Shang-Hua Teng

Shang-Hua Teng is a University Professor and Seeley G. Mudd Professor of Computer Science and Mathematics at the University of Southern California (USC), affiliated with the Viterbi School of Engineering. He leads the USC Theory Group and the Machine Learning Center. His research spans scalable algorithms, network analysis, spectral graph theory, smoothed analysis, computational economics, and mathematical board games. He holds dual B.S. and B.A. degrees from Shanghai Jiao Tong University, an M.S. from USC, and a Ph.D. from Carnegie Mellon University.

• Affiliations: USC Theory Group, USC Machine Learning Center, MIT (Affiliated Research Professor in Mathematics).
• Education: Ph.D. Carnegie Mellon University (1991), M.S. USC (1988), B.S./B.A. Shanghai Jiao Tong University (1985).

Research Interests: Focuses on foundational algorithmic problems with applications in networks, economics, and geometry. Notable contributions include smoothed analysis of algorithms, Laplacian solvers, and game theory. His work has been recognized with two Gödel Prizes, the Simons Investigator Award, and ACM Fellow status.

Awards: SIAM Fellow (2021), Gödel Prize (2008, 2015), Simons Investigator (2014), ACM Fellow (2009).

Teaching: Teaches advanced courses on algorithms, cryptography, and network analysis. Recent courses include CSCI 476 (Cryptography) and CSCI 670 (Advanced Algorithms).