World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
10816
World Ranking
9088
National Ranking
126

Shin'ichi Satoh 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 Shin'ichi Satoh 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: 437 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Shin'ichi Satoh 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 Shin'ichi Satoh 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

Shin'ichi Satoh is affiliated with the National Institute of Informatics in Japan. Their research focuses primarily on engineering, with a significant emphasis on aerospace engineering and control systems. Their work spans multiple subfields including aerospace engineering, control and systems engineering, astronomy and astrophysics, mechanical engineering, and civil and structural engineering.

The scientist's main topics of research include:

  • Spacecraft Dynamics and Control
  • Space Satellite Systems and Control
  • Astro and Planetary Science
  • Adaptive Control of Nonlinear Systems
  • Magnetic Bearings and Levitation Dynamics
  • Inertial Sensor and Navigation
  • Tribology and Lubrication Engineering

Among the frequent publication venues for their work are:

  • Acta Astronautica
  • Advances in Space Research
  • Transactions of the JSME (in Japanese)
  • TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES AEROSPACE TECHNOLOGY JAPAN
  • AEROSPACE TECHNOLOGY JAPAN THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES

Selected recent papers by Shin'ichi Satoh include:

  • Attitude control for spacecraft using pyramid-type variable-speed control moment gyros, 2020, Acta Astronautica
  • Feedback attitude control of spacecraft using two single gimbal control moment gyros, 2021, Advances in Space Research
  • Optimal constellation design based on satellite ground tracks for Earth observation missions, 2023, Acta Astronautica
  • Analysis of a distant retrograde orbit in the Hill three-body problem, 2020, Acta Astronautica
  • Attitude control experiment of a spinning spacecraft using only magnetic torquers, 2023, Advances in Space Research

The scientist has collaborated frequently with other researchers, including:

  • Katsuhiko Yamada
  • Yasuhiro Shoji
  • Tomoya Hattori
  • Yuta Imoto

Best Publications

  • The SR-tree: an index structure for high-dimensional nearest neighbor queries

    Norio Katayama;Shin'ichi Satoh

  • Embedding Watermarks into Deep Neural Networks

    Yusuke Uchida;Yuki Nagai;Shigeyuki Sakazawa;Shin'ichi Satoh

  • Learning to Reduce Dual-Level Discrepancy for Infrared-Visible Person Re-Identification

    Zhixiang Wang;Zheng Wang;Yinqiang Zheng;Yung-Yu Chuang

  • SpotFake: A Multi-modal Framework for Fake News Detection

    Shivangi Singhal;Rajiv Ratn Shah;Tanmoy Chakraborty;Ponnurangam Kumaraguru

  • Name-It: naming and detecting faces in news videos

    S. Satoh;Y. Nakamura;T. Kanade

  • Proceedings of the 20th ACM international conference on Multimedia

    Noboru Babaguchi;Kiyoharu Aizawa;John Smith;Shin'ichi Satoh

  • Video OCR: indexing digital new libraries by recognition of superimposed captions

    Toshio Sato;Takeo Kanade;Ellen K. Hughes;Michael A. Smith

  • Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge

    Ryota Hinami;Tao Mei;Shin'ichi Satoh

  • Name-It: association of face and name in video

    S. Satoh;T. Kanade

  • Digital watermarking for deep neural networks

    Yuki Nagai;Yusuke Uchida;Shigeyuki Sakazawa;Shin’ichi Satoh

  • MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction.

    Changhee Han;Leonardo Rundo;Kohei Murao;Tomoyuki Noguchi

  • Advances in Multimedia Information Processing - Pcm 2004

    Kiyoharu Aizawa;Yuichi Nakamura;Shin’ichi Satoh

  • Faster R-CNN Features for Instance Search

    Amaia Salvador;Xavier Giro-i-Nieto;Ferran Marques;Shin'ichi Satoh

  • Cooking navi: assistant for daily cooking in kitchen

    Reiko Hamada;Jun Okabe;Ichiro Ide;Shin'ichi Satoh

  • Illumination-Adaptive Person Re-Identification

    Zelong Zeng;Zhixiang Wang;Zheng Wang;Yinqiang Zheng

  • Guidance and Evaluation: Semantic-Aware Image Inpainting for Mixed Scenes

    Liang Liao;Jing Xiao;Zheng Wang;Chia-Wen Lin

  • Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification.

    Zheng Wang;Mang Ye;Fan Yang;Xiang Bai

  • Image Inpainting Guided by Coherence Priors of Semantics and Textures

    Liang Liao;Jing Xiao;Zheng Wang;Chia-Wen Lin

  • Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images

    Changhee Han;Kohei Murao;Tomoyuki Noguchi;Yusuke Kawata

  • Comparative evaluation of face sequence matching for content-based video access

    S. Satoh

  • Image sentiment analysis using latent correlations among visual, textual, and sentiment views

    Marie Katsurai;Shin'ichi Satoh

  • Building compact local pairwise codebook with joint feature space clustering

    Nobuyuki Morioka;Shin'ichi Satoh

Frequent Co-Authors

Chia-Wen Lin
Chia-Wen Lin National Tsing Hua University
Jianping Fan
Jianping Fan University of North Carolina at Charlotte
Hiroyoshi Hidaka
Hiroyoshi Hidaka D. Western Therapeutics Institute (Japan)
Jian Zhang
Jian Zhang University of Technology Sydney
Li Cheng
Li Cheng Hong Kong Polytechnic University
Yinqiang Zheng
Yinqiang Zheng National Institute of Informatics
Alexander G. Hauptmann
Alexander G. Hauptmann Carnegie Mellon University
Yusuke Miyao
Yusuke Miyao University of Tokyo
William Ribarsky
William Ribarsky University of North Carolina at Charlotte
Yi Yu
Yi Yu Hiroshima University

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