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Christopher Rozell attended the University of Michigan, receiving a B.S.E. in Computer Engineering and a B.F.A. in Performing Arts Technology (Music Technology) in 2000. He attended graduate school at Rice University, receiving the M.S. and Ph.D. in Electrical Engineering in 2002 and 2007, respectively. Following graduate school, he joined the Redwood Center for Theoretical Neuroscience at the University of California, Berkeley as a postdoctoral research fellow in 2007. He joined the Georgia Tech faculty in July 2008, where he is affiliated with the Center for Signal and Information Processing.
Dr. Rozell's research interests focus on the intersection of computational neuroscience and signal processing. One branch of this work aims to understand how neural systems organize and process sensory information, drawing on modern engineering ideas to develop improved data analysis tools and theoretical models. The other branch of this work uses recent insight into neural information processing to develop new and efficient approaches to difficult data analysis tasks.
- Biological and computational vision
- Theoretical and computational neuroscience
- High-dimensional data analysis
- Distributed computing in novel architectures
- Applications in imaging, remote sensing, and biotechnology
- National Science Foundation (NSF) CAREER Award in 2014
- Demetrius T. Paris Junior Professorship, 2013-present
- CETL/BP Junior Faculty Teaching Excellence Award, 2013
- Texas Instruments Distinguished Graduate Fellowship, 2000-2007
- Nettie S. Autrey Memorial Fellowship (Rice University), 2004-2005
- Honor society memberships: Tau Beta Pi and Eta Kappa Nu
- Professional memberships: Senior Member of IEEE
M. Zhu and C.J. Rozell. Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system. PLoS Computational Biology, 9(8):e1003191, August 2013.
H.L. Yap, M.B. Wakin, and C.J. Rozell. Stable manifold embeddings with structured random matrices. IEEE Journal of Selected Topics in Signal Processing, 7(4):720{730, August 2013.
A.A. Kressner, D.V. Anderson, and C.J. Rozell. Evaluating the generalization of the hearing aid speech quality index (HASQI). IEEE Transactions on Audio, Speech and Language Processing, 21:407-415, February 2013.
A.S. Charles and C.J. Rozell. Spectral super-resolution of hyperspectral imagery using re-weighted l1 spatial filtering. IEEE Geoscience and Remote Sensing Letters, 2013.
A.S. Charles, P. Garrigues, and C.J. Rozell. A common network architecture efficiently implements a variety of sparsity-based inference problems. Neural Computation, 24(12):3317-3339, December 2012.
A.S. Charles, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral imagery. IEEE Journal of Selected Topics in Signal Processing, 5(5):963{978, September 2011.
C.J. Rozell, D.H Johnson, R.G. Baraniuk, and B.A. Olshausen. Sparse coding via thresholding and local competition in neural circuits. Neural Computation, 20(10):2526-2563, October 2008.
S.W. Bishnoi, C.J. Rozell, C.S. Levin, M.K. Gheith, B.R. Johnson, D.H. Johnson, and N.J Halas. All-optical nanoscale pH meter. Nano Letters, 6(8):1687-1692, August 2006
C.J. Rozell, D.H. Johnson, and R.M. Glantz. Measuring information transfer in crayfish sustaining fiber spike generators. Biological Cybernetics, 90(2):89-97, February 2004.
Last revised May 17, 2022
Georgia Institute of Technology
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