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Neil Burch 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 Neil Burch 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+

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

Neil Burch 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 Neil Burch 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+

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

Overview

Neil Burch is affiliated with the University of Alberta in Canada and conducts research primarily in the field of Computer Science, with a strong focus on Artificial Intelligence. Their work spans several subfields including Management Science and Operations Research, Economics and Econometrics, Developmental and Educational Psychology, and Computer Vision and Pattern Recognition.

Their research topics include:

  • Reinforcement Learning in Robotics
  • Artificial Intelligence in Games
  • Game Theory and Applications
  • Sports Analytics and Performance
  • Adversarial Robustness in Machine Learning
  • Advanced Bandit Algorithms Research
  • Explainable Artificial Intelligence (XAI)

Neil Burch's recent publications highlight their involvement in multiagent decision making and game theory. Notable papers include:

  • "Mastering the game of Stratego with model-free multiagent reinforcement learning," 2022, Science
  • "Finding Optimal Abstract Strategies in Extensive-Form Games," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Rethinking formal models of partially observable multiagent decision making," 2021, Artificial Intelligence
  • "From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization," 2020, arXiv (Cornell University)
  • "Generalized Sampling and Variance in Counterfactual Regret Minimization," 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent co-authors in Neil Burch's research include:

  • Marc Lanctot
  • Finbarr Timbers
  • Michael Bowling
  • Edward Lockhart
  • Julien Pérolat

Neil Burch regularly publishes in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the International Symposium on Combinatorial Search
  • Zenodo (CERN European Organization for Nuclear Research)
  • Science

Best Publications

  • DeepStack: Expert-level artificial intelligence in heads-up no-limit poker

    Matej Moravčík;Matej Moravčík;Martin Schmid;Martin Schmid;Neil Burch;Viliam Lisý;Viliam Lisý

  • Checkers Is Solved

    Jonathan Schaeffer;Neil Burch;Yngvi Björnsson;Akihiro Kishimoto

  • Heads-up limit hold'em poker is solved

    Michael Bowling;Neil Burch;Michael Johanson;Oskari Tammelin

  • Approximating game-theoretic optimal strategies for full-scale poker

    D. Billings;N. Burch;A. Davidson;R. Holte

  • The Hanabi Challenge: A New Frontier for AI Research

    Nolan Bard;Jakob N. Foerster;Sarath Chandar;Neil Burch

  • Bayes' bluff: opponent modelling in poker

    Finnegan Southey;Michael Bowling;Bryce Larson;Carmelo Piccione

  • Solving heads-up limit Texas Hold'em

    Oskari Tammelin;Neil Burch;Michael Johanson;Michael Bowling

  • Game-Tree search with adaptation in stochastic imperfect-information games

    Darse Billings;Aaron Davidson;Terence Schauenberg;Neil Burch

  • Memory-based heuristics for explicit state spaces

    Nathan R. Sturtevant;Ariel Felner;Max Barrer;Jonathan Schaeffer

  • Evaluating state-space abstractions in extensive-form games

    Michael Johanson;Neil Burch;Richard Valenzano;Michael Bowling

  • Finding optimal abstract strategies in extensive-form games

    Michael Johanson;Nolan Bard;Neil Burch;Michael Bowling

  • Solving imperfect information games using decomposition

    Neil Burch;Michael Johanson;Michael Bowling

  • Solving checkers

    J. Schaeffer;Y. Björnsson;N. Burch;A. Kishimoto

  • No-Regret Learning in Extensive-Form Games with Imperfect Recall

    Marc Lanctot;Richard Gibson;Neil Burch;Martin Zinkevich

  • Block A*: database-driven search with applications in any-angle path-planning

    Peter Yap;Neil Burch;Rob Holte;Jonathan Schaeffer

  • No-Regret Learning in Extensive-Form Games with Imperfect Recall

    Marc Lanctot;Neil Burch;Martin Zinkevich;Michael Bowling

  • Predicting the performance of IDA* using conditional distributions

    Uzi Zahavi;Ariel Felner;Neil Burch;Robert C. Holte

  • Online implicit agent modelling

    Nolan Bard;Michael Johanson;Neil Burch;Michael Bowling

  • Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning

    Jakob N. Foerster;H. Francis Song;Edward Hughes;Neil Burch

  • From Poincar'e Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

    Julien Perolat;Remi Munos;Jean-Baptiste Lespiau;Shayegan Omidshafiei

Frequent Co-Authors

Michael Bowling
Michael Bowling University of Alberta
Robert C. Holte
Robert C. Holte University of Alberta
Jonathan Schaeffer
Jonathan Schaeffer University of Alberta
Marc Lanctot
Marc Lanctot DeepMind (United Kingdom)
Duane Szafron
Duane Szafron University of Alberta
Ariel Felner
Ariel Felner Ben-Gurion University of the Negev
Jakob Foerster
Jakob Foerster University of Oxford
Shimon Whiteson
Shimon Whiteson University of Oxford
Matthew Botvinick
Matthew Botvinick Yale University
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA

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