World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7472
World Ranking
8386
National Ranking
3593

Haym Hirsh 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 Haym Hirsh 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: 136 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Haym Hirsh 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 Haym Hirsh 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Haym Hirsh is affiliated with Cornell University in the United States. Their research contributions include work published in venues such as Nature Machine Intelligence.

The scientist has worked on topics related to accelerating evidence-informed decision-making for global development goals, with specific focus on applications of machine learning. A recent publication titled Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning was published in 2020 in Nature Machine Intelligence.

Collaborative efforts are notable in their work, with frequent co-authors including Jaron Porciello, Maryia Ivanina, Maidul Islam, and Stefan Einarson.

Publication venues associated with their work include:

  • Nature Machine Intelligence

Recent papers documented include:

  • Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning, 2020, Nature Machine Intelligence

Best Publications

  • Recommendation as classification: using social and content-based information in recommendation

    Chumki Basu;Haym Hirsh;William Cohen

  • Learning to predict rare events in event sequences

    Gary M. Weiss;Haym Hirsh

  • Predicting Sequences of User Actions

    Brian D. Davison;Haym Hirsh

  • Computing least common subsumers in description logics

    William W. Cohen;Alex Borgida;Haym Hirsh

  • Learning the classic description logic: theoretical and experimental results

    William W. Cohen;Haym Hirsh

  • Mining Text Using Keyword Distributions

    Ronen Feldman;Ido Dagan;Haym Hirsh

  • Joins that generalize: text classification using WHIRL

    William W. Cohen;Haym Hirsh

  • Amplify scientific discovery with artificial intelligence

    Yolanda Gil;Mark Greaves;James Hendler;Haym Hirsh

  • Using LSI for text classification in the presence of background text

    Sarah Zelikovitz;Haym Hirsh

  • Mining associations in text in the presence of background knowledge

    Ronen Feldman;Haym Hirsh

  • Technical paper recommendation: a study in combining multiple information sources

    Chumki Basu;Haym Hirsh;William W. Cohen;Craig Nevill-Manning

  • Towards Measuring Similarity in Description Logics.

    Alexander Borgida;Thomas J. Walsh;Haym Hirsh

  • Learning to personalize

    Haym Hirsh;Chumki Basu;Brian D. Davison

  • Knowledge Management: A Text Mining Approach

    R. Feldman;M. Fresko;H. Hirsh;Y. Aumann

  • Generalizing Version Spaces

    Haym Hirsh

  • A Quantitative Study of Small Disjuncts

    Gary M. Weiss;Haym Hirsh

  • Gado: a genetic algorithm for continuous design optimization

    Khaled Mohamed Rasheed;Haym Hirsh

  • Exploiting Background Information in Knowledge Discovery from Text

    Ronen Feldman;Haym Hirsh

  • A genetic algorithm for continuous design space search

    Khaled Rasheed;Haym Hirsh;Andrew Gelsey

  • The Learnability of Description Logics with Equality Constraints

    William W. Cohen;Haym Hirsh

  • Enabling technologies: learning to personalize.

    Haym Hirsh;Chumki Basu;Brian D. Davison

Frequent Co-Authors

William W. Cohen
William W. Cohen Carnegie Mellon University
Brian D. Davison
Brian D. Davison Lehigh University
Gary M. Weiss
Gary M. Weiss Fordham University
Cynthia Rudin
Cynthia Rudin Duke University
Ronen Feldman
Ronen Feldman Hebrew University of Jerusalem
Daniel Kudenko
Daniel Kudenko L3S Research Center
Yolanda Gil
Yolanda Gil University of Southern California
Foster Provost
Foster Provost New York University
Alexander Borgida
Alexander Borgida Rutgers, The State University of New Jersey
Ido Dagan
Ido Dagan Bar-Ilan University

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