Emerging applications like large-scale wireless sensor and ad hoc networks, and wireless multimedia telephony are driving the confluence of computing, communicating, and networking. Distributed signal processing plays a key role in this revolution, not in isolation, but rather as an interdisciplinary systems component, integrated with communications, information theory, coding theory, and networking protocols.

In this talk, we will focus on the problem of distributed compression, or so-called side-information coding, highlighting the foundational role of multi-user information theory. We will highligh the theory, practice, and intuition behind this framework, and address some of our recent work in this area in the context of distributed sensor networks. We will also describe a new video coding paradigm dubbed PRISM (Power-efficient, Robust, hIgh-compression, Syndrome-based Multimedia coding), whose architecture, in stark contrast to that driving current standards-based video codecs (like MPEG), allows for a nearly arbitrary shift of computational complexity from the encoder to the decoder, making it ideally suited to the emerging class of "uplink" video transmission scenarios in wireless multimedia and surveillance systems. The theoretical foundation for PRISM is based on an extension of side-information coding under an "unknown state of nature" (sort of a "universal" Wyner-Ziv coding framework), which we will describe, together with a practical video codec built on these principles, with very promising preliminary results. Time permitting, we will show "snippets" of our work on the important supporting role of distributed compression in other distributed sensor network signal processing tasks including distributed sampling, distributed estimation, and robust transmission.

Kannan Ramchandran is an Associate Professor in Electrical Engineering and Computer Science at the University of California at Berkeley, where he joined in 1999. He received his Ph.D. from Columbia University in 1993, and was an Assistant Professor in the ECE Department at the University of Illinois from 1993 to 1999. He was a Member of the Technical Staff at AT&T Bell Labs from 1984 to 1990. His awards include two Best Paper Awards from the IEEE Signal Processing Society, the Okawa Foundation Prize at Berkeley in 2001, the Hank Magnusky Scholar award at Illinois in 1998, the Eli Jury best thesis award at Columbia University in 1993, and numerous research awards including the NSF CAREER award. His research interests include distributed signal processing, multiuser information and communication theory, image processing, wavelets and multiresolution signal processing, and unified algorithms for signal processing, communications, and networking.