetic Interference. Extensive work has been carried out on this problem, however, limited to measured currents or assumed induced current pulse as the basis for any theoretical calculation. However, the phenomena is more complicated as the electron avalanche is in space surrounding the conductor and it produces its own electromagnetic field. The coupling of this field to the conductor is in different proportions and has different frequency characteristics. The quantification of this requires adequate representation of the associated dynamic electric fields, retardation effects and coupling mechanism. These have be aimed in the present work. This talk will elaborate on the field due to avalanche at different distances along with its indirect validation, coupling to the conductor and the difference in the frequency spectrum of the current and the actual field.

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Title : Distributed Target Tracking in Camera Networks
Speaker : Shiva Kumar K A
Advisor : Prof. K R Ramakrishnan and Dr G N Rathna
Date : 10/04/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Due to the availability of low-cost cameras and communication, camera networks are being used in applications such as wide-area surveillance, smart homes, disaster response, etc. One way to analyse the videos in camera networks is the centralized method. Here, videos from all cameras are sent to a central server. But centralized method has the following disadvantages: High communication bandwidth, high memory and computational requirement at the central server. Also, if the central server fails then the whole network fails. Distributed processing circumvents these issues. In distributed processing, there would be no central server, cameras carry out local processing and communicate with immediate neighbours to iteratively improve the results. In this talk we will discuss about distributed target tracking in camera networks using the principles of sigma point information filters and average consensus algorithm.

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Title : Numerical problems in the simulation of electromagnetic flow meter
Speaker : Sethupathy S
Advisor : Prof. Udaya Kumar
Date : 27/03/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: The numerical evaluation of the sensitivity of magnetic flowmeter is a best possible choice especially for liquid metal flow measurements. When classical Galerkin's finite element formulation is employed for this, it is known to introduce numerical oscillations at high flow rates. The magnetic field produced by the flow induced currents circulate within the pipe and it can be associated with the numerical problem. To overcome this, modified methods like stream-line upwind Petrov-Galerkin (SUPG) schemes are generally suggested in the allied areas like fluid dynamics, in which a similar dominance of advective (curl or circulation) component occurs over diffusion (divergence) component. However the direct application of SUPG scheme does not solve the problem completely.

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Title : An Alternating Minimization Approach for Sparse Blind Deconvolution
Speaker : Aniruddha Adiga
Advisor : Prof. Chandrasekhar Seelamantula
Date : 20/03/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Deconvolution is a class of inverse problems that involves estimating a signal from the observation which is a noisy version of the original signal convolved with known system response. It finds applications in image deblurring, microscopy, speech analysis, astronomy, biomedical imaging to name a few. The talk will give an overview of deconvolution and ill-posedness associated with the problem. We will then discuss about blind deconvolution, which involves estimating both the original signal as well as the system response based on the noisy observations. In particular, we will consider a class of signals which can be modelled as a convolution of system response and point-source excitations. Although ill-posed, we use structures pertaining to the underlying signals to make the problem tractable. The cost function used for estimating the signals from observations incorporates the data fidelity term and sparsity constraint on excitation. However, joint-optimization of the cost function is a non-convex problem and hence hard to solve. We develop an alternating minimization algorithm that iteratively estimates one of the signals by keeping the other fixed. We also discuss about the convergence of the algorithm. We show application of the technique for epoch extraction in speech signals and compare results with sparse linear prediction and electroglottograph.

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Title : Grid Outage and Its Prevention
Speaker : Ajit Kumar
Advisor : Prof. Indraneel Sen
Date : 13/03/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Widespread Power Outages is a major concern of power grid. Great blackouts are global phenomenon affecting millions of lives. In this talk, a brief survey of blackout will be presented followed by introduction of power system. Improving grid stability suffer from curse of dimensionality. Thereafter, a method to enhance power system stability will be presented using local measurements. In the second part of the talk, a nonlinear voltage controller designed using differential geometric theory will be discussed. Here, we will demonstrate that voltage regulation is decoupled with rotor oscillations.

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Title : Modeling and Applications of Noise in KINECT
Speaker : Avishek Chatterjee
Advisor : Prof. Venu Madhav Govindu
Date : 06/03/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: 3D scanning is used extensively in many computer vision applications, e.g. human-computer interface (HCI), virtual reality, game programming, industrial monitoring, archeology, etc. Although applications such as HCI or gaming generally demand speed rather than precision, the accuracy of the 3D reconstruction is of crucial importance for many other tasks including archeology or quality monitoring in industrial production. The recent commercial availability of inexpensive 3D cameras like Kinect has opened up new possibilities for 3D scanning and shape reconstruction. 3D scans obtained from Kinect, are easy to use, but are affected by significant amounts of noise. This talk is devoted to a study of the intrinsic noise characteristics of such depth maps, i.e. the standard deviation of noise in estimated depth varies quadratically with the distance of the object from the depth camera. We validate this theoretical model against empirical observations and demonstrate the utility of this noise model in three popular applications: depth map denoising, volumetric scan merging for 3D modeling, We also integrate this noise model in a 3D reconstruction pipeline.

