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Piyush Kumar Associate Professor

Piyush Kumar
Office: 161 LOV
Telephone: (850) 645-2355
E-Mail: piyush [ at cs dot fsu dot edu ]
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Dr. Kumar received his B.Sc. degree in Mathematics and Computing from IIT Kharagpur in 1999. He moved to New York in 2000 where he was awarded a Ph.D. in computer science from State University of New York (2004). Prior to joining FSU as an Assistant Professor in 2004, he has been a visiting scientist at MPI-Saarbruecken, Germany and has visited many computer science departments across US and Europe including Duke, MIT, Oregon, and Aarhus. Currently, Dr. Kumar is associated with ACM, SIAM and the Center of Applied Vision and Imaging Sciences at FSU.

Research

Dr. Kumar primarily conducts research on the boundary of algorithms and the ``real world". His main research interests lie in applying the rich theory of algorithms to the domains of computational geometry, computer graphics, pattern recognition, and machine learning. The general theme that threads his research interests in algorithms is narrowing the gap between theory and practice. Theoretical computer science relies on making assumptions that do not generally hold in the real world. For instance, the performance of algorithms on real data vs worst case analysis, the assumption that all memory operations are unit cost, noise in the input, degeneracies, importance of exact solution to optimization problems are issues that seem to need attention but are mostly ignored by the theory community. Addressing some of these issues has been the focus of his research. His work on core sets illustrates why column generation methods perform well in optimization, both theoretically and experimentally. His work on surface and curve reconstruction gave very simple algorithms that were provably fast and could handle noise in the data. His research on cache oblivious algorithms showed why certain ways to analyze algorithms compared to the RAM model of analysis were better for practical purposes. He also worked on the design of a classifier for biometric and other applications. This classifier has also been used for palm identification using outlines of the human hand. The classifier was based upon ideas that came out from his research in optimization.

Selected Publications

  • Approximate Minimum Volume Enclosing Ellipsoids Using Core Sets. (with Alper Yildirim), To appear in the Journal of Optimization Theory and Applications, Vol. 126,No. 1, July 2005.
  • Fast smallest enclosing hypersphere computation. (with J.S.B. Mitchell and A. Yildirim) Journal of Experimental Algorithmics, Vol 8, 2003.
  • Cache oblivious algorithms. Book Chapter in Algorithms for Memory Hierarchies. LNCS 2625, Pages: 193 - 212, SpringerVerlag, 2003.
  • A simple provable algorithm for curve reconstruction. (with T.K. Dey) ACM-SIAM Symposium on Discrete Algorithms, Pages: 893 - 894, 1999.