World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
27862
World Ranking
4677
National Ranking
2170

Samuel R. Bowman 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 Samuel R. Bowman 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: 120 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Samuel R. Bowman 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 Samuel R. Bowman 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: 53 D-Index — 67th percentile

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

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

Overview

Samuel R. Bowman is affiliated with New York University in the United States. Their research primarily focuses on computer science, with a specialization in artificial intelligence. They have contributed notably to several related subfields including information systems, computer science applications, and computer vision and pattern recognition.

Their publications encompass a wide range of topics within the broader scope of artificial intelligence. Main areas of focus include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Explainable Artificial Intelligence (XAI)
  • Speech and Dialogue Systems
  • Mobile Crowdsensing and Crowdsourcing
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification

Samuel R. Bowman has published extensively in academic venues. Frequent publication platforms include:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Critical AI
  • Proceedings of the AAAI Conference on Artificial Intelligence

Recent papers authored or coauthored by Bowman illustrate their involvement in contemporary research discussions. Notable papers include:

  • "Eight Things to Know about Large Language Models", 2023, arXiv (Cornell University)
  • "Constitutional AI: Harmlessness from AI Feedback", 2022, arXiv (Cornell University)
  • "Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting", 2023, arXiv (Cornell University)
  • "Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?", 2020, arXiv (Cornell University)
  • "Towards Understanding Sycophancy in Language Models", 2023, arXiv (Cornell University)

Bowman has frequently collaborated with other researchers, with consistent coauthors being:

  • Ethan Perez
  • Jason Phang
  • Jared Kaplan
  • Alicia Parrish
  • Haokun Liu

With a publication record of 144 works in computer science and 126 in artificial intelligence alone, Bowman's academic output reflects sustained activity in these fields. Their extensive work on topic modeling and natural language processing techniques positions them within key areas of current AI research and development.

Best Publications

  • GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

    Alex Wang;Amanpreet Singh;Julian Michael;Felix Hill

  • A large annotated corpus for learning natural language inference

    Samuel R. Bowman;Gabor Angeli;Christopher Potts;Christopher D. Manning

  • A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

    Adina Williams;Nikita Nangia;Samuel R. Bowman

  • Generating Sentences from a Continuous Space

    Samuel R. Bowman;Luke Vilnis;Oriol Vinyals;Andrew M. Dai

  • SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems

    Alex Wang;Yada Pruksachatkun;Nikita Nangia;Amanpreet Singh

  • Annotation Artifacts in Natural Language Inference Data

    Suchin Gururangan;Swabha Swayamdipta;Omer Levy;Roy Schwartz;Roy Schwartz

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams

  • Neural Network Acceptability Judgments

    Alex Warstadt;Amanpreet Singh;Samuel R. Bowman

  • Universal Dependencies 2.2

    Joakim Nivre;Mitchell Abrams;Željko Agić;Lars Ahrenberg

  • Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks

    Jason Phang;Thibault Févry;Samuel R. Bowman

  • What do you learn from context? Probing for sentence structure in contextualized word representations

    Ian Tenney;Patrick Xia;Berlin Chen;Alex Wang

  • On Measuring Social Biases in Sentence Encoders

    Chandler May;Alex Wang;Shikha Bordia;Samuel R. Bowman

  • A Fast Unified Model for Parsing and Sentence Understanding

    Samuel R. Bowman;Jon Gauthier;Abhinav Rastogi;Raghav Gupta

  • CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

    Nikita Nangia;Clara Vania;Rasika Bhalerao;Samuel R. Bowman

  • BLiMP: The Benchmark of Linguistic Minimal Pairs for English

    Alex Warstadt;Alicia Parrish;Haokun Liu;Anhad Mohananey

  • A Gold Standard Dependency Corpus for English

    Natalia Silveira;Timothy Dozat;Marie-Catherine de Marneffe;Samuel Bowman

  • Universal Dependencies 2.1

    Joakim Nivre;Željko Agić;Lars Ahrenberg;Lene Antonsen

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Guillaume Lample;Ruty Rinott;Adina Williams

  • Identifying and reducing gender bias in word-level language models

    Shikha Bordia;Samuel R. Bowman

  • Universal Dependencies 2.0

    Joakim Nivre;Željko Agić;Lars Ahrenberg;Maria Jesus Aranzabe

  • Universal Dependencies 2.7

    Daniel Zeman;Joakim Nivre;Mitchell Abrams;Elia Ackermann

Frequent Co-Authors

Christopher D. Manning
Christopher D. Manning Stanford University
Marie-Catherine de Marneffe
Marie-Catherine de Marneffe The Ohio State University
Jan Hajič
Jan Hajič Charles University
Sampo Pyysalo
Sampo Pyysalo University of Turku
Barbara Plank
Barbara Plank Ludwig-Maximilians-Universität München
Filip Ginter
Filip Ginter University of Turku
Slav Petrov
Slav Petrov Google (United States)
Joakim Nivre
Joakim Nivre Uppsala University

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