Dror Baron   Postdoctoral Research Associate (2003-2006) Department of Electrical and Computer Engineering - Rice University Digital Signal Processing and Compressed Sensing Groups

• I scanned numerous photos from the last 5 years.
• M. F. Duarte, S. Sarvotham, D. Baron, M. B. Wakin, and R. G. Baraniuk, "Performace Limits for Jointly Sparse Signals via Graphical Models," Proceedings of the Sensor, Signal and Information Processing Workshop (SenSIP), Sedona, AZ, May 2008 (pdf, poster).
• M. F. Duarte, S. Sarvotham, M. B. Wakin, D. Baron, and R. G. Baraniuk, "Theoretical Performace Limits for Jointly Sparse Signals via Graphical Models," Technical Report ECE-0802, Electrical and Computer Engineering Department, Rice University, July 2008 (pdf).

I received B.Sc. from the Electrical Engineering Department at the Technion - Israel Institute of Technology and was a member of the Technion's Program for Outstanding Students. Following my graduation, I worked as a modem design engineer at Witcom, an Israeli startup specializing in broadband wireless communication technology. During the same period I studied toward my M.Sc., also in electrical engineering. In 1999 I joined the Department of Electrical and Computer Engineering  and the Coordinated Science Laboratory  at the University of Illinois at Urbana-Champaign, where I completed my Ph.D. in 2003. During the Spring 2003 semester, I was a visiting assistant professor at Illinois, and taught an image/video processing class. From 2003 to 2006, I was a postdoctoral research associate in the Department of Electrical and Computer Engineering at Rice University. From Janurary 2007 through July 2008 I was a quantitative analyst with Menta Capital, but have returned to academic research, and am currently completing several papers.

My research tackles problems in various application domains where vast amounts of data must be processed effectively and rapidly in order to extract useful information. I call this computational information processing. To approach these multi-disciplinary problems, I combine tools from information theory, signal processing, machine learning, and theoretical computer science. Specific problems lie in areas such as networks, signal processing, distributed sensing, communication systems, and finance. While my M.Sc. research was in networks, during my Ph.D. I focused on parallel algorithms for lossless data compression (click here for a brief description). The highlight of my postdoctoral work was compressed sensing (CS), an emerging field that provides revolutionary new ways to process sparse signals using limited resources. More specifically, I worked on distributed multi-sensor CS and information theoretic performance bounds on compressed sensing performance. My work at Menta Capital employed ideas from these areas to develop novel investment algorithms.

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