World's Best Scientists 2026 revealed!
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Computer Science
UK
2026

D-Index & Metrics

Computer Science

D-Index
109
Citations
44546
World Ranking
247
National Ranking
10

Shaogang Gong 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 Shaogang Gong 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 432 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.

Shaogang Gong 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 Shaogang Gong sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 109 D-Index — 98th percentile

98% 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

  • 2026 - Research.com Computer Science in United Kingdom Leader Award
  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Shaogang Gong is affiliated with Queen Mary University of London in the United Kingdom. Their research is situated primarily in the field of Computer Science, featuring a strong focus on Computer Vision and Pattern Recognition. Within this domain, they explore various subfields including Artificial Intelligence, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, and Mechanical Engineering.

The scope of their research topics covers several specific subjects, such as:

  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Video Analysis and Summarization

Shaogang Gong has contributed extensively to scientific literature, with notable recent papers including:

  • "RGB-IR Person Re-identification by Cross-Modality Similarity Preservation" (2020), published in the International Journal of Computer Vision
  • "Semi-Supervised Learning under Class Distribution Mismatch" (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Peer Collaborative Learning for Online Knowledge Distillation" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Tracklet Self-Supervised Learning for Unsupervised Person Re-Identification" (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation" (2021), published in the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The frequent coauthors collaborating with Shaogang Gong include Jiabo Huang, Guile Wu, Xiatian Zhu, Hailin Jin, and Shitong Sun. These collaborations indicate a network centered on computer vision and machine learning research.

Publication venues where Shaogang Gong often publishes include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Pattern Recognition
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • International Journal of Computer Vision

Shaogang Gong has contributed significantly to advancing methods and applications in video surveillance, human action recognition, and multimodal learning, reflecting the integration of diverse computer vision techniques and domain adaptation strategies. The blend of topics and publication outlets underscores a research profile deeply embedded in addressing challenges within visual data interpretation and machine intelligence.

Best Publications

  • Facial expression recognition based on Local Binary Patterns: A comprehensive study

    Caifeng Shan;Shaogang Gong;Peter W. McOwan

  • Harmonious Attention Network for Person Re-identification

    Wei Li;Xiatian Zhu;Shaogang Gong

  • Semantic Autoencoder for Zero-Shot Learning

    Elyor Kodirov;Tao Xiang;Shaogang Gong

  • Person re-identification by probabilistic relative distance comparison

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Reidentification by Relative Distance Comparison

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Person Re-Identification by Support Vector Ranking

    Bryan James Prosser;Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • RGB-Infrared Cross-Modality Person Re-identification

    Ancong Wu;Wei-Shi Zheng;Hong-Xing Yu;Shaogang Gong

  • Person re-identification by video ranking

    Taiqing Wang;Shaogang Gong;Xiatian Zhu;Shengjin Wang

  • Learning a Deep Embedding Model for Zero-Shot Learning

    Li Zhang;Tao Xiang;Shaogang Gong

  • Feature mining for localised crowd counting

    Ke Chen;Chen Change Loy;Shaogang Gong;Tony Xiang

  • Learning a Discriminative Null Space for Person Re-identification

    Li Zhang;Tao Xiang;Shaogang Gong

  • Robust facial expression recognition using local binary patterns

    Caifeng Shan;Shaogang Gong;P.W. McOwan

  • Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-identification

    Jingya Wang;Xiatian Zhu;Shaogang Gong;Wei Li

  • Associating Groups of People

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Transductive Multi-View Zero-Shot Learning

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Shaogang Gong

  • Cumulative Attribute Space for Age and Crowd Density Estimation

    Ke Chen;Shaogang Gong;Tao Xiang;Chen Change Loy

  • Tracking colour objects using adaptive mixture models

    Stephen J. McKenna;Yogesh Raja;Shaogang Gong

  • Recognising action as clouds of space-time interest points

    Matteo Bregonzio;Shaogang Gong;Tao Xiang

  • Person Re-identification by Attributes.

    Ryan Layne;Timothy M. Hospedales;Shaogang Gong

  • Person Re-Identification by Deep Joint Learning of Multi-Loss Classification

    Wei Li;Xiatian Zhu;Shaogang Gong

Frequent Co-Authors

Xiatian Zhu
Xiatian Zhu University of Surrey
Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Chen Change Loy
Chen Change Loy Nanyang Technological University
Stephen J. McKenna
Stephen J. McKenna University of Dundee
Wei-Shi Zheng
Wei-Shi Zheng Sun Yat-sen University
Yanwei Fu
Yanwei Fu Fudan University
Caifeng Shan
Caifeng Shan Nanjing University
Kui Jia
Kui Jia South China University of Technology
Jianhuang Lai
Jianhuang Lai Sun Yat-sen University
Yi-Zhe Song
Yi-Zhe Song University of Surrey

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