World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
12461
World Ranking
9510
National Ranking
4028

Daniel Gildea 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 Daniel Gildea 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: 143 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Daniel Gildea 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 Daniel Gildea 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Daniel Gildea is a researcher affiliated with the University of Rochester in the United States, with a broad focus encompassing computer science and medicine. Their work spans multiple subfields, including artificial intelligence, computer vision and pattern recognition, pulmonary and respiratory medicine, molecular biology, and surgery.

Their research covers a range of topics within these fields. Key areas include natural language processing techniques, topic modeling, multimodal machine learning applications, algorithms and data compression, advanced graph neural networks, speech and dialogue systems, and neonatal respiratory health research.

Gildea has authored several papers published in various academic venues. Some recent works are:

  • Evidence Integration for Multi-Hop Reading Comprehension With Graph Neural Networks, 2020, IEEE Transactions on Knowledge and Data Engineering
  • Hierarchical Context Tagging for Utterance Rewriting, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Derivation of a Natural Language Processing Algorithm to Identify Febrile Infants, 2022, Journal of Hospital Medicine
  • Unsupervised Bilingual Lexicon Induction Across Writing Systems, 2020, arXiv (Cornell University)
  • AWLCO: All-Window Length Co-Occurrence, 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Frequent co-authors collaborating with Daniel Gildea include Lisa Jin, Linfeng Song, Joshua Sobel, Noah Bertram, and Chen Ding.

The main publication venues where Gildea's work has appeared are:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Journal of Hospital Medicine
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Best Publications

  • The Proposition Bank: An Annotated Corpus of Semantic Roles

    Martha Palmer;Daniel Gildea;Paul Kingsbury

  • Automatic labeling of semantic roles

    Daniel Gildea;Daniel Jurafsky

  • Effects of disfluencies, predictability, and utterance position on word form variation in English conversation

    Alan Bell;Daniel Jurafsky;Eric Fosler-Lussier;Cynthia Girand

  • Corpus Variation and Parser Performance

    Daniel Gildea

  • A Smorgasbord of Features for Statistical Machine Translation

    Franz Josef Och;Daniel Gildea;Sanjeev Khudanpur;Anoop Sarkar

  • Topic-based language models using EM.

    Daniel Gildea;Thomas Hofmann

  • The Necessity of Parsing for Predicate Argument Recognition

    Daniel Gildea;Martha Palmer

  • Loosely Tree-Based Alignment for Machine Translation

    Daniel Gildea

  • A Graph-to-Sequence Model for AMR-to-Text Generation

    Linfeng Song;Yue Zhang;Zhiguo Wang;Daniel Gildea

  • Syntactic Features for Evaluation of Machine Translation

    Ding Liu;Daniel Gildea

  • Do Grammars Minimize Dependency Length

    Daniel Gildea;David Temperley

  • N-ary Relation Extraction using Graph-State LSTM

    Linfeng Song;Yue Zhang;Zhiguo Wang;Daniel Gildea

  • Synchronous Binarization for Machine Translation

    Hao Zhang;Liang Huang;Daniel Gildea;Kevin Knight

  • Leveraging Context Information for Natural Question Generation

    Linfeng Song;Zhiguo Wang;Wael Hamza;Yue Zhang

  • Semantic Neural Machine Translation using AMR

    Linfeng Song;Daniel Gildea;Yue Zhang;Zhiguo Wang

  • Automated Analysis and Prediction of Job Interview Performance

    Iftekhar Naim;Md. Iftekhar Tanveer;Daniel Gildea;Mohammed Ehsan Hoque

  • Identifying semantic roles using Combinatory Categorial Grammar

    Daniel Gildea;Julia Hockenmaier

  • Automated prediction and analysis of job interview performance: The role of what you say and how you say it

    Iftekhar Naim;M. Iftekhar Tanveer;Daniel Gildea;Mohammed Ehsan Hoque

  • Semantic Role Features for Machine Translation

    Ding Liu;Daniel Gildea

  • Learning bias and phonological-rule induction

    Daniel Gildea;Daniel Jurafsky

  • Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks.

    Linfeng Song;Zhiguo Wang;Mo Yu;Yue Zhang

Frequent Co-Authors

Yue Zhang
Yue Zhang Westlake University
Dan Jurafsky
Dan Jurafsky Stanford University
James F. Allen
James F. Allen University of Rochester
Liang Huang
Liang Huang Oregon State University
Jinsong Su
Jinsong Su Xiamen University
Mo Yu
Mo Yu IBM (United States)
Henry Kautz
Henry Kautz University of Virginia
Jiebo Luo
Jiebo Luo University of Rochester
Shay B. Cohen
Shay B. Cohen University of Edinburgh
Martha Palmer
Martha Palmer University of Colorado Boulder

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