World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
29174
World Ranking
850
National Ranking
466

Kevin Knight 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 Kevin Knight 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: 270 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Kevin Knight 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 Kevin Knight 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: 84 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Overview

Kevin Knight is affiliated with the University of Southern California in the United States. Their research spans interdisciplinary fields including Computer Science, Medicine, and Psychology, with a significant focus on artificial intelligence and health-related topics.

The principal fields of study in their work are:

  • Computer Science
  • Medicine
  • Psychology

The scientist's subfields of expertise include:

  • Artificial Intelligence
  • General Health Professions
  • Clinical Psychology
  • Epidemiology
  • Sociology and Political Science

Kevin Knight's research topics cover a range of social and health-related issues. These include:

  • HIV, Drug Use, Sexual Risk
  • Criminal Justice and Corrections Analysis
  • Natural Language Processing Techniques
  • HIV/AIDS Research and Interventions
  • Homelessness and Social Issues
  • Topic Modeling
  • Child and Adolescent Psychosocial and Emotional Development

The scientist has published frequently in the following venues:

  • arXiv (Cornell University)
  • Substance Use & Misuse
  • Journal of Substance Abuse Treatment
  • Journal of Offender Rehabilitation
  • Frontiers in Psychology

Recent papers from Kevin Knight include:

  • "Linking criminal justice-involved individuals to HIV, Hepatitis C, and opioid use disorder prevention and treatment services upon release to the community: Progress, gaps, and future directions" (2021) published in International Journal of Drug Policy
  • "Preventing opioid use among justice-involved youth as they transition to adulthood: leveraging safe adults (LeSA)" (2021) published in BMC Public Health
  • "Study protocol of a randomized controlled trial comparing two linkage models for HIV prevention and treatment in justice-involved persons" (2022) published in BMC Infectious Diseases
  • "Justice community opioid innovation network (JCOIN): The TCU research hub" (2021) published in Journal of Substance Abuse Treatment
  • "The Role of Personality Functioning on Early Drop out in Outpatient Substance Misuse Treatment" (2021) published in Substance Use & Misuse

Frequent co-authors working alongside Kevin Knight include:

  • Thomas B. Sease
  • Amanda L. Wiese
  • Wayne E. K. Lehman
  • Jennifer E. Becan
  • Jennifer Pankow

Best Publications

  • Machine transliteration

    Kevin Knight;Jonathan Graehl

  • Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

    Kevin Knight;Ani Nenkova;Owen Rambow

  • Abstract Meaning Representation for Sembanking

    Laura Banarescu;Claire Bonial;Shu Cai;Madalina Georgescu

  • A Syntax-based Statistical Translation Model

    Kenji Yamada;Kevin Knight

  • Transfer Learning for Low-Resource Neural Machine Translation

    Barret Zoph;Deniz Yuret;Jonathan May;Kevin Knight

  • Summarization beyond sentence extraction: a probabilistic approach to sentence compression

    Kevin Knight;Daniel Marcu

  • What’s in a translation rule?

    Michel Galley;Mark Hopkins;Kevin Knight;Daniel Marcu

  • Generation that Exploits Corpus-Based Statistical Knowledge

    Irene Langkilde;Kevin Knight

  • Statistics-Based Summarization - Step One: Sentence Compression

    Kevin Knight;Daniel Marcu

  • Scalable Inference and Training of Context-Rich Syntactic Translation Models

    Michel Galley;Jonathan Graehl;Kevin Knight;Daniel Marcu

  • Building a large-scale knowledge base for machine translation

    Kevin Knight;Steve K. Luk

  • Unification: a multidisciplinary survey

    Kevin Knight

  • Statistical machine translation

    Kevin Knight;Philipp Koehn

  • Decoding complexity in word-replacement translation models

    Kevin Knight

  • Empirical methods for compound splitting

    Philipp Koehn;Kevin Knight

  • Cross-lingual Name Tagging and Linking for 282 Languages

    Xiaoman Pan;Boliang Zhang;Jonathan May;Joel Nothman

  • Fast and optimal decoding for machine translation

    Ulrich Germann;Michael Jahr;Kevin Knight;Daniel Marcu

  • Plan-And-Write: Towards Better Automatic Storytelling

    Lili Yao;Nanyun Peng;Ralph M. Weischedel;Kevin Knight

  • Does String-Based Neural MT Learn Source Syntax?

    Xing Shi;Inkit Padhi;Kevin Knight

  • Fast Decoding and Optimal Decoding for Machine Translation

    Ulrich Germann;Michael Jahr;Kevin Knight;Daniel Marcu

  • Smatch: an Evaluation Metric for Semantic Feature Structures

    Shu Cai;Kevin Knight

Frequent Co-Authors

Daniel Marcu
Daniel Marcu University of Southern California
Heng Ji
Heng Ji University of Illinois at Urbana-Champaign
Philipp Koehn
Philipp Koehn Johns Hopkins University
Ashish Vaswani
Ashish Vaswani Google (United States)
Vasileios Hatzivassiloglou
Vasileios Hatzivassiloglou Columbia University
David Chiang
David Chiang University of Notre Dame
Barret Zoph
Barret Zoph Google (United States)
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Liang Huang
Liang Huang Oregon State University
Panayiotis G. Georgiou
Panayiotis G. Georgiou University of Southern California

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