World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
48784
World Ranking
3146
National Ranking
1524

Michael Lewis 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 Michael Lewis 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: 326 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Michael Lewis 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 Michael Lewis 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Michael Lewis is affiliated with the University of Pittsburgh in the United States. Their research spans multiple fields, primarily in computer science and psychology, with a focus on artificial intelligence and social psychology as key subfields. The scientist's work also intersects with cultural studies, molecular biology, and sociology and political science.

Their main research topics include human-automation interaction and safety, reinforcement learning in robotics, and team dynamics and performance. Other areas covered by their work include adversarial robustness in machine learning, language and cultural evolution, viral infectious diseases and gene expression in insects, and occupational health and safety research.

Michael Lewis has contributed to academic literature through various publication venues. These include:

  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting
  • arXiv (Cornell University)
  • Frontiers in Psychology
  • Analytical Chemistry
  • IEEE Transactions on Human-Machine Systems

They have collaborated frequently with several co-authors over the years. The most common among these are:

  • Katia Sycara
  • Huao Li
  • Dana Hughes
  • Joseph B. Lyons
  • August Capiola

Among the recent papers authored or co-authored by Michael Lewis are:

  • Human-Autonomy Teaming: Definitions, Debates, and Directions (2021), published in Frontiers in Psychology
  • ID-MAM: A Validated Identity and Multi-Attribute Monitoring Method for Commercial Release and Stability Testing of a Bispecific Antibody (2021), published in Analytical Chemistry
  • Individualized Mutual Adaptation in Human-Agent Teams (2021), published in IEEE Transactions on Human-Machine Systems
  • PACAP and VIP Neuropeptides' and Receptors' Effects on Appetite, Satiety and Metabolism (2023), published in Biology
  • Planning and Monitoring Multi-Job Type Swarm Search and Service Missions (2021), published in Journal of Intelligent & Robotic Systems

In addition to journal and conference publications, Michael Lewis has a book published by Springer International Publishing titled Fandom Analytics (2024).

Best Publications

  • RoBERTa: A Robustly Optimized BERT Pretraining Approach

    Yinhan Liu;Myle Ott;Naman Goyal;Jingfei Du

  • BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

    Mike Lewis;Yinhan Liu;Naman Goyal;Marjan Ghazvininejad

  • Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

    Patrick S. H. Lewis;Ethan Perez;Aleksandra Piktus;Fabio Petroni

  • Multilingual Denoising Pre-training for Neural Machine Translation

    Yinhan Liu;Jiatao Gu;Naman Goyal;Xian Li

  • Hierarchical Neural Story Generation

    Angela Fan;Mike Lewis;Yann N. Dauphin

  • Common metrics for human-robot interaction

    Aaron Steinfeld;Terrence Fong;David Kaber;Michael Lewis

  • End-to-end Neural Coreference Resolution

    Kenton Lee;Luheng He;Mike Lewis;Luke Zettlemoyer

  • USARSim: a robot simulator for research and education

    S. Carpin;M. Lewis;Jijun Wang;S. Balakirsky

  • Deep Semantic Role Labeling: What Works and What’s Next

    Luheng He;Kenton Lee;Mike Lewis;Luke Zettlemoyer

  • Human Interaction With Robot Swarms: A Survey

    Andreas Kolling;Phillip Walker;Nilanjan Chakraborty;Katia Sycara

  • Deal or No Deal? End-to-End Learning of Negotiation Dialogues

    Mike Lewis;Denis Yarats;Yann N. Dauphin;Devi Parikh

  • Human-robot teaming for search and rescue

    I.R. Nourbakhsh;K. Sycara;M. Koes;M. Yong

  • Asking and Answering Questions to Evaluate the Factual Consistency of Summaries

    Alex Wang;Kyunghyun Cho;Mike Lewis

  • The role of trust in human-robot interaction

    Michael Lewis;Katia Sycara;Phillip M Walker

  • GAME ENGINES IN SCIENTIFIC RESEARCH

    Jeffrey Jacobson;Michael Lewis

  • Cross-lingual Transfer Learning for Multilingual Task Oriented Dialog

    Sebastian Schuster;Sonal Gupta;Rushin Shah;Mike Lewis

  • Strategies for Structuring Story Generation

    Angela Fan;Mike Lewis;Yann N. Dauphin

  • Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language

    Luheng He;Mike Lewis;Luke Zettlemoyer

  • A Corpus of Natural Language for Visual Reasoning.

    Alane Suhr;Mike Lewis;James Yeh;Yoav Artzi

  • Generalization through Memorization: Nearest Neighbor Language Models

    Urvashi Khandelwal;Omer Levy;Dan Jurafsky;Luke Zettlemoyer

  • Deal or No Deal? End-to-End Learning for Negotiation Dialogues

    Mike Lewis;Denis Yarats;Yann N. Dauphin;Devi Parikh

  • Common metrics for human-robot interaction

    T. Fong;D. Kaber;M. Lewis;J. Scholtz

  • Question-answer driven semantic role labeling

    Luheng He;Mike Lewis;Luke Zettlemoyer

Frequent Co-Authors

Katia Sycara
Katia Sycara Carnegie Mellon University
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Mark Steedman
Mark Steedman University of Edinburgh
Christian Lebiere
Christian Lebiere Carnegie Mellon University
Terry R. Payne
Terry R. Payne University of Liverpool
Kenton Lee
Kenton Lee Google (United States)
Sebastian Scherer
Sebastian Scherer Carnegie Mellon University
Yann N. Dauphin
Yann N. Dauphin Google (United States)
Veselin Stoyanov
Veselin Stoyanov Facebook (United States)
Omer Levy
Omer Levy Deep Mind

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