World's Best Scientists 2026 revealed!
Award Badge
Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
53
Citations
12355
World Ranking
4786
National Ranking
55

Kaoru Hirota 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 Kaoru Hirota 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: 660 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Kaoru Hirota 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 Kaoru Hirota 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: 53 D-Index — 67th percentile

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

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Kaoru Hirota is affiliated with the Tokyo Institute of Technology in Japan, contributing to research across multiple intersecting fields of computer science, psychology, and engineering. Their work primarily focuses on computational methods related to emotion recognition, human-robot interaction, and pattern recognition technologies.

Their research spans several core fields of study:

  • Computer Science
  • Psychology
  • Engineering

Within these broad fields, they have engaged deeply with subfields including:

  • Computer Vision and Pattern Recognition
  • Experimental and Cognitive Psychology
  • Artificial Intelligence
  • Social Psychology
  • Human-Computer Interaction

The main research topics addressed by Kaoru Hirota include:

  • Emotion and Mood Recognition
  • Face and Expression Recognition
  • Human Pose and Action Recognition
  • Hand Gesture Recognition Systems
  • Robotic Path Planning Algorithms
  • Gait Recognition and Analysis
  • Social Robot Interaction and Human-Robot Interaction (HRI)

Frequent co-authors in their collaborative work include:

  • Luefeng Chen
  • Witold Pedrycz
  • Min Wu
  • Yaping Dai
  • Zhiyang Jia

Kaoru Hirota has published extensively in venues such as:

  • Journal of Advanced Computational Intelligence and Intelligent Informatics
  • IFAC-PapersOnLine
  • 2021 China Automation Congress (CAC)
  • 2022 41st Chinese Control Conference (CCC)
  • IEEE Transactions on Industrial Electronics

Selected recent publications showcase the focus of their research:

  • K-Means Clustering-Based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition in Human-Robot Interaction, 2022, IEEE Transactions on Industrial Electronics
  • A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods, 2023, Neurocomputing
  • Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition, 2020, IEEE Transactions on Affective Computing
  • Coupled Multimodal Emotional Feature Analysis Based on Broad-Deep Fusion Networks in Human-Robot Interaction, 2023, IEEE Transactions on Neural Networks and Learning Systems
  • Path Planning Based on Improved Hybrid A*Algorithm, 2021, Journal of Advanced Computational Intelligence and Intelligent Informatics

Best Publications

  • A flexible representation of quantum images for polynomial preparation, image compression, and processing operations

    Phuc Q. Le;Fangyan Dong;Kaoru Hirota

  • Approximate reasoning by linear rule interpolation and general approximation

    LászlóT T. Kóczy;Kaoru Hirota

  • Granular prototyping in fuzzy clustering

    A. Bargiela;W. Pedrycz;K. Hirota

  • Interpolative reasoning with insufficient evidence in sparse fuzzy rule bases

    László T. Kóczy;Kaoru Hirota

  • Concepts of probabilistic sets

    Kaoru Hirota

  • Size reduction by interpolation in fuzzy rule bases

    L.T. Koczy;K. Hirota

  • Construction of fuzzy models through clustering techniques

    Y. Yoshinari;W. Pedrycz;K. Hirota

  • Watermarking and authentication of quantum images based on restricted geometric transformations

    Abdullah M. Iliyasu;Phuc Q. Le;Fangyan Dong;Kaoru Hirota

  • A Hu moment invariant as a shape circularity measure

    Joviša unić;Kaoru Hirota;Paul L. Rosin

  • An RGB Multi-Channel Representation for Images on Quantum Computers

    Bo Sun;Abdullah M. Iliyasu;Fei Yan;Fangyan Dong

  • Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction

    Luefeng Chen;Mengtian Zhou;Wanjuan Su;Min Wu

  • Design and implementation of a simple dynamical 4-D chaotic circuit with applications in image encryption

    Nestor Tsafack;Jacques Kengne;Bassem Abd-El-Atty;Abdullah M. Iliyasu;Abdullah M. Iliyasu;Abdullah M. Iliyasu

  • Ordering, distance and closeness of fuzzy sets

    László T. Kóczy;Kaoru Hirota

  • Two-layer fuzzy multiple random forest for speech emotion recognition in human-robot interaction

    Luefeng Chen;Wanjuan Su;Yu Feng;Min Wu

  • Strategies for designing geometric transformations on quantum images

    Phuc Q. Le;Abdullahi M. Iliyasu;Fangyan Dong;Kaoru Hirota

  • Anti-swing and positioning control of overhead traveling crane

    Jianqiang Yi;Naoyoshi Yubazaki;Kaoru Hirota

  • Fuzzy computing for data mining

    Unknown

  • Fast solving method of fuzzy relational equation and its application to lossy image compression/reconstruction

    H. Nobuhara;W. Pedrycz;K. Hirota

  • A Multi-Channel Representation for images on quantum computers using the RGBα color space

    Bo Sun;Phuc Q. Le;Abdullah M. Iliyasu;Fei Yan

  • A new fuzzy controller for stabilization of parallel-type double inverted pendulum system

    Jianqiang Yi;Naoyoshi Yubazaki;Kaoru Hirota

  • Upswing and stabilization control of inverted pendulum system based on the SIRMs dynamically connected fuzzy inference model

    Jianqiang Yi;Naoyoshi Yubazaki;Kaoru Hirota

  • Fuzzy relational compression

    K. Hirota;W. Pedrycz

  • Interactive Multiobjective Optimization: A Review of the State-of-the-Art

    Bin Xin;Lu Chen;Jie Chen;Hisao Ishibuchi

Frequent Co-Authors

Witold Pedrycz
Witold Pedrycz University of Alberta
Min Wu
Min Wu China University of Geosciences
Jianqiang Yi
Jianqiang Yi Chinese Academy of Sciences
Abdullah M. Iliyasu
Abdullah M. Iliyasu Prince Sattam Bin Abdulaziz University
Jinhua She
Jinhua She Tokyo University of Technology
Toshio Fukuda
Toshio Fukuda Nagoya University
Ahmed A. Abd El-Latif
Ahmed A. Abd El-Latif Menoufia University
Michio Sugeno
Michio Sugeno Tokyo Institute of Technology
Nikola Kasabov
Nikola Kasabov Auckland University of Technology
Michael Negnevitsky
Michael Negnevitsky University of Tasmania

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Considering a degree in Computer Science opens up many flexible options, especially if you want to study online. A growing number of universities offer best colleges for low gpa applicants, giving more students access to quality education despite challenging academic backgrounds.

Accelerated online programs can help students finish their degrees faster. If you’re eager to launch your technology career efficiently, explore a computer science accelerated program to jump-start your professional journey.

Computer Science also has strong connections with fields like environmental science and engineering. Studying these fields online is possible—discover your options by reading about what can you do with an environmental science degree or comparing the online environmental engineering degree programs available at an affordable cost.

With so many online degrees and career pathways, it’s never been easier to find a program that aligns with your interests, goals, and lifestyle.

Best Scientists Citing Kaoru Hirota

Trending Scientists

Recently Published Articles