World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
6505
World Ranking
7313
National Ranking
973

Hau-San Wong 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 Hau-San Wong 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: 248 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Hau-San Wong 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 Hau-San Wong 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Hau-San Wong is affiliated with the City University of Hong Kong in China. Their research primarily falls under the umbrella of Computer Science, with a strong focus on the subfields of Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Signal Processing, and Cancer Research.

Their scientific contributions are documented extensively, with a particular concentration on topics such as Domain Adaptation and Few-Shot Learning, Generative Adversarial Networks and Image Synthesis, Advanced Image Processing Techniques, Advanced Image and Video Retrieval Techniques, Machine Learning and Extreme Learning Machines (ELM), as well as Video Surveillance and Tracking Methods and Face and Expression Recognition.

Hau-San Wong has published research in a variety of notable venues, including:

  • Pattern Recognition
  • Knowledge-Based Systems
  • IEEE Transactions on Neural Networks and Learning Systems
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering

Among the recent papers authored or co-authored by Wong are:

  • "Incremental Weighted Ensemble Broad Learning System for Imbalanced Data," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "Self-Supervised Graph Completion for Incomplete Multi-View Clustering," 2023, IEEE Transactions on Knowledge and Data Engineering
  • "Simplified Unsupervised Image Translation for Semantic Segmentation Adaptation," 2020, Pattern Recognition
  • "Fast and Effective Active Clustering Ensemble Based on Density Peak," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "Self-Guided Partial Graph Propagation for Incomplete Multiview Clustering," 2023, IEEE Transactions on Neural Networks and Learning Systems

Wong has frequently collaborated with several researchers, with the most common co-authors including:

  • Si Wu
  • Cheng Liu
  • Zhiwen Yu
  • Wenming Cao
  • Qianfen Jiao

Best Publications

  • Model Adaptation: Unsupervised Domain Adaptation Without Source Data

    Rui Li;Qianfen Jiao;Wenming Cao;Hau-San Wong

  • Graph-based consensus clustering for class discovery from gene expression data

    Zhiwen Yu;Hau-San Wong;Hongqiang Wang

  • Incremental Semi-Supervised Clustering Ensemble for High Dimensional Data Clustering

    Zhiwen Yu;Peinan Luo;Jane You;Hau-San Wong

  • Adaptive activation functions in convolutional neural networks

    Sheng Qian;Hua Liu;Cheng Liu;Si Wu

  • Letters: Face and palmprint feature level fusion for single sample biometrics recognition

    Yong-Fang Yao;Xiao-Yuan Jing;Hau-San Wong

  • Rapid and brief communication: Face recognition based on 2D Fisherface approach

    Xiao-Yuan Jing;Hau-San Wong;David Zhang

  • Adaptive Image Processing: A Computational Intelligence Perspective

    Stuart William Perry;Hau-San Wong;Ling Guan

  • A Bayesian Model for Crowd Escape Behavior Detection

    Si Wu;Hau-San Wong;Zhiwen Yu

  • Hybrid Classifier Ensemble for Imbalanced Data

    Kaixiang Yang;Zhiwen Yu;Xin Wen;Wenming Cao

  • Generalized Adjusted Rand Indices for cluster ensembles

    Shaohong Zhang;Hau-San Wong;Ying Shen

  • