SUNMONTUEWEDTHUFRISAT
Events for April 11, 2018
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Research and Technology Seminar
Wed, Apr 11, 2018 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sunil Bharitkar, Distinguished Member of Tech. Staff (HP Labs)
Talk Title: Advances in Joint Signal Processing, Perception, and Machine Learning at HP Labs
Abstract: In HP's Emerging Compute Lab, research is being conducted at the intersection of signal processing, auditory perception and machine learning to create fundamentally new experiences for differentiation in HP devices including VR HMD. In this talk we will present various techniques and algorithms, incorporating knowledge of binaural perception, machine learning, and signal processing, to enhance low-frequency perception, spatial rendering, and automated content classification. The research results have been validated through perceptual testing in large-scale studies giving statistically meaningful results. Ongoing research being conducted in the areas deep learning (stacked autoencoders and LSTM) for VR head-related transfer function synthesis, content classification, speech and multimodal biometrics, sensing towards emotion interpretation, and cancer cell data classification (jointly with Life Sciences Lab) will also be presented. The presentation will be accompanied with demonstrations.
Biography: Sunil Bharitkar received his Ph.D. in Electrical Engineering from the University of Southern California (USC) in 2004 and is involved in research in speech/audio analysis and processing including spatial audio for AR/VR, biometric & biomedical signal processing, multimodal signal processing, and machine learning. From 2011-2016 he was at Dolby leading/guiding research in audio, signal processing, haptics, machine learning, hearing augmentation, and standardization activities at ITU, SMPTE, AES. He co-founded the company Audyssey Laboratories in 2002 where he was VP of Research and responsible for inventing new technologies which were licensed to companies including IMAX, Denon, Audi, Sharp, etc. He also taught in the Department of Electrical Engineering at USC. Sunil has published over 50 technical papers and has over 20 patents in the area of signal processing applied to acoustics, neural networks and pattern recognition, and a textbook (Immersive Audio Signal Processing) from Springer-Verlag. He is a reviewer for papers at various conferences and journals. He has also been on the Organizing and Technical Program Committees of various conferences such as the 2008 and 2009 European Sig. Proc. Conference (EUSIPCO), the 57th AES Conference, SMPTE Conferences. He has also served as an invited tutorial speaker at the 2006 IEEE Conf. on Acoustics Speech and Signal Processing (ICASSP). He is a Senior Member of the IEEE, the Acoustical Soc. of America (ASA), European Association for Signal and Image Processing (EURASIP), and the Audio Eng. Soc. (AES). Sunil is a PADI diver and enjoys playing the Didgeridoo.
Host: Panos Georgiou and Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Wed, Apr 11, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jun Chen, Department of Electrical and Computer Engineering, McMaster University
Talk Title: From Gaussian Multiterminal Source Coding to Distributed Karhunen Loève Transform
Series: Joint Seminar Series Seminar Series on Cyber-Physical Systems and CommNetS-MHI Seminar Series
Abstract: Characterizing the rate-distortion region of Gaussian multiterminal source coding is a longstanding open problem in network information theory. In this talk, I will show how to obtain new conclusive results for this problem using nonlinear analysis and convex relaxation techniques. A byproduct of this line of research is an efficient algorithm for determining the optimal distributed Karhunen-“Loève transform in the high-resolution regime, which partially settles a question posed by Gastpar, Dragotti, and Vetterli. I will also introduce a generalized version of the Gaussian multiterminal source coding problem where the source-encoder connections can be arbitrary. It will be demonstrated that probabilistic graphical models offer an ideal mathematical language for describing how the performance limit of a generalized Gaussian multiterminal source coding system depends on its topology, and more generally they can serve as the long-sought platform for systematically integrating the existing achievability schemes and converse arguments. The architectural implication of our work for low-latency lossy source coding will also be discussed. This talk is based on joint work with Jia Wang, Farrokh Etezadi, and Ashish Khisti.
Biography: Jun Chen received the B.E. degree with honors in communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001 and the M.S. and Ph.D. degrees in electrical and computer engineering from Cornell University, Ithaca, NY, in 2004 and 2006, respectively. He was a Postdoctoral Research Associate in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, from September 2005 to July 2006, and a Postdoctoral Fellow at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, from July 2006 to August 2007. Since September 2007 he has been with the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada, where he is currently an Associate Professor and a Joseph Ip Distinguished Engineering Fellow. His research interests include information theory, machine learning, wireless communications, and signal processing. He received the Josef Raviv Memorial Postdoctoral Fellowship in 2006, the Early Researcher Award from the Province of Ontario in 2010, and the IBM Faculty Award in 2010. He served as an Associate Editor for the IEEE Transactions on Information Theory from 2014 to 2016.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
