World's Best Scientists 2026 revealed!
Joel Lehman

Joel Lehman

D-Index & Metrics

Computer Science

D-Index
34
Citations
8386
World Ranking
11930
National Ranking
4875

Joel Lehman 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 Joel Lehman 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: 91 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Joel Lehman 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 Joel Lehman 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Joel Lehman is affiliated with OpenAI in the United States and has contributed extensively to the field of computer science, focusing primarily on artificial intelligence. Their work spans several subfields, including artificial intelligence, safety research, sociology and political science, health informatics, and cognitive neuroscience.

The research topics covered by Joel Lehman include:

  • Reinforcement Learning in Robotics
  • Evolutionary Algorithms and Applications
  • Topic Modeling
  • Evolutionary Game Theory and Cooperation
  • Natural Language Processing Techniques
  • Ethics and Social Impacts of AI
  • Artificial Intelligence in Healthcare and Education

Joel Lehman has published in a variety of venues, with a frequent presence in:

  • arXiv (Cornell University)
  • Artificial Life
  • ACM Transactions on Evolutionary Learning and Optimization
  • Nature

Some of the recent papers authored or coauthored by Joel Lehman include:

  • The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities, 2020, Artificial Life
  • Learning to Continually Learn, 2020, arXiv (Cornell University)
  • Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions, 2020, arXiv (Cornell University)
  • Language Model Crossover: Variation through Few-Shot Prompting, 2024, ACM Transactions on Evolutionary Learning and Optimization
  • The Ethics of Advanced AI Assistants, 2024, arXiv (Cornell University)

Joel Lehman often collaborates with other researchers. Frequent coauthors include:

  • Kenneth O. Stanley
  • Jeff Clune
  • Herbie Bradley
  • Elliot Meyerson
  • Matija Franklin

Best Publications

  • Abandoning objectives: Evolution through the search for novelty alone

    Joel Lehman;Kenneth O. Stanley

  • An intriguing failing of convolutional neural networks and the CoordConv solution

    Rosanne Liu;Joel Lehman;Piero Molino;Felipe Petroski Such

  • Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

    Felipe Petroski Such;Vashisht Madhavan;Edoardo Conti;Joel Lehman

  • Designing neural networks through neuroevolution

    Kenneth O. Stanley;Kenneth O. Stanley;Jeff Clune;Jeff Clune;Joel Lehman;Risto Miikkulainen

  • Exploiting Open-Endedness to Solve Problems Through the Search for Novelty

    Joel Lehman;Kenneth O. Stanley

  • Evolving a diversity of virtual creatures through novelty search and local competition

    Joel Lehman;Kenneth O. Stanley

  • First return, then explore

    Adrien Ecoffet;Adrien Ecoffet;Joost Huizinga;Joost Huizinga;Joel Lehman;Joel Lehman;Kenneth O. Stanley;Kenneth O. Stanley

  • Go-Explore: a New Approach for Hard-Exploration Problems

    Adrien Ecoffet;Joost Huizinga;Joel Lehman;Kenneth O. Stanley

  • Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

    Edoardo Conti;Vashisht Madhavan;Felipe Petroski Such;Joel Lehman

  • The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

    Joel Lehman;Jeff Clune;Dusan Misevic;Christoph Adami

  • A Neuroevolution Approach to General Atari Game Playing

    Matthew Hausknecht;Joel Lehman;Risto Miikkulainen;Peter Stone

  • The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

    Joel Lehman;Jeff Clune;Dusan Misevic;Christoph Adami

  • Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions

    Rui Wang;Joel Lehman;Jeff Clune;Kenneth O. Stanley

  • Revising the evolutionary computation abstraction: minimal criteria novelty search

    Joel Lehman;Kenneth O. Stanley

  • Novelty Search and the Problem with Objectives

    Joel Lehman;Kenneth O. Stanley

  • Efficiently evolving programs through the search for novelty

    Joel Lehman;Kenneth O. Stanley

  • Learning to Continually Learn

    Shawn Beaulieu;Lapo Frati;Thomas Miconi;Joel Lehman

  • Safe mutations for deep and recurrent neural networks through output gradients

    Joel Lehman;Jay Chen;Jeff Clune;Kenneth O. Stanley

  • Combining search-based procedural content generation and social gaming in the Petalz video game

    Sebastian Risi;Joel Lehman;David B. D'Ambrosio;Ryan Hall

  • Effective diversity maintenance in deceptive domains

    Joel Lehman;Kenneth O. Stanley;Risto Miikkulainen

  • ES is more than just a traditional finite-difference approximator

    Joel Lehman;Jay Chen;Jeff Clune;Kenneth O. Stanley

  • Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

    Felipe Petroski Such;Aditya Rawal;Joel Lehman;Kenneth Stanley

Frequent Co-Authors

Kenneth O. Stanley
Kenneth O. Stanley University of Central Florida
Jeff Clune
Jeff Clune University of British Columbia
Sebastian Risi
Sebastian Risi IT University of Copenhagen
Risto Miikkulainen
Risto Miikkulainen The University of Texas at Austin
Jian Peng
Jian Peng University of Illinois at Urbana-Champaign
William F. Punch
William F. Punch Michigan State University
Marc Schoenauer
Marc Schoenauer French Institute for Research in Computer Science and Automation - INRIA
Hod Lipson
Hod Lipson Columbia University
Peter Stone
Peter Stone The University of Texas at Austin
François Taddei
François Taddei Université Paris Cité

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens the door to many related online degree programs and career paths. Whether you are looking for flexibility, affordability, or a way to accelerate your studies, online degrees provide a range of options to meet diverse needs.

Students interested in fast-tracking their education can consider enrolling in a 1 year computer science degree online. This option allows motivated learners to complete their studies at an accelerated pace while gaining the technical skills needed for in-demand tech careers.

There are also interdisciplinary opportunities, such as earning an environmental engineering online degree. This pathway is ideal for students who want to combine computer science with sustainability and environmental problem-solving.

If you are interested in a more specialized field, consider options like the cheapest online master's mechanical engineering or an online physics degree. These programs can expand your expertise and open career opportunities in engineering, research, and academia.

Exploring these related degrees can help you tailor your education to your career goals and keep pace with the evolving demands of the job market.

Best Scientists Citing Joel Lehman

Trending Scientists

Recently Published Articles