World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
75
Citations
24897
World Ranking
1407
National Ranking
731

Craig Boutilier 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 Craig Boutilier 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: 271 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Craig Boutilier 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 Craig Boutilier 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: 75 D-Index — 90th percentile

90% 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

  • 2014 - Fellow of the Royal Society of Canada Academy of Science
  • 2012 - ACM Fellow For contributions to knowledge representation and computational decision making.
  • 2006 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to default reasoning, belief revision, and decision-theoretic foundations of AI.

Overview

Craig Boutilier is affiliated with Google in the United States, focusing primarily on computer science with an emphasis on artificial intelligence. Their research activity includes 70 publications in computer science, with 45 specifically in artificial intelligence, 22 in management science and operations research, and 11 related to information systems. Other subfields include computer vision and pattern recognition as well as signal processing.

Boutilier's research encompasses a range of topics centered on advanced bandit algorithms, recommender systems, topic modeling, machine learning, reinforcement learning applied to robotics, game theory, and data management algorithms. These thematic areas collectively represent their primary scholarly contributions and areas of expertise.

They have collaborated frequently with several researchers, including Yinlam Chow, Martin Mladenov, Guy Tennenholtz, Chih-Wei Hsu, and Mohammad Ghavamzadeh.

Craig Boutilier has contributed papers to prominent venues such as arXiv (Cornell University), where they have 34 publications, Proceedings of the AAAI Conference on Artificial Intelligence with 4 publications, ACM Transactions on Recommender Systems with 2 publications, as well as individual contributions to Artificial Intelligence and the Dagstuhl Research Online Publication Server.

Selected recent publications include the following:

  • "Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report" (2022, arXiv (Cornell University))
  • "Building Human Values into Recommender Systems: An Interdisciplinary Synthesis" (2023, ACM Transactions on Recommender Systems)
  • "Aligning Text-to-Image Models using Human Feedback" (2023, arXiv (Cornell University))
  • "DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models" (2023, arXiv (Cornell University))
  • "On the equivalence of optimal recommendation sets and myopically optimal query sets" (2020, Artificial Intelligence)

Their work has been acknowledged through various honors including Fellowship of the Royal Society of Canada awarded in 2014 by the Academy of Science, ACM Fellow in 2012 for contributions to knowledge representation and computational decision making, and Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2006 recognizing advances in default reasoning, belief revision, and decision-theoretic foundations of AI.

Best Publications

  • The dynamics of reinforcement learning in cooperative multiagent systems

    Caroline Claus;Craig Boutilier

  • Decision-theoretic planning: structural assumptions and computational leverage

    Craig Boutilier;Thomas Dean;Steve Hanks

  • CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

  • Context-specific independence in Bayesian networks

    Craig Boutilier;Nir Friedman;Moises Goldszmidt;Daphne Koller

  • Planning, Learning and Coordination in Multiagent Decision Processes

    Craig Boutilier

  • Stochastic dynamic programming with factored representations

    Craig Boutilier;Richard Dearden;Moisés Goldszmidt

  • Exploiting Structure in Policy Construction

    Craig Boutilier;Richard Dearden;Moises Goldszmidt

  • SPUDD: stochastic planning using decision diagrams

    Jesse Hoey;Robert St-Aubin;Alan Hu;Craig Boutilier

  • Sequential Optimality and Coordination in Multiagent Systems

    Craig Boutilier

  • Toward a Logic for Qualitative Decision Theory

    Craig Boutilier

  • Reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Holger H. Hoos;David Poole

  • Solving Combinatorial Auctions Using Stochastic Local Search

    Holger H. Hoos;Craig Boutilier

  • A POMDP formulation of preference elicitation problems

    Craig Boutilier

  • Conditional logics of normality: a modal approach

    Craig Boutilier

  • Symbolic dynamic programming for first-order MDPs

    Craig Boutilier;Ray Reiter;Bob Price

  • Hierarchical solution of Markov decision processes using macro-actions

    Milos Hauskrecht;Nicolas Meuleau;Leslie Pack Kaelbling;Thomas Dean

  • CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

    C. Boutilier;R. I. Brafman;C. Domshlak;H. H. Hoos

  • Computing optimal policies for partially observable decision processes using compact representations

    Craig Boutilier;David Poole

  • Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process

    Jesse Hoey;Pascal Poupart;Axel von Bertoldi;Tammy Craig

  • Decision-Theoretic, High-Level Agent Programming in the Situation Calculus

    Craig Boutilier;Raymond Reiter;Mikhail Soutchanski;Sebastian Thrun

  • Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence

    Craig Boutilier;Moisés Goldszmidt

Frequent Co-Authors

Pascal Poupart
Pascal Poupart University of Waterloo
Dale Schuurmans
Dale Schuurmans University of Alberta
Ronen I. Brafman
Ronen I. Brafman Ben-Gurion University of the Negev
Branislav Kveton
Branislav Kveton Adobe Systems (United States)
Moises Goldszmidt
Moises Goldszmidt Apple (United States)
Tuomas Sandholm
Tuomas Sandholm Carnegie Mellon University
Holger H. Hoos
Holger H. Hoos RWTH Aachen University
Csaba Szepesvári
Csaba Szepesvári University of Alberta
Jesse Hoey
Jesse Hoey University of Waterloo
David Poole
David Poole University of British Columbia

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