In Short...
I am a PhD candidate
in
Electrical Engineering
at the
University of California, Berkeley working with
Michael Gastpar. I am a member of the
Sensory Information Processing and Communication group which is a part of the
Wireless Foundations Center. In December 2007, I received my M.S. in Electrical Engineering from UC Berkeley, and in May 2005, I received my BS in
Electrical and Computer Engineering from
Cornell University. I am currently supported by an ARO MURI grant.
Publications
- G. Reeves and M. Gastpar, Sampling Bounds for Sparse Support Recovery in the Presence of Noise, Proceedings of the IEEE International Symposium on Information Theory (ISIT 2008), Toronto, Canada, July 2008.
- G. Reeves, Sparse Signal Sampling using Noisy Linear Projections, Master's Thesis, Dec 2007.
-
G. Reeves and M. Gastpar, Differences between Observation and Sampling Error in Sparse Signal Reconstruction , Proceedings of the 2007 IEEE Workshop on Statistical Signal Processing (SSP 2007), Madison, Wisconsin, August, 2007.
- T. Berger, C. Levy, and G. Reeves, Energy-Efficient Recursive Estimation by Variable Threshold Neurons, Presented at CoSyNe Workshop on Info-Neuro, Park City, UT, February, 2007.
Research Interests
I have been looking at distributed signal processing for applications in sensor networks. I am also interested in information theory and theoretical neuroscience.
