World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
18635
World Ranking
2188
National Ranking
1099

Shang-Hua Teng publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Shang-Hua Teng sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 242 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Shang-Hua Teng D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Shang-Hua Teng sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 67 D-Index — 85th percentile

85% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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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