World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
100
Citations
39283
World Ranking
371
National Ranking
204

Dan Roth 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 Dan Roth 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: 581 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Dan Roth 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 Dan Roth 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: 100 D-Index — 97th percentile

97% 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

  • 2014 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2011 - ACM Fellow For contributions to machine learning and natural language processing.

Overview

Dan Roth is affiliated with the University of Pennsylvania in the United States. Their research primarily centers on computer science, with a strong focus on artificial intelligence, computer vision and pattern recognition, information systems, management science and operations research, and computer networks and communications.

The scientist has contributed extensively to the fields of topic modeling, natural language processing techniques, multimodal machine learning applications, advanced text analysis techniques, explainable artificial intelligence (XAI), semantic web and ontologies, and data quality and management.

Dan Roth's recent papers include:

  • Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey (2023, ACM Computing Surveys)
  • Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022, arXiv (Cornell University))
  • Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey (2021, arXiv (Cornell University))
  • Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies (2021, Transactions of the Association for Computational Linguistics)
  • Visual Pivoting for (Unsupervised) Entity Alignment (2021, Proceedings of the AAAI Conference on Artificial Intelligence)

Frequent co-authors in their work include Hongming Zhang, Muhao Chen, Daniel Deutsch, Haoyu Wang, and Xingyu Fu.

Dan Roth has published in several recurring venues, such as:

  • arXiv (Cornell University)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Findings of the Association for Computational Linguistics: NAACL 2022

The scientist has authored a book titled "Multilingual Entity Linking," published by Morgan & Claypool Publishers in 2024.

Awards received by Dan Roth include being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2014 and an ACM Fellow in 2011 for contributions to machine learning and natural language processing.

Best Publications

  • Design Challenges and Misconceptions in Named Entity Recognition

    Lev Ratinov;Dan Roth

  • Learning question classifiers

    Xin Li;Dan Roth

  • Learning to detect objects in images via a sparse, part-based representation

    S. Agarwal;A. Awan;D. Roth

  • Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey

    Unknown

  • Emotions from Text: Machine Learning for Text-based Emotion Prediction

    Cecilia Ovesdotter Alm;Dan Roth;Richard Sproat

  • Local and Global Algorithms for Disambiguation to Wikipedia

    Lev Ratinov;Dan Roth;Doug Downey;Mike Anderson

  • On the hardness of approximate reasoning

    Dan Roth

  • Learning a Sparse Representation for Object Detection

    Shivani Agarwal;Dan Roth

  • A SNoW-Based Face Detector

    Ming-Hsuan Yang;Dan Roth;Narendra Ahuja

  • The importance of syntactic parsing and inference in semantic role labeling

    Vasin Punyakanok;Vasin Punyakanok;Vasin Punyakanok;Dan Roth;Dan Roth;Dan Roth;Wen-tau Yih;Wen-tau Yih;Wen-tau Yih

  • A Linear Programming Formulation for Global Inference in Natural Language Tasks

    Dan Roth;Wen-tau Yih

  • A Winnow-Based Approach to Context-Sensitive Spelling Correction

    Andrew R. Golding;Dan Roth

  • Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences

    Daniel Khashabi;Snigdha Chaturvedi;Michael Roth;Shyam Upadhyay

  • Lifted first-order probabilistic inference

    Rodrigo De Salvo Braz;Eyal Amir;Dan Roth

  • Learning question classifiers: the role of semantic information

    Xin Li;Dan Roth

  • Understanding the Value of Features for Coreference Resolution

    Eric Bengtson;Dan Roth

  • Knowing What to Believe (when you already know something)

    Jeff Pasternack;Dan Roth

  • Recognizing textual entailment: Rational, evaluation and approaches – Erratum

    Ido Dagan;Bill Dolan;Bernardo Magnini;Dan Roth

  • Constraint Classification for Multiclass Classification and Ranking

    Sariel Har-Peled;Dan Roth;Dav Zimak

  • Recognizing Textual Entailment: Models and Applications

    Ido Dagan;Dan Roth;Mark Sammons;Fabio Massimo Zanzotto

  • Solving General Arithmetic Word Problems

    Subhro Roy;Dan Roth

  • Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

    Mor Geva;Daniel Khashabi;Elad Segal;Tushar Khot

  • Synthesis Lectures on Human Language Technologies

    Ido Dagan;Dan Roth;Mark Sammons;Fabio Massimo Zanzotto

Frequent Co-Authors

Daniel Khashabi
Daniel Khashabi Johns Hopkins University
Vivek Srikumar
Vivek Srikumar University of Utah
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology
Wen-tau Yih
Wen-tau Yih Facebook (United States)
Ming-Wei Chang
Ming-Wei Chang Google (United States)
Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Wenpeng Yin
Wenpeng Yin Pennsylvania State University
Sariel Har-Peled
Sariel Har-Peled University of Illinois at Urbana-Champaign
Ido Dagan
Ido Dagan Bar-Ilan University

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