World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
18635
World Ranking
2188
National Ranking
1098

Research.com Recognitions

  • 2009 - ACM Fellow For contributions to theoretical computer science, algorithms and interdisciplinary applications of computing.
  • 1996 - Fellow of Alfred P. Sloan Foundation

Overview

Shang-Hua Teng is affiliated with the University of Southern California in the United States. Their research primarily spans the field of Computer Science with a focus on several subfields including Artificial Intelligence, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Management Science and Operations Research, and Modeling and Simulation.

Their work covers a variety of main research topics such as Complex Network Analysis Techniques, Opinion Dynamics and Social Influence, Computability, Logic, AI Algorithms, Game Theory and Applications, Artificial Intelligence in Games, COVID-19 epidemiological studies, and Quantum Mechanics and Applications.

Frequent co-authors collaborating with Shang-Hua Teng include Kyle Burke, Matthew Ferland, Julian Asilis, Siddartha Devic, and Shaddin Dughmi.

The scientist has published extensively in a range of venues, notably:

  • arXiv (Cornell University)
  • Theoretical Computer Science
  • Journal of Complex Networks
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • ACM Transactions on Intelligent Systems and Technology

Selected recent papers by Shang-Hua Teng include:

  • "Non-conservative diffusion and its application to social network analysis" (2023), Journal of Complex Networks
  • "A graph-theoretical basis of stochastic-cascading network influence: Characterizations of influence-based centrality" (2020), Theoretical Computer Science
  • "Quantum-Inspired Combinatorial Games: Algorithms and Complexity" (2022), Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "Intelligent Heuristics Are the Future of Computing" (2023), ACM Transactions on Intelligent Systems and Technology
  • "On the Equivalence Between High-Order Network-Influence Frameworks: General-Threshold, Hypergraph-Triggering, and Logic-Triggering Models" (2020), arXiv (Cornell University)

Awards conferred to Shang-Hua Teng include election as an ACM Fellow in 2009 for contributions to theoretical computer science, algorithms, and interdisciplinary applications of computing, and being named a Fellow of the Alfred P. Sloan Foundation in 1996.

Best Publications

  • Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time

    Daniel A. Spielman;Shang-Hua Teng

  • Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems

    Daniel A. Spielman;Shang-Hua Teng

  • Metadata search results ranking system

    Stefan B. Edlund;Michael L. Emens;Reiner Kraft;Jussi Myllymaki

  • Settling the complexity of computing two-player Nash equilibria

    Xi Chen;Xiaotie Deng;Shang-Hua Teng

  • Spectral partitioning works: planar graphs and finite element meshes

    D.A. Spielmat;Shang-Hua Teng

  • Spectral Sparsification of Graphs

    Daniel A. Spielman;Shang-Hua Teng

  • On trip planning queries in spatial databases

    Feifei Li;Dihan Cheng;Marios Hadjieleftheriou;George Kollios

  • Nearly Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems

    Daniel A. Spielman;Shang-Hua Teng

  • Silver exudation

    Siu-Wing Cheng;Tamal K. Dey;Herbert Edelsbrunner;Michael A. Facello

  • Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs

    Paul Christiano;Jonathan A. Kelner;Aleksander Madry;Daniel A. Spielman

  • A LOCAL CLUSTERING ALGORITHM FOR MASSIVE GRAPHS AND ITS APPLICATION TO NEARLY LINEAR TIME GRAPH PARTITIONING

    Daniel A. Spielman;Shang-Hua Teng

  • Subspace gradient domain mesh deformation

    Jin Huang;Xiaohan Shi;Xinguo Liu;Kun Zhou

  • Smoothed Analysis of the Condition Numbers and Growth Factors of Matrices

    Arvind Sankar;Daniel A. Spielman;Shang-Hua Teng

  • How Good is Recursive Bisection

    Horst D. Simon;Shang-Hua Teng

  • Separators for sphere-packings and nearest neighbor graphs

    Gary L. Miller;Shang-Hua Teng;William Thurston;Stephen A. Vavasis

  • Geometric Mesh Partitioning: Implementation and Experiments

    John R. Gilbert;Gary L. Miller;Shang-Hua Teng

  • Spectral partitioning works : Planar graphs and finite element meshes

    Daniel A. Spielman;Shang-Hua Teng

  • Generating local addresses and communication sets for data-parallel programs

    Siddhartha Chatterjee;John R. Gilbert;Fred J. E. Long;Robert Schreiber

  • Generating Local Addresses and Communication Sets for Data-Parallel Programs

    Siddhartha Chatterjee;John R. Gilbert;Fred J. E. Long;Robert Schreiber

  • Lower-Stretch Spanning Trees

    Michael Elkin;Yuval Emek;Daniel A. Spielman;Shang-Hua Teng

  • Smoothed analysis: an attempt to explain the behavior of algorithms in practice

    Daniel A. Spielman;Shang-Hua Teng

Frequent Co-Authors

Daniel A. Spielman
Daniel A. Spielman Yale University
Gary L. Miller
Gary L. Miller Carnegie Mellon University
Xi Chen
Xi Chen Columbia University
Christian Borgs
Christian Borgs University of California, Berkeley
Jennifer Chayes
Jennifer Chayes University of California, Berkeley
Maria-Florina Balcan
Maria-Florina Balcan Carnegie Mellon University
Xiang-Yang Li
Xiang-Yang Li University of Science and Technology of China
Ravi Sundaram
Ravi Sundaram Northeastern University
Rajmohan Rajaraman
Rajmohan Rajaraman Northeastern University
John R. Gilbert
John R. Gilbert University of California, Santa Barbara

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