World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
3923
World Ranking
14089
National Ranking
1703

Yi-Dong Shen 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 Yi-Dong Shen 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: 138 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

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

Yi-Dong Shen 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 Yi-Dong Shen 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Yi-Dong Shen is affiliated with the Chinese Academy of Sciences in China and has contributed extensively to the field of computer science, particularly focusing on computer vision and pattern recognition, as well as artificial intelligence. Their research portfolio includes significant work in biomedical engineering, surgery, and automotive engineering, with a primary concentration on the development and application of advanced computational techniques.

The scientist's main areas of study include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Biomedical Engineering
  • Surgery
  • Automotive Engineering

Yi-Dong Shen has addressed several core topics in the field, including:

  • Advanced Image and Video Retrieval Techniques
  • Multimodal Machine Learning Applications
  • Advanced Clustering Algorithms Research
  • Domain Adaptation and Few-Shot Learning
  • Face and Expression Recognition
  • Advanced Neural Network Applications
  • Logic, Reasoning, and Knowledge

Their scholarly output includes publications in prominent venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Neural Networks and Learning Systems
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Image Processing

Several notable papers authored or co-authored by Yi-Dong Shen include:

  • Self-Paced Clustering Ensemble, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Vision-Language Navigation with Random Environmental Mixup, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Unsupervised feature selection with adaptive multiple graph learning, 2020, Pattern Recognition
  • Efficient Token-Guided Image-Text Retrieval With Consistent Multimodal Contrastive Training, 2023, IEEE Transactions on Image Processing
  • Tri-level Robust Clustering Ensemble with Multiple Graph Learning, 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in their research include Chong Liu, Peng Zhou, Liang Du, Xuejun Li, and Yuqi Zhang. The scientist's work has intersected with these co-authors across multiple joint publications, showing a pattern of ongoing academic partnerships.

Best Publications

  • Mining high utility itemsets

    Raymond Chan;Qiang Yang;Yi-Dong Shen

  • Dual-path Convolutional Image-Text Embeddings with Instance Loss

    Zhedong Zheng;Liang Zheng;Michael Garrett;Yi Yang

  • Unsupervised Feature Selection with Adaptive Structure Learning

    Liang Du;Yi-Dong Shen

  • Robust multiple kernel K-means using ℓ 2;1 -norm

    Liang Du;Peng Zhou;Lei Shi;Hanmo Wang

  • Automatic clustering using genetic algorithms

    Yongguo Liu;Xindong Wu;Yidong Shen

  • Person Reidentification via Multi-Feature Fusion With Adaptive Graph Learning

    Runwu Zhou;Xiaojun Chang;Lei Shi;Yi-Dong Shen

  • Robust Spectral Learning for Unsupervised Feature Selection

    Lei Shi;Liang Du;Yi-Dong Shen

  • End-to-End Adversarial-Attention Network for Multi-Modal Clustering

    Runwu Zhou;Yi-Dong Shen

  • Robust Nonnegative Matrix Factorization via Half-Quadratic Minimization

    Liang Du;Xuan Li;Yi-Dong Shen

  • RCAA: Relational Context-Aware Agents for Person Search

    Xiaojun Chang;Po-Yao Huang;Yi-Dong Shen;Xiaodan Liang

  • Implementation of a Linear Tabling Mechanism.

    Neng-Fa Zhou;Yi-Dong Shen;Li-Yan Yuan;Jia-Huai You

  • Objective-oriented utility-based association mining

    Yi-Dong Shen;Zhong Zhang;Qiang Yang

  • Dual-Path Convolutional Image-Text Embedding with Instance Loss

    Zhedong Zheng;Liang Zheng;Michael Garrett;Yi Yang

  • Self-Paced Clustering Ensemble

    Peng Zhou;Liang Du;Xinwang Liu;Yi-Dong Shen

  • Unity Style Transfer for Person Re-Identification

    Chong Liu;Xiaojun Chang;Yi-Dong Shen

  • City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones

    Chong Liu;Yuqi Zhang;Hao Luo;Jiasheng Tang

  • Unsupervised feature selection for balanced clustering

    Peng Zhou;Peng Zhou;Jiangyong Chen;Mingyu Fan;Liang Du

  • Vision-Language Navigation with Random Environmental Mixup

    Chong Liu;Fengda Zhu;Xiaojun Chang;Xiaodan Liang

  • Incremental multi-view spectral clustering

    Peng Zhou;Yi-Dong Shen;Liang Du;Fan Ye

  • Linear tabling strategies and optimizations

    Neng-fa Zhou;Taisuke Sato;Yi-dong Shen

  • Evaluating epistemic negation in answer set programming

    Yi-Dong Shen;Thomas Eiter

  • Unsupervised feature selection with adaptive multiple graph learning

    Peng Zhou;Peng Zhou;Liang Du;Xuejun Li;Yi-Dong Shen

  • Relational click prediction for sponsored search

    Chenyan Xiong;Taifeng Wang;Wenkui Ding;Yidong Shen

Frequent Co-Authors

Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Guilin Qi
Guilin Qi Southeast University
Jeff Z. Pan
Jeff Z. Pan University of Edinburgh
Zhedong Zheng
Zhedong Zheng University of Macau
Xiaodan Liang
Xiaodan Liang Sun Yat-sen University
Xindong Wu
Xindong Wu Hefei University of Technology
Liang Zheng
Liang Zheng Australian National University
Yuhua Qian
Yuhua Qian Shanxi University
Xiaojun Chang
Xiaojun Chang University of Technology Sydney

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