Venkat Chandrasekaran

32-D570
77 Massachusetts Avenue
Cambridge, MA 02139

Email: alpha@beta.edu (alpha = venkatc; beta = mit)

Brief biography

I earned a B.A. in Mathematics and a B.S. in Electrical and Computer Engineering in May 2005 at Rice University in Houston, Texas. I am currently a graduate student in the Department of Electrical Engineering and Computer Science at MIT, where I work with Professor Alan Willsky as a member of the Stochastic Systems Group in the Laboratory for Information and Decision Systems.

Research interests

My current research interests lie in the areas of statistical signal processing and machine learning within the framework of graphical models. I have also done some work in the past in the field of computational harmonic analysis, with a focus on developing new sparse representations for certain classes of signals.

Publications

Journal papers

V. Chandrasekaran, M. B. Wakin, D. Baron, and R. G. Baraniuk, Representation and Compression of Multi-Dimensional Piecewise Functions Using Surflets, IEEE Transactions on Information Theory, accepted.

M. J. Choi, V. Chandrasekaran, D. M. Malioutov, J. K. Johnson, and A. S. Willsky, Multiscale Stochastic Modeling for Tractable Inference and Data Assimilation, Computer Methods in Applied Mechanics and Engineering, accepted.

V. Chandrasekaran, J. K. Johnson, and A. S. Willsky, Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis, IEEE Transactions on Signal Processing, Vol. 56, No. 5, May 2008.

Conference papers

V. Chandrasekaran, N. Srebro, and P. Harsha, Complexity of Inference in Graphical Models, 24th Conference on Uncertainty in Artificial Intelligence and Statistics (UAI 2008), Helsinki, Finland, July 2008.

V. Chandrasekaran, J. K. Johnson, and A. S. Willsky, Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis, Neural Information Processing Systems (NIPS 2007), Vancouver, Canada, December 2007.

V. Chandrasekaran, J. K. Johnson, and A. S. Willsky, Maximum Entropy Relaxation for Graphical Model Selection given Inconsistent Statistics, IEEE 2007 Statistical Signal Processing Workshop (SSP 2007), Madison, Wisconsin, August 2007.

J. K. Johnson, V. Chandrasekaran, and A. S. Willsky, Learning Markov Structure by Maximum Entropy Relaxation, 11th International Conference in Artificial Intelligence and Statistics (AISTATS 2007), San Juan, Puerto Rico, March 2007.

V. Chandrasekaran, M. B. Wakin, D. Baron, and R. G. Baraniuk, Surflets: A Sparse Representation for Multidimensional Functions Containing Smooth Discontinuities, IEEE 2004 International Symposium on Information Theory (ISIT 2004), Chicago, Illinois, June 2004.

V. Chandrasekaran, M. B. Wakin, D. Baron, and R. G. Baraniuk, Compression of Higher Dimensional Functions Containing Smooth Discontinuities, 38th Annual Conference on Information Sciences and Systems (CISS 2004), Princeton, New Jersey, March 2004. (See supplemental tech report)

Theses

V. Chandrasekaran, Modeling and Estimation in Gaussian Graphical Models: Maximum-Entropy Relaxation and Walk-Sum Analysis, S.M. thesis, Massachusetts Institute of Technology, June 2007.

Technical reports

V. Chandrasekaran, M. B. Wakin, D. Baron, and R. Baraniuk, Compressing Piecewise Smooth Multidimensional Functions Using Surflets: Rate-Distortion Analysis, Rice University ECE Technical Report, Houston, Texas, March 2004. (supplement to CISS 2004 paper)

Last updated: May 2008