Profile: Prakash Ishwar received the B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay, in 1996, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 1998 and 2002 respectively. From 2002 to 2004 he was an Associate Specialist Researcher in the Electronics Research Laboratory and the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. In 2005 he joined Boston University where he is currently an Assistant Professor in the Department of Electrical and Computer Engineering and a faculty member in the Information Systems and Sciences group, the Center for Information and Systems Engineering, and the Sensor Network Consortium. He is also an affiliated faculty member of the Division of Systems Engineering in the College of Enginnering at Boston University.

He received the CAREER award from the US National Science Foundation in December 2005. He served as the chair of exhibits and demonstrations at the 3rd IEEE/ACM International Symposium on Information Processing in Sensor Networks in 2004 and was a co-organizer of Berkeley-Fuse 2003, a mini-workshop on the fundamentals of sensorwebs aimed at bringing together researchers from the signal processing, radar, communications, control, and networking communities working on various theoretical aspects of sensing and sensor networks. He is a Senior Member of the IEEE, and an elected member of the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee.

Research Areas:

• Distributed Signal Processing: distributed sampling and interpolation of fields under precision and rate constraints in sensor networks.
• Network Information Theory: interactive function computation, distributed source coding, and statistical inferencing (estimation/classification) under distributed compression constraints in unreliable sensor networks; sequential rate-distortion theory for video coding; distributed video coding; information privacy, steganalysis, and secure multi-party computation.
• Image/Video Processing and Coding: video summarization, video coding, adaptive motion compensation algorithms, image denoising and restoration, wavelet-based overcomplete representations, set-theoretic and maximum entropy methods.

Note to prospective graduate students:

I work very closely with my students and generally limit the size of my research group to 3 or 4. I welcome requests for assistanships (with attached CV) as they help my recruiting efforts. However, due to the large volume of email, I regret I am generally unable to reply to the vast majority of requests; please do not be offended.