World's Best Scientists 2026 revealed!
Yasutaka Kamei

Yasutaka Kamei

D-Index & Metrics

Computer Science

D-Index
33
Citations
5675
World Ranking
12532
National Ranking
199

Yasutaka Kamei 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 Yasutaka Kamei 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: 208 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Yasutaka Kamei 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 Yasutaka Kamei 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

Yasutaka Kamei is affiliated with Kyushu University in Japan and has contributed significantly to the field of computer science, with a focus on software engineering research and related areas. Their body of work spans numerous subfields including information systems, software, artificial intelligence, computer networks and communications, and computer science applications.

Their research covers a broad array of topics prominently centered on software engineering and its practical challenges. Key areas of study include:

  • Software Engineering Research
  • Software Testing and Debugging Techniques
  • Software Reliability and Analysis Research
  • Software Engineering Techniques and Practices
  • Software System Performance and Reliability
  • Open Source Software Innovations
  • Advanced Malware Detection Techniques

Kamei has authored numerous scientific papers published in various reputable venues. Some notable recent publications include:

  • The Impact of Feature Importance Methods on the Interpretation of Defect Classifiers, 2021, IEEE Transactions on Software Engineering
  • An empirical study on self-admitted technical debt in Dockerfiles, 2022, Empirical Software Engineering
  • An empirical study on self-admitted technical debt in modern code review, 2022, Information and Software Technology
  • The Ghost Commit Problem When Identifying Fix-Inducing Changes: An Empirical Study of Apache Projects, 2021, IEEE Transactions on Software Engineering
  • The Human Side of Fuzzing: Challenges Faced by Developers during Fuzzing Activities, 2023, ACM Transactions on Software Engineering and Methodology

The venues where Kamei frequently publishes include:

  • arXiv (Cornell University)
  • Empirical Software Engineering
  • Zenodo (CERN European Organization for Nuclear Research)
  • ACM Transactions on Software Engineering and Methodology
  • Information and Software Technology

Kamei has collaborated extensively with a number of researchers, with the most frequent co-authors being:

  • Naoyasu Ubayashi
  • Masanari Kondo
  • Yutaro Kashiwa
  • Hiroki Kuramoto
  • Olivier Nourry

The collective work of Yasutaka Kamei reflects a concentrated effort in advancing knowledge around software quality, defect analysis, technical debt, and broader software engineering methodologies. Their multidisciplinary approach incorporates elements of artificial intelligence and software systems performance, contributing to a variety of academic and practical discussions in the field.

Best Publications

  • A large-scale empirical study of just-in-time quality assurance

    Y. Kamei;E. Shihab;B. Adams;A. E. Hassan

  • The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects

    Shane McIntosh;Yasutaka Kamei;Bram Adams;Ahmed E. Hassan

  • An empirical study of the impact of modern code review practices on software quality

    Shane Mcintosh;Yasutaka Kamei;Bram Adams;Ahmed E. Hassan

  • Revisiting common bug prediction findings using effort-aware models

    Yasutaka Kamei;Shinsuke Matsumoto;Akito Monden;Ken-ichi Matsumoto

  • Studying just-in-time defect prediction using cross-project models

    Yasutaka Kamei;Takafumi Fukushima;Shane Mcintosh;Kazuhiro Yamashita

  • Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction

    Shane McIntosh;Yasutaka Kamei

  • An empirical study of just-in-time defect prediction using cross-project models

    Takafumi Fukushima;Yasutaka Kamei;Shane McIntosh;Kazuhiro Yamashita

  • DeepJIT: an end-to-end deep learning framework for just-in-time defect prediction

    Thong Hoang;Hoa Khanh Dam;Yasutaka Kamei;David Lo

  • An empirical study of build maintenance effort

    Shane McIntosh;Bram Adams;Thanh H.D. Nguyen;Yasutaka Kamei

  • Studying re-opened bugs in open source software

    Emad Shihab;Akinori Ihara;Yasutaka Kamei;Walid M. Ibrahim

  • The Effects of Over and Under Sampling on Fault-prone Module Detection

    Y. Kamei;A. Monden;S. Matsumoto;T. Kakimoto

  • Predicting Re-opened Bugs: A Case Study on the Eclipse Project

    Emad Shihab;Akinori Ihara;Yasutaka Kamei;Walid M. Ibrahim

  • Defect Prediction: Accomplishments and Future Challenges

    Yasutaka Kamei;Emad Shihab

  • An analysis of developer metrics for fault prediction

    Shinsuke Matsumoto;Yasutaka Kamei;Akito Monden;Ken-ichi Matsumoto

  • High-impact defects: a study of breakage and surprise defects

    Emad Shihab;Audris Mockus;Yasutaka Kamei;Bram Adams

  • The impact of feature importance methods on the interpretation of defect classifiers

    Gopi Krishnan Rajbahadur;Shaowei Wang;Gustavo Ansaldi;Yasutaka Kamei

  • Characterizing Software Architecture Changes: An Initial Study

    B.J. Williams;J.C. Carver

  • Towards effective AI-powered agile project management

    Hoa Khanh Dam;Truyen Tran;John Grundy;Aditya Ghose

  • The impact of feature reduction techniques on defect prediction models

    Masanari Kondo;Cor Paul Bezemer;Yasutaka Kamei;Ahmed E. Hassan

  • Quantifying programmers' mental workload during program comprehension based on cerebral blood flow measurement: a controlled experiment

    Takao Nakagawa;Yasutaka Kamei;Hidetake Uwano;Akito Monden

  • Revisiting the applicability of the pareto principle to core development teams in open source software projects

    Kazuhiro Yamashita;Shane McIntosh;Yasutaka Kamei;Ahmed E. Hassan

  • SHINOBI: A Tool for Automatic Code Clone Detection in the IDE

    Shinji Kawaguchi;Takanobu Yamashina;Hidetake Uwano;Kyohei Fushida

Frequent Co-Authors

Kenichi Matsumoto
Kenichi Matsumoto Nara Institute of Science and Technology
Ahmed E. Hassan
Ahmed E. Hassan Queen's University
Shane McIntosh
Shane McIntosh McGill University
Bram Adams
Bram Adams Queen's University
Emad Shihab
Emad Shihab Concordia University
Meiyappan Nagappan
Meiyappan Nagappan University of Waterloo
Audris Mockus
Audris Mockus University of Tennessee at Knoxville
Jacky Keung
Jacky Keung City University of Hong Kong
Abram Hindle
Abram Hindle University of Alberta
Éric Tanter
Éric Tanter University of Chile

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