World's Best Scientists 2026 revealed!
Tetsuya Ogata

Tetsuya Ogata

D-Index & Metrics

Computer Science

D-Index
40
Citations
6714
World Ranking
9311
National Ranking
135

Tetsuya Ogata 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 Tetsuya Ogata 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: 434 publications — 89th percentile

89% of scientists in this discipline score the same or lower.

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

Tetsuya Ogata 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 Tetsuya Ogata 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Tetsuya Ogata is affiliated with Waseda University in Japan. Their research spans multiple fields of engineering and computer science, focusing on areas such as control and systems engineering, computer vision and pattern recognition, cognitive neuroscience, artificial intelligence, and biomedical engineering.

The primary topics covered in Ogata's work include:

  • Robot Manipulation and Learning
  • Robotics and Automated Systems
  • Tactile and Sensory Interactions
  • Reinforcement Learning in Robotics
  • Soft Robotics and Applications
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition

Ogata has published extensively, with key recent papers including:

  • Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control (2022), Science Robotics
  • Multi-Fingered In-Hand Manipulation With Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors (2022), IEEE Robotics and Automation Letters
  • Point Cloud Pre-training with Natural 3D Structures (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions (2023), IEEE Robotics and Automation Letters
  • Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder (2020), Frontiers in Psychiatry

Frequent co-authors collaborating with Ogata include:

  • Hiroki Mori
  • Hiroshi Ito
  • Kanata Suzuki
  • Shigeki Sugano
  • Hideyuki Ichiwara

The scientist regularly publishes in venues such as:

  • arXiv (Cornell University)
  • The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
  • IEEE Robotics and Automation Letters
  • Advanced Robotics
  • 2022 IEEE/SICE International Symposium on System Integration (SII)

Best Publications

  • Audio-visual speech recognition using deep learning

    Kuniaki Noda;Yuki Yamaguchi;Kazuhiro Nakadai;Hiroshi G. Okuno

  • Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning

    Pin-Chu Yang;Kazuma Sasaki;Kanata Suzuki;Kei Kase

  • An Efficient Hybrid Music Recommender System Using an Incrementally Trainable Probabilistic Generative Model

    K. Yoshii;M. Goto;K. Komatani;T. Ogata

  • Multimodal integration learning of robot behavior using deep neural networks

    Kuniaki Noda;Hiroaki Arie;Yuki Suga;Tetsuya Ogata

  • Hybrid collaborative and content-based music recommendation using probabilistic model with latent user preferences

    Kazuyoshi Yoshii;Masataka Goto;Kazunori Komatani;Tetsuya Ogata

  • Symbol emergence in robotics: a survey

    Tadahiro Taniguchi;Takayuki Nagai;Tomoaki Nakamura;Naoto Iwahashi

  • Lipreading using convolutional neural network

    Kuniaki Noda;Yuki Yamaguchi;Kazuhiro Nakadai;Hiroshi G. Okuno

  • Sound source localization using deep learning models

    Nelson Yalta;Kazuhiro Nakadai;Tetsuya Ogata

  • Instrument identification in polyphonic music: feature weighting to minimize influence of sound overlaps

    Tetsuro Kitahara;Masataka Goto;Kazunori Komatani;Tetsuya Ogata

  • Tactile object recognition using deep learning and dropout

    Alexander Schmitz;Yusuke Bansho;Kuniaki Noda;Hiroyasu Iwata

  • Automatic Synchronization between Lyrics and Music CD Recordings Based on Viterbi Alignment of Segregated Vocal Signals

    H. Fujihara;M. Goto;J. Ogata;K. Komatani

  • Enhanced Robot Speech Recognition Based on Microphone Array Source Separation and Missing Feature Theory

    S. Yamamoto;J.-M. Valin;J.-M. Valin;K. Nakadai;J. Rouat

  • Emotional Communication Robot: WAMOEBA-2R - Emotion Model and Evaluation Experiments -

    Tetsuya Ogata;Shigeki Sugano

  • Singer identification based on accompaniment sound reduction and reliable frame selection

    Hiromasa Fujihara;Tetsuro Kitahara;Masataka Goto;Kazunori Komatani

  • Emergence of mind in robots for human interface - research methodology and robot model

    S. Sugano;T. Ogata

  • Real-Time Robot Audition System That Recognizes Simultaneous Speech in The Real World

    Shun'ichi Yamamoto;Kazuhiro Nakadai;Mikio Nakano;Hiroshi Tsujino

  • Two-way translation of compound sentences and arm motions by recurrent neural networks

    T. Ogata;M. Murase;Jun Tani;K. Komatani

  • Automatic Chord Transcription with Concurrent Recognition of Chord Symbols and Boundaries.

    Takuya Yoshioka;Tetsuro Kitahara;Kazunori Komatani;Tetsuya Ogata

  • Emotional communication between humans and the autonomous robot which has the emotion model

    T. Ogata;S. Sugano

  • A biped robot that keeps steps in time with musical beats while listening to music with its own ears

    K. Yoshii;K. Nakadai;T. Torii;Y. Hasegawa

Frequent Co-Authors

Hiroshi G. Okuno
Hiroshi G. Okuno Waseda University
Shigeki Sugano
Shigeki Sugano Waseda University
Kazuhiro Nakadai
Kazuhiro Nakadai Tokyo Institute of Technology
Jun Tani
Jun Tani Okinawa Institute of Science and Technology
Masataka Goto
Masataka Goto National Institute of Advanced Industrial Science and Technology
Angelo Cangelosi
Angelo Cangelosi University of Manchester
Dieter Fox
Dieter Fox University of Washington
Gordon Cheng
Gordon Cheng Technical University of Munich
Chenguang Yang
Chenguang Yang University of Liverpool

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