World's Best Scientists 2026 revealed!
Leslie Pack Kaelbling

Leslie Pack Kaelbling

D-Index & Metrics

Computer Science

D-Index
74
Citations
40111
World Ranking
1448
National Ranking
754

Leslie Pack Kaelbling 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 Leslie Pack Kaelbling 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: 370 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Leslie Pack Kaelbling 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 Leslie Pack Kaelbling 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: 74 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

  • 2000 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For seminal contributions to situated agents, machine learning, planning and mobile robotics.

Overview

Leslie Pack Kaelbling is affiliated with the Massachusetts Institute of Technology (MIT) in the United States. Their research primarily spans the domain of computer science, with a particular concentration in artificial intelligence and its various subfields.

The main fields of study for Leslie Pack Kaelbling include:

  • Computer Science

Within computer science, the subfields of study are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Computer Networks and Communications
  • Aerospace Engineering

Their research topics cover a range of specialized areas, including:

  • AI-based Problem Solving and Planning
  • Reinforcement Learning in Robotics
  • Robotic Path Planning Algorithms
  • Machine Learning and Algorithms
  • Robot Manipulation and Learning
  • Topic Modeling
  • Multimodal Machine Learning Applications

Leslie Pack Kaelbling has contributed to numerous publications across several respected venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the International Conference on Automated Planning and Scheduling
  • The International Journal of Robotics Research
  • 2022 International Conference on Robotics and Automation (ICRA)

Selected recent publications are as follows:

  • PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning, 2020, Proceedings of the International Conference on Automated Planning and Scheduling
  • Learning compositional models of robot skills for task and motion planning, 2021, The International Journal of Robotics Research
  • Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Generalized Planning in PDDL Domains with Pretrained Large Language Models, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • The foundation of efficient robot learning, 2020, Science

Frequent co-authors collaborating with Leslie Pack Kaelbling include:

  • Tomás Lozano-Pérez
  • Tom Silver
  • Joshua B. Tenenbaum
  • Rohan Chitnis
  • Aidan Curtis

Leslie Pack Kaelbling has been recognized as a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) since 2000 for contributions in situated agents, machine learning, planning, and mobile robotics.

Best Publications

  • Reinforcement learning: a survey

    Leslie Pack Kaelbling;Michael L. Littman;Andrew W. Moore

  • Planning and Acting in Partially Observable Stochastic Domains

    Leslie Pack Kaelbling;Michael L. Littman;Anthony R. Cassandra

  • Learning policies for partially observable environments: scaling up

    Michael L. Littman;Anthony R. Cassandra;Leslie Pack Kaelbling

  • Acting Optimally in Partially Observable Stochastic Domains

    Anthony R. Cassandra;Leslie Pack Kaelbling;Michael L. Littman

  • Learning in Embedded Systems

    Nils J. Nilsson;Leslie Pack Kaelbling

  • Acting under uncertainty: discrete Bayesian models for mobile-robot navigation

    A.R. Cassandra;L.P. Kaelbling;J.A. Kurien

  • Hierarchical task and motion planning in the now

    Leslie Pack Kaelbling;Tomas Lozano-Perez

  • Hierarchical Planning in the Now

    Leslie Pack Kaelbling;Tomás Lozano-Pérez

  • On the complexity of solving Markov decision problems

    Michael L. Littman;Thomas L. Dean;Leslie Pack Kaelbling

  • Exact and approximate algorithms for partially observable markov decision processes

    Leslie Pack Kaelbling;Anthony Rocco Cassandra

  • An Architecture for Intelligent Reactive Systems

    Leslie Pack Kaelbling

  • The synthesis of digital machines with provable epistemic properties

    Stanley J. Rosenschein;Leslie Pack Kaelbling

  • Effective reinforcement learning for mobile robots

    Unknown

  • Integrated task and motion planning in belief space

    Leslie Pack Kaelbling;Tomás Lozano-Pérez

  • Input generalization in delayed reinforcement learning: an algorithm and performance comparisons

    David Chapman;Leslie Pack Kaelbling

  • Belief space planning assuming maximum likelihood observations

    Robert Platt;Russell Louis Tedrake;Leslie P. Kaelbling;Tomas Lozano-Perez

  • Learning to cooperate via policy search

    Leonid Peshkin;Kee-Eung Kim;Nicolas Meuleau;Leslie Pack Kaelbling

  • Action and planning in embedded agents

    Leslie Pack Kaelbling;Stanley J. Rosenschein

  • Generalization in Deep Learning

    Kenji Kawaguchi;Leslie Pack Kaelbling;Yoshua Bengio

  • Practical Reinforcement Learning in Continuous Spaces

    William D. Smart;Leslie Pack Kaelbling

  • Learning to Achieve Goals

    Leslie Pack Kaelbling

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