Shang-Hua Teng
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Shang-Hua Teng

Shang-Hua Teng (Chinese: ; pinyin: Téng Shàng-huá, born 1964)[2] is a Chinese-American computer scientist. He is the Seeley G. Mudd Professor of Computer Science and Mathematics at the University of Southern California. Previously, he was the chairman of the Computer Science Department at the Viterbi School of Engineering of the University of Southern California.[3] In 2008 he was awarded the Gödel Prize for his joint work on smoothed analysis of algorithms with Daniel Spielman. They went to win the prize again in 2015 for their contribution on "nearly-linear-time Laplacian solvers".[4][5] In 2009, he received the Fulkerson Prize given by the American Mathematical Society and the Mathematical Programming Society.


Teng graduated with BA in electrical engineering and BS in computer science, both from Shanghai Jiao Tong University in 1985. He obtained MS in computer science from the University of Southern California in 1988. Teng holds a Ph.D in computer science from Carnegie Mellon University (in 1991).

Prior to joining USC in 2009, Teng was a professor at Boston University. He has also taught at MIT, the University of Minnesota, and the University of Illinois at Urbana-Champaign. He has worked at Xerox PARC, NASA Ames Research Center, Intel Corporation, IBM Almaden Research Center, Akamai Technologies, Microsoft Research Redmond, Microsoft Research New England and Microsoft Research Asia.

Teng is a Fellow of the Association for Computing Machinery (ACM)[6] as well as an Alfred P. Sloan Research Fellow.


  1. ^ Parberry, Ian (1999-05-10). "2008 Gödel Prize". ACM SIGACT. Archived from the original on March 28, 2009. Retrieved .
  2. ^ "Diana Williams, Shanghua Teng". The New York Times. July 27, 2003. Retrieved 2011.
  3. ^ Calverley, Bob (July 15, 2009). "Computer Scientist Teng to Join USC". USC News. Archived from the original on July 23, 2009..
  4. ^ "ACM SIGACT: Prizes: Gödel" (PDF). ACM SIGACT. Retrieved .
  5. ^
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External links

  This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.



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