World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
17764
World Ranking
6019
National Ranking
2708

Steven Bethard 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 Steven Bethard 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: 176 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Steven Bethard 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 Steven Bethard 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Steven Bethard is affiliated with the University of Arizona in the United States and specializes primarily in the field of Computer Science. Within this broad domain, their work extensively covers subfields such as Artificial Intelligence, Communication, Molecular Biology, Sociology and Political Science, and Information Systems.

Their research focuses on a variety of topics including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Biomedical Text Mining and Ontologies
  • Social Media and Politics
  • Domain Adaptation and Few-Shot Learning
  • Semantic Web and Ontologies
  • Intelligent Tutoring Systems and Adaptive Learning

Steven Bethard has contributed to several recent academic papers. Notable publications include:

  • "Does BERT need domain adaptation for clinical negation detection?" (2020), published in the Journal of the American Medical Informatics Association
  • "Rethinking domain adaptation for machine learning over clinical language" (2020), published in JAMIA Open
  • "Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)-based ranking for concept normalization" (2020), published in the Journal of the American Medical Informatics Association
  • "Toward NEPA performance: A framework for assessing EIAs" (2022), published in Environmental Impact Assessment Review
  • "A Comparison of Strategies for Source-Free Domain Adaptation" (2022), published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Common co-authors with whom Steven Bethard frequently collaborates include:

  • Xin Su
  • Egoitz Laparra
  • Guergana Savova
  • Timothy A. Miller
  • Stephen A. Rains

Their work has been published in several venues multiple times. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Journal of the American Medical Informatics Association
  • Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
  • Zenodo (CERN European Organization for Nuclear Research)
  • JAMIA Open

Best Publications

  • The Stanford CoreNLP Natural Language Processing Toolkit

    Christopher Manning;Mihai Surdeanu;John Bauer;Jenny Finkel

  • A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

    Vikas Yadav;Steven Bethard

  • A survey on the application of recurrent neural networks to statistical language modeling

    Wim De Mulder;Steven Bethard;Marie-Francine Moens

  • How Good Are Humans at Solving CAPTCHAs? A Large Scale Evaluation

    Elie Bursztein;Steven Bethard;Celine Fabry;John C. Mitchell

  • Proceedings of The 12th International Workshop on Semantic Evaluation

    Marianna Apidianaki;Saif M. Mohammad;Jonathan May;Ekaterina Shutova

  • Automatic Extraction of Opinion Propositions and their Holders

    Steven Bethard;Hong Yu;Ashley Thornton;Vasileios Hatzivassiloglou

  • Overview for the First Shared Task on Language Identification in Code-Switched Data

    Unknown

  • SemEval-2016 Task 12: Clinical TempEval

    Steven Bethard;Guergana Savova;Wei-Te Chen;Leon Derczynski

  • Overview for the First Shared Task on Language Identification in Code-Switched Data

    Thamar Solorio;Elizabeth Blair;Suraj Maharjan;Steven Bethard

  • Not All Character N-grams Are Created Equal: A Study in Authorship Attribution

    Upendra Sapkota;Steven Bethard;Manuel Montes;Thamar Solorio

  • Temporal Annotation in the Clinical Domain

    William F. Styler;Steven Bethard;Sean Finan;Martha Palmer

  • Dense Event Ordering with a Multi-Pass Architecture

    Nathanael Chambers;Taylor Cassidy;Bill McDowell;Steven Bethard

  • Crowdsourcing and language studies: the new generation of linguistic data

    Robert Munro;Steven Bethard;Victor Kuperman;Vicky Tzuyin Lai

  • SemEval-2015 Task 6: Clinical TempEval

    Steven Bethard;Leon Derczynski;Guergana Savova;James Pustejovsky

  • Who should I cite: learning literature search models from citation behavior

    Steven Bethard;Dan Jurafsky

  • DLS$@$CU: Sentence Similarity from Word Alignment and Semantic Vector Composition

    Arafat Sultan;Steven Bethard;Tamara Sumner

  • An Annotation Framework for Dense Event Ordering

    Taylor Cassidy;Bill McDowell;Nathanael Chambers;Steven Bethard

  • ClearTK-TimeML: A minimalist approach to TempEval 2013

    Steven Bethard

  • Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

    David Yarowsky;Timothy Baldwin;Anna Korhonen;Karen Livescu

  • Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

    Jyotishman D Pathak;Kent R Bailey;Calvin E. Beebe;Steven Bethard

  • Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence

    Arafat Sultan;Steven Bethard;Tamara Sumner

  • Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

    Steven Bethard;Marine Carpuat;Marianna Apidianaki;Saif M. Mohammad

Frequent Co-Authors

Guergana Savova
Guergana Savova Harvard University
James H. Martin
James H. Martin University of Colorado Boulder
Mihai Surdeanu
Mihai Surdeanu University of Arizona
Thamar Solorio
Thamar Solorio Mohamed bin Zayed University of Artificial Intelligence
Dan Jurafsky
Dan Jurafsky Stanford University
Martha Palmer
Martha Palmer University of Colorado Boulder
James Pustejovsky
James Pustejovsky Brandeis University
Sameer Pradhan
Sameer Pradhan Vassar College
Ted Pedersen
Ted Pedersen University of Minnesota

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

Exploring online study options in the USA opens up various career pathways in STEM. For those pursuing a technology-driven career, options like the fastest computer science degree programs are designed to help students graduate quickly and enter the rapidly evolving tech market.

Many students are also attracted to affordable programs in related sciences and engineering fields. If you are interested in sustainability, consider the cheapest online environmental science degree programs, which provide a budget-friendly entry into impactful careers.

Engineering remains a popular choice for its versatility. The mechanical engineering degree online cost is a crucial consideration for those looking to minimize debt while building practical skills for the job market.

For students passionate about the fundamental sciences, an affordable physics degree online offers strong analytical and problem-solving skills applicable across many industries.

Each pathway offers unique benefits, from accelerated completion times to cost savings, making online degrees a flexible option for future professionals in computer science and beyond.

Best Scientists Citing Steven Bethard

Trending Scientists

Recently Published Articles