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个人简介
Dr. Shang-Hua Teng has twice won the prestigious Gödel Prize in theoretical computer science, first in 2008, for developing the theory of smoothed analysis, and then in 2015, for designing the groundbreaking nearly-linear time Laplacian solver for network systems. Both are joint work with Dan Spielman of Yale --- his long-time collaborator. Smoothed analysis is fundamental for modeling and analyzing practical algorithms, and the Laplacian paradigm has since led to several breakthroughs in network analysis, matrix computation, and optimization. Citing him as, ``one of the most original theoretical computer scientists in the world'', the Simons Foundation named Teng a 2014 Simons Investigator, for pursuing long-term curiosity-driven fundamental research.
研究兴趣
论文共 274 篇作者统计合作学者相似作者
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arXiv (Cornell University) (2024)
Annual Conference Computational Learning Theorypp.5301-5305, (2024)
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Theoretical computer science (2024): 114636-114636
ACM Transactions on Intelligent Systems and Technologyno. 6 (2023): 1-39
Communications of the ACMno. 12 (2023): 84-84
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作者统计
#Papers: 274
#Citation: 15157
H-Index: 57
G-Index: 117
Sociability: 6
Diversity: 1
Activity: 1
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