World's Best Scientists 2026 revealed!
Kazuya Takeda

Kazuya Takeda

Award Badge
Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
53
Citations
12181
World Ranking
4794
National Ranking
56

Kazuya Takeda 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 Kazuya Takeda 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: 559 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Kazuya Takeda 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 Kazuya Takeda 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

Kazuya Takeda is affiliated with Nagoya University in Japan and has contributed extensively to research primarily in the fields of Computer Science and Engineering. Their work spans numerous subfields, with a significant focus on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Signal Processing, and Economics and Econometrics.

The scientist's research covers several main topics including Autonomous Vehicle Technology and Safety, Sports Analytics and Performance, Anomaly Detection Techniques and Applications, Human-Automation Interaction and Safety, Sports Performance and Training, and Music and Audio Processing. This variety underscores a multidisciplinary approach to their studies.

Their recent papers include:

  • "A Survey of Autonomous Driving: Common Practices and Emerging Technologies" (2020), published in IEEE Access
  • "Perception and sensing for autonomous vehicles under adverse weather conditions: A survey" (2023), published in ISPRS Journal of Photogrammetry and Remote Sensing
  • "Performance Analysis of 10 Models of 3D LiDARs for Automated Driving" (2020), published in IEEE Access
  • "Extracting Human-Like Driving Behaviors From Expert Driver Data Using Deep Learning" (2020), published in IEEE Transactions on Vehicular Technology
  • "Distracted driving detection based on the fusion of deep learning and causal reasoning" (2022), published in Information Fusion

Kazuya Takeda collaborates frequently with a number of co-authors, including Alexander Carballo, Keisuke Fujii, Eijiro Takeuchi, and Tomoki Toda. These collaborations have contributed to a substantial body of work in their research areas.

Their publications appear mainly in venues such as arXiv (Cornell University), IEEE Access, Sensors, the 2022 IEEE Intelligent Vehicles Symposium (IV), and the Journal of Robotics and Mechatronics. The distribution of publications in these venues reflects a focus on automotive technology as well as broader engineering and computer science inquiries.

Best Publications

  • A Survey of Autonomous Driving: Common Practices and Emerging Technologies

    Ekim Yurtsever;Jacob Lambert;Alexander Carballo;Kazuya Takeda

  • An Open Approach to Autonomous Vehicles

    Shinpei Kato;Eijiro Takeuchi;Yoshio Ishiguro;Yoshiki Ninomiya

  • Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification

    C. Miyajima;Y. Nishiwaki;K. Ozawa;T. Wakita

  • ATR Japanese speech database as a tool of speech recognition and synthesis

    Akira Kurematsu;Kazuya Takeda;Yoshinori Sagisaka;Shigeru Katagiri

  • JNAS: Japanese speech corpus for large vocabulary continuous speech recognition research

    Katunobu Itou;Mikio Yamamoto;Kazuya Takeda;Toshiyuki Takezawa

  • Speaker-Dependent WaveNet Vocoder.

    Akira Tamamori;Tomoki Hayashi;Kazuhiro Kobayashi;Kazuya Takeda

  • Evaluation of blind signal separation method using directivity pattern under reverberant conditions

    S. Kurita;H. Saruwatari;S. Kajita;K. Takeda

  • Blind source separation combining independent component analysis and beamforming

    Hiroshi Saruwatari;Satoshi Kurita;Kazuya Takeda;Fumitada Itakura

  • Analysis and recognition of whispered speech

    Taisuke Ito;Kazuya Takeda;Fumitada Itakura

  • Driver Identification Using Driving Behavior Signals

    Toshihiro Wakita;Koji Ozawa;Chiyomi Miyajima;Kei Igarashi

  • Espnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit

    Tomoki Hayashi;Ryuichi Yamamoto;Katsuki Inoue;Takenori Yoshimura

  • Free software toolkit for Japanese large vocabulary continuous speech recognition

    Tatsuya Kawahara;Akinobu Lee;Tetsunori Kobayashi;Kazuya Takeda

  • A new phonetic tied-mixture model for efficient decoding

    A. Lee;T. Kawahara;K. Takeda;K. Shikano

  • Driving Profile Modeling and Recognition Based on Soft Computing Approach

    A. Wahab;Chai Quek;Chin Keong Tan;K. Takeda

  • Exploring multi-channel features for denoising-autoencoder-based speech enhancement

    Shoko Araki;Tomoki Hayashi;Marc Delcroix;Masakiyo Fujimoto

  • The Design of the Newspaper-Based Japanese Large Vocabulary Continuous Speech Recognition Corpus

    Katunobu Itou;Mikio Yamamoto;Kazuya Takeda;Toshiyuki Takezawa

  • Estimation of HRTFs on the horizontal plane using physical features

    Takanori Nishino;Naoya Inoue;Kazuya Takeda;Fumitada Itakura

  • Multipoint Measuring System for Video and Sound - 100-camera and microphone system

    T. Fujii;K. Mori;K. Takeda;K. Mase

  • An investigation of multi-speaker training for wavenet vocoder

    Tomoki Hayashi;Akira Tamamori;Kazuhiro Kobayashi;Kazuya Takeda

  • Duration-Controlled LSTM for Polyphonic Sound Event Detection

    Tomoki Hayashi;Shinji Watanabe;Tomoki Toda;Takaaki Hori

  • Driver Modeling Based on Driving Behavior and Its Evaluation in Driver

    Chiyomi Miyajima;Yoshihiro Nishiwaki;Koji Ozawa;Toshihiro Wakita

Frequent Co-Authors

Tomoki Toda
Tomoki Toda Nagoya University
Kiyohiro Shikano
Kiyohiro Shikano Nara Institute of Science and Technology
Satoshi Nakamura
Satoshi Nakamura Nara Institute of Science and Technology
Seiichi Yamamoto
Seiichi Yamamoto Doshisha University
Hiroshi Saruwatari
Hiroshi Saruwatari University of Tokyo
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Tatsuya Kawahara
Tatsuya Kawahara Kyoto University
Gerhard Schmidt
Gerhard Schmidt Kiel University
Hirokazu Kameoka
Hirokazu Kameoka NTT (Japan)
Toshiaki Fujii
Toshiaki Fujii Nagoya University

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

Exploring computer science in the USA often opens doors to a variety of related online degrees and fast-track career paths. Many students are searching for flexible options, such as the cheapest mba online, to expand their technical expertise with business leadership skills. This combination can make candidates more attractive in both tech and managerial roles.

For those eager to advance quickly, there are also one year graduate programs that offer intensive, focused study. These programs can fast-track your entry into specialized industries or help you pivot your career efficiently.

Many students look for the fastest degree to get that leads to high-paying jobs. Accelerated online programs in fields related to computer science allow you to quickly build essential skills and certifications, making it easier to land competitive positions.

Emerging technologies like artificial intelligence are also in high demand. If you’re interested in specializing, you might consider targeted programs through the degrees in ai page. These affordable online degrees prepare students for cutting-edge careers in one of tech’s fastest-growing sectors.

Best Scientists Citing Kazuya Takeda

Trending Scientists

Recently Published Articles