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Title : Integrated CM Filter for Single-Phase and Three-Phase PWM Rectifiers
Speaker : Mohammad Hassan Hedayati
Advisor : Prof. Vinod John
Date : 27/02/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: Use of IGBT base grid connected power converters are increasing in applications such as power factor correction (PFC); adjustable speed drives (ASD), PWM rectifiers, battery chargers, active filters, etc. This is due to high efficiency, ease of control, low THD, etc. of the power converters. As the technology of semiconductor devices advances more, the power converters become more efficient. Faster devices can be switched at higher frequency and more efficiently, this makes the power converters even more attractive. However, fast turn-on and turn-off of the IGBT generate high dv/dt, which excites parasitic capacitances in the circuit. This leads to injection of narrow peaky current to ground that contains excitations at high frequencies of the spectrum. This causes problems such as shaft induced voltage, bearing currents, and high EMI/EMC noise level. Standards specify the limits of voltage disturbance on the mains by power converters for industrial, commercial, and domestic applications. This work, focuses on studying of different filter topology for single phase, parallel single phase and three phase grid connected power converter with reduced EMI and ground leakage current, different PWM methods and their impacts on EMI and leakage current, active and passive damping of the resonance oscillations in common mode (CM) and in the differential mode (DM) are investigated.

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Title : Action Recognition in Videos using Causality Descriptors
Speaker : Sanath Narayan
Advisor : Prof. K. R. Ramakrishnan
Date : 30/01/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this talk, I will discuss our causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 to show that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

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Title : Analysis of Grid Connected Doubly Fed Induction Machine – Accurate steady state equivalent model and its impact on Voltage Stability of Power Grid
Speaker : V Seshadri Sravan Kumar
Advisor : Prof. D Thukaram
Date : 23/01/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: There is a continuous increase in the installed capacity of wind generators due to lack of sufficient generation to meet ever increasing load in some countries and search for renewable energy sources in the rest. This increase in penetration requires power engineers to tackle multifold challenges related to operational and stability aspects of the grid. Increasingly popular among the class of wind turbine generating units are the variable speed generators which use Doubly Fed Induction Machines (DFIM). In this talk, we re look at various modeling aspects of DFIM and discuss in brief some key observations. In particular, the short comings of existing steady state equivalent circuit of DFIM is emphasized. Further a proposed steady state equivalent circuit of DFIM which accurately represents its behavior is presented. The last part of the talk discusses in brief some aspects of voltage stability of power grid with penetration of wind generators.

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Title : Finite-Rate-of-Innovation Signal Sampling and Reconstruction
Speaker : Mr. Satish M
Advisor : Prof. Chandra Sekhar Seelamantula
Date : 16/01/2015 (4.00 pm - 5.00 pm)
Venue : MMCR (C 241)
Abstract: In the last 5 decades there has been a rapid development in the field of digital computers and digital signal processors. With this development, the problem of representing a larger class of continuous-time signals by discrete measurements always attracted researchers from the signal processing community and other engineering/scientific fields. Among various discretization methods, Shannon’s sampling theorem for banlimited signals is well known and applied widely in practical scenarios with the help of bandlimiting filters. Since Shannon, many researchers worked to represent a larger class of non-bandlimited signals. In this talk, we focus on a particular class of signals called finite-rate-of-innovation (FRI) signals which can be represented by finite number of parameters per unit time-interval. We discuss the basics of Shannon’s sampling framework and then the topics of sampling and reconstruction methods for FRI signals. We show applications in ultrasound imaging and frequency-domain optical coherence tomography (FDOCT).

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Title: Personalized Feedback in Sensor-enhanced Social Media Systems
Name of the Speaker: Prof. Mohan Kankanhalli
Venue: EE 303
Date & Time: 10:00 hrs 12th June Thursday 2014
Abstract: This talk will first start with a very brief overview of the SeSaMe (Sensor-enhanced Social Media Centre) at NUS. Then preliminary work from two SeSaMe research projects will be presented.
The first is about real-time photography assistance. To assist photographers in taking better photos, camera devices have intelligent features, such as auto-focus and face detection, etc. But capturing high-quality photos still remains a challenge for amateur users who lack skills and training. While post-processing can improve poorly captured images, we propose a photographic assistance system where we can utilize social media to learn photography rules. The system can then provide real-time suggestions based on learning from social media which will enable novice users to capture better quality photos.
The second project is about tweeting cameras for situation awareness. Motivated by the growing popularity of social media, we propose a multi-layer tweeting cameras framework to broadcast the events-of-interest, where various levels of semantic concepts are automatically detected and tweeted like humans. We define a unified Probabilistic Spatio-Temporal data structure to represent the low-level camera-based information, where an array of operators and analysis functions are employed to extract the mid-level concepts. We also have developed a graphical concept representation method, namely concept based image (C-Mage), as an intuitive data visualization tool. We have done preliminary testing of our approach on two real-world data-sets: New York City traffic feeds and NUS canteen feeds. The studies show promising results about the effectiveness of the proposed framework.
Some of the open problems in this area will also be highlighted.
Speaker bio: Mohan Kankanhalli is a Professor at the Department of Computer Science of the National University of Singapore. He is also the Vice Provost for Graduate Education at NUS. Before becoming the Vice Provost in 2014, he was the Associate Provost (Graduate Education) during 2011-2013. Earlier, he was the Vice-Dean for Academic Affairs & Graduate Studies at the NUS School of Computing during 2008-2010 and Vice-Dean for Research during 2001-2007.
Mohan obtained his BTech from IIT Kharagpur and MS & PhD from the Rensselaer Polytechnic Institute.
His current research interests are in Multimedia Systems (content processing, retrieval) and Multimedia Security (surveillance and privacy). He also directs Singapore's National Research Foundation funded Centre for "Sensor-enhanced Social Media" (sesame.comp.nus.edu.sg).
Mohan is actively involved in organizing of many major conferences in the area of Multimedia. He was the Technical Program Co-Chair for ICMR 2014. He was the Director of Conferences for ACM SIG Multimedia during 2009-2013. He is on the editorial boards of several journals including the ACM Transactions on Multimedia, Springer Multimedia Systems Journal, Pattern Recognition Journal and Multimedia Tools & Applications Journal. He is a Fellow of IEEE.