World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
28086
World Ranking
3326
National Ranking
1614

Mark Steyvers 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 Mark Steyvers 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: 168 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Mark Steyvers 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 Mark Steyvers 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Overview

Mark Steyvers is a researcher primarily affiliated with the University of California, Irvine in the United States. Their work focuses on computer science, with a particular emphasis on artificial intelligence and related subfields. Steyvers has contributed significantly to topics such as explainable artificial intelligence (XAI), topic modeling, anomaly detection techniques, ethics and social impacts of AI, and machine learning methodologies.

The researcher's recent publications include:

  • Bayesian modeling of human-AI complementarity, 2022, Proceedings of the National Academy of Sciences
  • Three Challenges for AI-Assisted Decision-Making, 2023, Perspectives on Psychological Science
  • A Critical Review of Network-Based and Distributional Approaches to Semantic Memory Structure and Processes, 2021, Topics in Cognitive Science
  • What large language models know and what people think they know, 2025, Nature Machine Intelligence
  • AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies, 2022, Computational Brain & Behavior

Steyvers frequently publishes in venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Psychological Review
  • Proceedings of the National Academy of Sciences
  • Perspectives on Psychological Science

Their collaborative network includes multiple frequent co-authors, notably:

  • Padhraic Smyth
  • Aakriti Kumar
  • Heliodoro Tejeda
  • Disi Ji
  • Guy E. Hawkins

Steyvers' research spans these subfields within computer science:

  • Artificial Intelligence
  • Cognitive Neuroscience
  • Safety Research
  • Sociology and Political Science
  • Management Science and Operations Research

Their work covers main topics such as:

  • Explainable Artificial Intelligence (XAI)
  • Topic Modeling
  • Anomaly Detection Techniques and Applications
  • Ethics and Social Impacts of AI
  • Machine Learning and Data Classification
  • Intelligent Tutoring Systems and Adaptive Learning
  • Machine Learning and Algorithms

Best Publications

  • Finding scientific topics

    Thomas L. Griffiths;Mark Steyvers

  • Probabilistic Topic Models

    Mark Steyvers;Tom Griffiths

  • The large-scale structure of semantic networks: statistical analyses and a model of semantic growth.

    Mark Steyvers;Joshua B. Tenenbaum

  • The author-topic model for authors and documents

    Michal Rosen-Zvi;Thomas Griffiths;Mark Steyvers;Padhraic Smyth

  • Topics in semantic representation.

    Thomas L. Griffiths;Mark Steyvers;Joshua B. Tenenbaum

  • A model for recognition memory: REM—retrieving effectively from memory

    Richard M. Shiffrin;Mark Steyvers

  • Probabilistic author-topic models for information discovery

    Mark Steyvers;Padhraic Smyth;Michal Rosen-Zvi;Thomas Griffiths

  • Integrating Topics and Syntax

    Thomas L. Griffiths;Mark Steyvers;David M. Blei;Joshua B. Tenenbaum

  • Inferring causal networks from observations and interventions

    Mark Steyvers;Joshua B. Tenenbaum;Eric-Jan Wagenmakers;Ben Blum

  • Statistical topic models for multi-label document classification

    Timothy N. Rubin;America Chambers;Padhraic Smyth;Mark Steyvers

  • Learning author-topic models from text corpora

    Michal Rosen-Zvi;Chaitanya Chemudugunta;Thomas Griffiths;Padhraic Smyth

  • A probabilistic approach to semantic representation

    Thomas L Griffiths;Mark Steyvers

  • A method for efficiently sampling from distributions with correlated dimensions

    Brandon M. Turner;Per B. Sederberg;Scott D. Brown;Mark Steyvers

  • The sensitization and differentiation of dimensions during category learning.

    Robert L. Goldstone;Mark Steyvers

  • Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model

    Chaitanya Chemudugunta;Padhraic Smyth;Mark Steyvers

  • A Bayesian analysis of human decision-making on bandit problems

    Mark Steyvers;Michael D. Lee;Eric-Jan Wagenmakers

  • Word Association Spaces for Predicting Semantic Similarity Effects in Episodic Memory.

    Mark Steyvers;Richard M. Shiffrin;Douglas L. Nelson

  • A Bayesian framework for simultaneously modeling neural and behavioral data

    Brandon M. Turner;Birte U. Forstmann;Eric-Jan Wagenmakers;Scott D. Brown

  • Google and the Mind Predicting Fluency With PageRank

    Thomas L. Griffiths;Mark Steyvers;Alana Firl

  • A Bayesian account of reconstructive memory.

    Pernille Hemmer;Mark Steyvers

  • The Large-Scale Structure of Semantic Networks

    M. Steyvers;J. Tenenbaum

Frequent Co-Authors

Padhraic Smyth
Padhraic Smyth University of California, Irvine
Thomas L. Griffiths
Thomas L. Griffiths Princeton University
Scott D. Brown
Scott D. Brown University of Newcastle Australia
Eric-Jan Wagenmakers
Eric-Jan Wagenmakers University of Amsterdam
David C. Atkins
David C. Atkins University of Washington
Zhong-Lin Lu
Zhong-Lin Lu New York University Shanghai
Richard M. Shiffrin
Richard M. Shiffrin Indiana University
Robert L. Goldstone
Robert L. Goldstone Indiana University
Jeroen G. W. Raaijmakers
Jeroen G. W. Raaijmakers University of Amsterdam

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