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Computer Science

D-Index
60
Citations
18422
World Ranking
3194
National Ranking
1550

David Yarowsky 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 David Yarowsky 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: 132 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

David Yarowsky 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 David Yarowsky 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

David Yarowsky is affiliated with Johns Hopkins University in the United States. Their research primarily focuses on the field of Computer Science, with a sub-specialization in Artificial Intelligence. Other subfields include Experimental and Cognitive Psychology, Health Informatics, Radiology, Nuclear Medicine and Imaging, and Physiology.

The main topics of David Yarowsky's work cover a range of areas including:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and Dialogue Systems
  • Phonetics and Phonology Research
  • Artificial Intelligence in Healthcare and Education
  • AI in Cancer Detection
  • Radiomics and Machine Learning in Medical Imaging

The following are some recent papers authored or co-authored by David Yarowsky, reflecting their involvement in interdisciplinary research:

  • "Hierarchical Bayesian Models for Latent Attribute Detection in Social Media," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "UniMorph 3.0: Universal Morphology," 2020, Minerva Access (University of Melbourne)
  • "Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations," 2025, Plastic & Reconstructive Surgery Global Open
  • "2023 International Rome consensus for the nomenclature of Sjögren disease," 2025, Nature Reviews Rheumatology
  • "Evaluating Large Language Models along Dimensions of Language Variation: A Systematik Investigation of Cross-lingual Generalization," 2024, arXiv (Cornell University)

David Yarowsky frequently collaborates with other researchers. Key co-authors include:

  • Niyati Bafna
  • Alison Mackey
  • Kenton Murray
  • David R. Mortensen
  • Hale Sirin

Their publications have appeared in several venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Minerva Access (University of Melbourne)
  • Plastic & Reconstructive Surgery Global Open
  • Nature Reviews Rheumatology
  • Proceedings of the International AAAI Conference on Web and Social Media

Best Publications

  • UNSUPERVISED WORD SENSE DISAMBIGUATION RIVALING SUPERVISED METHODS

    David Yarowsky

  • Word-sense disambiguation using statistical models of Roget's categories trained on large corpora

    David Yarowsky

  • A method for disambiguating word senses in a large corpus

    William A. Gale;Kenneth Ward Church;David Yarowsky

  • Classifying latent user attributes in twitter

    Delip Rao;David Yarowsky;Abhishek Shreevats;Manaswi Gupta

  • One sense per discourse

    William A. Gale;Kenneth W. Church;David Yarowsky

  • Inducing multilingual POS taggers and NP bracketers via robust projection across aligned corpora

    David Yarowsky;Grace Ngai

  • Inducing multilingual text analysis tools via robust projection across aligned corpora

    David Yarowsky;Grace Ngai;Richard Wicentowski

  • One sense per collocation

    David Yarowsky

  • DECISION LISTS FOR LEXICAL AMBIGUITY RESOLUTION: Application to Accent Restoration in Spanish and French

    David Yarowsky

  • Unsupervised personal name disambiguation

    Gideon S. Mann;David Yarowsky

  • Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence.

    Silviu Cucerzan;David Yarowsky

  • Distinguishing systems and distinguishing senses: new evaluation methods for Word Sense Disambiguation

    Philip Resnik;David Yarowsky

  • Estimating Upper and Lower Bounds on the Performance of Word-Sense Disambiguation Programs

    William Gale;Kenneth Ward Church;David Yarowsky

  • The SIGMORPHON 2016 Shared Task - Morphological Reinflection.

    Ryan Cotterell;Christo Kirov;John Sylak-Glassman;David Yarowsky

  • Homograph Disambiguation in Text-to-Speech Synthesis

    David Yarowsky

  • Minimally supervised morphological analysis by multimodal alignment

    David Yarowsky;Richard Wicentowski

  • Bootstrapping a multilingual part-of-speech tagger in one person-day

    Silviu Cucerzan;David Yarowsky

  • Using Bilingual Materials to Develop Word Sense Disambiguation Methods

    William A. Gale;Kenneth W. Church;David Yarowsky

  • Word disambiguation methods and apparatus

    Kenneth Ward Church;William Arthur Gale;David Eric Yarowsky

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

    David Yarowsky;Timothy Baldwin;Anna Korhonen;Karen Livescu

  • Natural Language Processing Using Very Large Corpora

    S. Armstrong;Kenneth Church;Pierre Isabelle

Frequent Co-Authors

Ryan Cotterell
Ryan Cotterell ETH Zurich
Kenneth Church
Kenneth Church Baidu (China)
Jason Eisner
Jason Eisner Johns Hopkins University
William A. Gale
William A. Gale Salesforce (United States)
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Ting Liu
Ting Liu Harbin Institute of Technology
Douglas W. Oard
Douglas W. Oard University of Maryland, College Park
Haifeng Wang
Haifeng Wang Baidu (China)
Wanxiang Che
Wanxiang Che Harbin Institute of Technology

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