- IIT-Bombay, B. Tech, Computer Science and Engineering, 1999
- Stanford, PhD, Computer Science, 2004
Devavrat Shah completed his PhD at Stanford University in October 2004. His thesis focused on the development of novel design and analytic methods for network algorithms.
Before coming to LIDS in the fall of 2005, he spent a year at the Mathematical Sciences Research Institute (MSRI) in Berkeley, California. During this year of study, he was introduced to message-passing algorithms and graphical statistical inference. At LIDS, his research areas include statistical inference, network algorithms, and stochastics.
Books and Book Chapters:
- D. Shah, “Network scheduling and message-passing,” Performance Modeling and Engineering, Z. Liu and C. Xia, eds., a collection of tutorials from ACM Sigmetrics/Performance, 2008.
- D. Shah and D. Wischik, “Heavy Traffic Analysis of Optimal Scheduling Algorithm for Switched Networks,” [undergoing revision].
- D. Mosk Aoyama and D. Shah, “Fast Gossip Algorithms for Computing Separable Functions,” IEEE Transactions on Information Theory, 54(7), 2008.
- M. Bayati, D. Shah, and M. Sharma, “Max-product for Maximum Weight Matching: Correctness, Convergence and LP Duality,” IEEE Transactions on Information Theory, 54(3), 2008.
- S. Boyd, A. Ghosh, B. Prabhakar, and D. Shah, "Randomized Gossip Algorithms," IEEE Transactions on Information Theory, 52(6), 2006.
- A. El Gamal, J. Mammen, B. Prabhakar, and D. Shah, “Optimal Throughput-Delay Tradeoff in Wireless Networks – Part I: The Fluid Model,” IEEE Transactions on Information Theory, 52(6), 2006.
- S. Rajagopalan, J. Shin, and D. Shah, “Network Adiabetic Theorem: An Efficient Randomized Protocol for Contention Resolution,” ACM Sigmetrics/Performance, 2009.
- U. Niesen, P. Gupta, and D. Shah, “The Multicast Capacity Region of Large Wireless Networks,” IEEE Infocom, 2009.
- J. Salez and D. Shah, “Belief Propagation: Optimal Algorithm For Random Assignment Problem,” SIAM SODA, 2009.
- S. Jagabathula and D. Shah, “Inferring Popular Rankings Under Constrained Sensing,” Neural Information Processing Systems, 2008 (Best Student Paper Award).
- K. Jung, Y. Lu, D. Shah, M. Sharma, and M. Squillante, “Revisiting Stochastic Loss Networks: Structures and Algorithms,” ACM Sigmetrics/Performance, 2008.
ACM SIGMETRICS/Performance best student paper award 2009 (supervised)
Neural Information Processing System (NIPS) outstanding paper award 2008 (supervised)
ACM SIGMETRICS/Performance best paper award 2006
NSF CAREER Award 2006
George B. Dantzig best dissertation award from INFORMS 2005
IEEE INFOCOM best paper award 2004
President of India Gold Medal at Indian Institute of Technology-Bombay 1999
Spring 2008 Advanced Stochastic Processes (6.975/15.070)
Fall 2011 Algorithms for Inference (6.438)