World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
4992
World Ranking
10876
National Ranking
4524

Kenji Sagae 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 Kenji Sagae 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: 112 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Kenji Sagae 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 Kenji Sagae 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Kenji Sagae is affiliated with the University of California, Davis in the United States. Their research work spans multiple fields, primarily within computer science and psychology, with a focus on artificial intelligence and developmental and educational psychology.

The main fields of study associated with their publications include:

  • Computer Science
  • Psychology

The subfields of their work are:

  • Artificial Intelligence
  • Developmental and Educational Psychology
  • Applied Psychology
  • Cognitive Neuroscience
  • Cardiology and Cardiovascular Medicine

The key topics explored in their research are:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Second Language Acquisition and Learning
  • Neurobiology of Language and Bilingualism
  • Language Development and Disorders
  • Multimodal Machine Learning Applications
  • Hate Speech and Cyberbullying Detection

Kenji Sagae has contributed to several recent papers, including:

  • "Neural correlates of word representation vectors in natural language processing models: Evidence from representational similarity analysis of event-related brain potentials" (2021), published in Psychophysiology
  • "COWS-L2H: A corpus of Spanish learner writing" (2020), published in Research in Corpus Linguistics
  • "Tracking Child Language Development With Neural Network Language Models" (2021), published in Frontiers in Psychology
  • "Lexical diversity in an L2 Spanish learner corpus" (2021), published in International Journal of Learner Corpus Research
  • "Beyond NVD: Cybersecurity meets the Semantic Web." (2021), published in New Security Paradigms Workshop

The most frequent publication venues for their work include:

  • arXiv (Cornell University)
  • Research in Corpus Linguistics
  • JMIR Cardio
  • Circulation
  • Psychophysiology

Kenji Sagae has collaborated multiple times with several coauthors; the most frequent collaborators are:

  • Jingwen Zhang
  • Yoshimi Fukuoka
  • Holli A. DeVon
  • Dian Yu
  • Paloma Fernández-Mira

Best Publications

  • YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context

    M. Wollmer;F. Weninger;T. Knaup;B. Schuller

  • Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles

    Kenji Sagae;Jun'ichi Tsujii

  • Dynamic Programming for Linear-Time Incremental Parsing

    Liang Huang;Kenji Sagae

  • Parser Combination by Reparsing

    Kenji Sagae;Alon Lavie

  • Evaluating contributions of natural language parsers to protein–protein interaction extraction

    Yusuke Miyao;Kenji Sagae;Rune Sætre;Takuya Matsuzaki

  • The significance of recall in automatic metrics for MT evaluation

    Alon Lavie;Kenji Sagae;Shyamsundar Jayaraman

  • A Classifier-Based Parser with Linear Run-Time Complexity

    Kenji Sagae;Alon Lavie

  • Computational Analysis of Persuasiveness in Social Multimedia: A Novel Dataset and Multimodal Prediction Approach

    Sunghyun Park;Han Suk Shim;Moitreya Chatterjee;Kenji Sagae

  • Syntactic Features for Protein-Protein Interaction Extraction.

    Rune Sætre;Kenji Sagae;Jun'ichi Tsujii

  • Task-oriented Evaluation of Syntactic Parsers and Their Representations

    Yusuke Miyao;Rune Saetre;Kenji Sagae;Takuya Matsuzaki

  • Automatic Measurement of Syntactic Development in Child Language

    Kenji Sagae;Alon Lavie;Brian MacWhinney

  • Incremental interpretation and prediction of utterance meaning for interactive dialogue

    David DeVault;Kenji Sagae;David R. Traum

  • High-accuracy Annotation and Parsing of CHILDES Transcripts

    Kenji Sagae;Eric Davis;Alon Lavie;Brian MacWhinney

  • Sorting Out the Virtual Patient: How to Exploit Artificial Intelligence, Game Technology and Sound Educational Practices to Create Engaging Role-Playing Simulations

    Thomas Talbot;Kenji Sagae;Bruce Sheffield John;Albert Rizzo

  • SimCoach: an intelligent virtual human system for providing healthcare information and support

    Albert Rizzo;Belinda Lange;John G. Buckwalter;Eric Forbell

  • YouTube Movie Reviews: In, Cross, and Open-domain Sentiment Analysis in an Audiovisual Context

    M. Wöllmer;F. Weninger;T. Knaup;B. Schuller

  • Morphosyntactic annotation of CHILDES transcripts.

    Kenji Sagae;Eric Davis;Alon Lavie;Brian Macwhinney

  • Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates

    Jonas T. Kaplan;Sarah I. Gimbel;Morteza Dehghani;Mary Helen Immordino-Yang;Mary Helen Immordino-Yang

  • Shift-Reduce Dependency DAG Parsing

    Kenji Sagae;Jun'ichi Tsujii

  • An intelligent virtual human system for providing healthcare information and support.

    Albert A. Rizzo;Belinda Lange;John Galen Buckwalter;Eric Forbell

  • Automatic parsing of parental verbal input.

    Kenji Sagae;Brian MacWhinney;Alon Lavie

Frequent Co-Authors

David Traum
David Traum University of Southern California
Alon Lavie
Alon Lavie Carnegie Mellon University
Jun'ichi Tsujii
Jun'ichi Tsujii University of Manchester
Brian MacWhinney
Brian MacWhinney Carnegie Mellon University
Yusuke Miyao
Yusuke Miyao University of Tokyo
Albert Rizzo
Albert Rizzo University of Southern California
Sanjeev Khudanpur
Sanjeev Khudanpur Johns Hopkins University
Murat Saraclar
Murat Saraclar Boğaziçi University
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania

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