Fall 2007 Seminar Series

Shang-Hua Teng is now a full professor in the Computer Science Department at Boston University and also a senior research scientist at Akamai Technologies Inc. He taught as a faculty in the Department of Mathematics of MIT and in the Computer Science Departments of the University of Minnesota and UIUC. He has worked and consulted for IBM Almaden Research Center, Intel Corporation, Xerox PARC, Cray Research/SGI, Thinking Machine Corporation, and NASA Ames Research Center. He is an Alfred P. Sloan Fellow, winner of Senior Xerox Award for Outstanding Faculty Research (UIUC), and has received NSF Faculty Early Career Development Award. Teng received a B.S. degree in computer science and a B.A. degree in electrical engineering from Shanghai Jiao Tong University in 1985, a M.S. degree in computer science from University of Southern California (USC) in 1988, and a Ph.D. degree in computer science from Carnegie Mellon University (CMU) in 1991. With Dan Spielman of MIT, he developed the theory of Smoothed Analysis for modeling and analyzing practical algorithms, and had demonstrated that the simplex method for linear programming has a polynomial smoothed complexity. This joint work was cited by National Science Foundation in its FY'03 budget request to Congress. His research centers on the design and analysis of efficient algorithms. His recent interests include computational game theory, spectral graph theory and its applications in optimization and information processing, parallel scientific computing, computational geometry, graph partitioning and clustering, and cryptography. He has also received 8 US Patents for his work on compiler optimization and Internet technology.