Shang-Hua Teng

Seeley G. Mudd Professor of Computer Science and Mathematics
USC Theory Group
Computer Science Department
Viterbi School of Engineering
University of Southern California

RTH 402, 941 Bloom Walk Los Angeles, CA 90089
Affiliated Research Professor of Mathematics at MIT

Ph.D. in Computer Science, Carnegie Mellon University
M.S. in Computer Science, USC
B.S. in Computer Science & B.A. in Electrical Engineering, Shanghai Jiao Tong University

RESEARCH INTERESTS: network analysis, spectral graph theory, smoothed analysis of algorithms, computational economics and game theory, mathematical board games, scientific computing, mathematical programming, combinatorial optimization, computational geometry and computer graphics.

I am currently teaching:

SHORT BIO   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. He and his collaborators also received the best paper award at ACM Symposium on Theory of Computing (STOC) for what's considered to be the ``first improvement in 10 years'' of a fundamental optimization problem --- the computation of maximum flows and minimum cuts in a network. In addition, he is known for his joint work with Xi Chen and Xiaotie Deng that characterized the complexity for computing an approximate Nash equilibrium in game theory, and his joint papers on market equilibria in computational economics. He and his collaborators also pioneered the development of well-shaped Dalaunay meshing algorithms for arbitrary three-dimensional geometric domains, which settled a long-term open problem in numerical simulation, also a fundamental problem in computer graphics. Software based on this development was used at the University of Illinois for the simulation of advanced rockets. Teng is also interested in mathematical board games. With his former Ph.D. student Kyle Burke, he designed and analyzed a game called Atropos , which is played on the Sperner's triangle and based on the beautiful, celebrated Sperner's Lemma. In 2000 at UIUC, Teng was named on the List of Teachers Ranked as Excellent by Their Students for his class, ``Network Security and Cryptography''. He has worked and consulted for Microsoft Research, Akamai, IBM Almaden Research Center, Intel Corporation, Xerox PARC, and NASA Ames Research Center, for which he received fifteen patents for his work on compiler optimization, Internet technology, and social network.


Click here , for full career narrative.

SELECTED PUBLICATIONS:   Electrial flows, Laplacian systems, and faster approximation of maximum flow in undirected graphs, in STOC 2011: 273-282 (with Paul Christiano, Jon Kelner, Aleksander Madry, and Daniel Spielman).

Nearly-Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems, Journal on Matrix Analysis (2014) 35 (3) (with Dan Spielman)

Spectral Sparsification of Graphs, in SIAM J. Computing, 40(4): 981-1025, 2011 (with Daniel Spielman).

A Local Clustering Algorithm for Massive Graphs and Its Application to Nearly Linear Time Graph Partitioning, SIAM J. Comput. 42(1): 1-26 (2013) (with Dan Spielman)

Settling the complexity of computing two-player Nash equilibria, in J. ACM, 56(3) May 2009 (with Xi Chen and Xiaotie Deng).

Smoothed analysis of algorithms: the simplex algorithm usually takes polynomial number of steps, in J. ACM, 51(3) pages 385-463, May 2004 (with Daniel Spielman).

Separators for sphere-packings and nearest neighborhood graphs, in J. ACM, 44(1), 1-29, January 1997 (with Gary Miller, William Thurston, and Steve Vavasis).

Sliver Exudation, in J. ACM, 47(5): 883-904, 2000 (with S.-W. Cheng, T. Dey, H. Edelsbrunner, and M. Facello).

Spectral partitioning works: planar graphs and finite element meshes, in Linear Algebria and Its Applications, vol 421, 284-305, March 2007 (with Daniel Spielman).

Subspace gradient domain mesh deformation, in ACM Transactions on Graphics: SIGGRAPH'06, 1126-1134, 2006 (with Jin Huang, Xiaohan Shi, Xinguo Liu, Kun Zhou, Li-Yi Wei, Hujun Bao, Baining Guo, Harry Shum).

Atropos: A PSPACE-complete Sperner Triangle Game, in Internet Mathematics, 5(4): 477-492, 2008 (with Kyle Burke).

Learning and smoothed analysis, in FOCS 2009, 395-404 (with Adam Kalai and Alex Samorodnitsky).

Settling the complexity of Arrow-Debreu equilibria in markets with additively separable utilities, in FOCS 2009, 273-282 (with Xi Chen, Decheng Dai, and Ye Du).

Smoothed analysis of multiobjective optimization, in FOCS 2009, 681-690 (with Heiko Roglin).

Higher eigenvalues of graphs, in FOCS 2009, 735-744 (with Jon Kelner, James Lee, and Greg Price).

Reducibility among fractional stability problems, in FOCS 2009, 283-292 (with Shiva Kintali, Laura Poplawski, Rajmohan Rajaraman, and Ravi Sundaram).

Finding local communities in protein networks, in BMC Bioinformatics, 10:297, 2009 (with Konstantin Voevodski and Yu Xia).

k-nearst neighbor clustering and percolation theory, in Algorithmica, 49(3):192-211, 2007 (with Frances Yao).

Security, verifiability, and universality in distributed computing, in J. Algorithms 11(3):492-521, 1990 (with Ming-Deh Huang).

Functional inversion and communication complexity, in Journal Cryptology, 7(3):153-170, 1994.

Provably good partitioning and load balancing algorithms for parallel adaptive N-Body simulation, in SIAM J, Scientific Computing, 19:635-654, 1998.


INDUSTRY/INVENTION:   Software: mesh partitioning (Xerox/MathWorks), transistor-level circuit simulation (Intel), web crawling (IBM), massive data analysis (Akamai)

Patents: fifteen patents for his work on compiler optimization, Internet technology, and social network analysis.


PERSONAL:   YOUTHFUL CHILD-FREE LIFE: I love Latin music and Latin dance, especially Salsa Dancing. I also like cooking, reading, and traveling, and enjoy solving math problems on the airplane.

SINCE 2012: I love to understand learning and language acquisition. I also like cooking and playing various games with my daughter, and enjoy watching her to figure out the world.

CONTACT:   shanghua AT usc DOT edu

TEACHING:   CSCI 670: Advanced Analysis of Algorithms (Fall 2013)  
    CSCI 499: Cryptography - Fundamentals of Secure Communication & Computation (Fall 2013)  
    CSCI 670: Advanced Analysis of Algorithms (Spring 2012)  
    CSCI 599: Algorithms for the New Age: Games, Economics, Networking, & Data Analysis (Fall 2010)  
    CSCI 303: Analysis of Algorithms (Spring 2010)  
RECENT TALKS:   Algorithmic Primitives for Network Analysis: Through the Lens of the Laplacian Paradigm SIAM Data Mining Conference, 2012  

CV, Research Statements, Teaching Statements, Career Narrative, Biographical Sketch