World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
8807
World Ranking
12393
National Ranking
5023

David Chiang 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 Chiang 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: 125 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

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

David Chiang 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 Chiang 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

David Chiang is affiliated with the University of Notre Dame in the United States. Their research primarily spans the field of Computer Science, with a particular focus on Artificial Intelligence and Computational Theory and Mathematics. Additional subfields of interest include Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, and Management Science and Operations Research.

The scientist's work covers a range of main topics, prominently featuring Natural Language Processing Techniques and Topic Modeling. Other notable areas of research include semigroups and automata theory, Text Readability and Simplification, Ferroelectric and Negative Capacitance Devices, Speech Recognition and Synthesis, and Formal Methods in Verification.

David Chiang has contributed extensively to scholarly publications, with frequent appearances in several venues. The most common publication platform is arXiv (Cornell University), where they have 37 publications. Other key venues include Transactions of the Association for Computational Linguistics with 2 publications, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Proceedings of the ACM on Programming Languages, and Engineering Optimization.

Recent papers by David Chiang include the following:

  • Overcoming a Theoretical Limitation of Self-Attention (2022), published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Exact Recursive Probabilistic Programming (2023), published in the Proceedings of the ACM on Programming Languages
  • Tighter Bounds on the Expressivity of Transformer Encoders (2023), available on arXiv (Cornell University)
  • Named Tensor Notation (2021), available on arXiv (Cornell University)

David Chiang also appears as a co-author in works with several frequent collaborators, including Dana Angluin, Lena Strobl, Brian DuSell, Ryan Cotterell, and Andy Yang.

Best Publications

  • A Hierarchical Phrase-Based Model for Statistical Machine Translation

    David Chiang

  • Hierarchical Phrase-Based Translation

    David Chiang

  • DyNet: The Dynamic Neural Network Toolkit

    Graham Neubig;Chris Dyer;Yoav Goldberg;Austin Matthews

  • Better k-best Parsing

    Liang Huang;David Chiang

  • Word Sense Disambiguation Improves Statistical Machine Translation

    Yee Seng Chan;Hwee Tou Ng;David Chiang

  • Forest Rescoring: Faster Decoding with Integrated Language Models

    Liang Huang;David Chiang

  • Online Large-Margin Training of Syntactic and Structural Translation Features

    David Chiang;Yuval Marton;Philip Resnik

  • 11,001 New Features for Statistical Machine Translation

    David Chiang;Kevin Knight;Wei Wang

  • Decoding with Large-Scale Neural Language Models Improves Translation

    Ashish Vaswani;Yinggong Zhao;Victoria Fossum;David Chiang

  • Statistical parsing with an automatically-extracted tree adjoining grammar

    David Chiang

  • Tied Multitask Learning for Neural Speech Translation

    Antonios Anastasopoulos;David Chiang

  • Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation

    Toan Q. Nguyen;David Chiang

  • An attentional model for speech translation without transcription

    Long Duong;Antonios Anastasopoulos;David Chiang;Steven Bird;Steven Bird

  • Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder

    Huadong Chen;Shujian Huang;David Chiang;Jiajun Chen

  • Learning to Translate with Source and Target Syntax

    David Chiang

  • Two Statistical Parsing Models Applied to the Chinese Treebank

    Daniel M. Bikel;David Chiang

  • Correcting Length Bias in Neural Machine Translation

    Kenton Murray;David Chiang

  • Parsing arabic dialects

    David Chiang;Mona T. Diab;Nizar Habash;Owen Rambow

  • Recovering latent information in treebanks

    David Chiang;Daniel M. Bikel

  • Improving Lexical Choice in Neural Machine Translation.

    Toan Q. Nguyen;David Chiang

Frequent Co-Authors

Ashish Vaswani
Ashish Vaswani Google (United States)
Dekai Wu
Dekai Wu Hong Kong University of Science and Technology
Kevin Knight
Kevin Knight University of Southern California
Aravind K. Joshi
Aravind K. Joshi University of Pennsylvania
Shujian Huang
Shujian Huang Nanjing University
Steven Bird
Steven Bird Charles Darwin University
Liang Huang
Liang Huang Oregon State University
Walter J. Scheirer
Walter J. Scheirer University of Notre Dame
Philip Resnik
Philip Resnik University of Maryland, College Park
Owen Rambow
Owen Rambow Stony Brook University

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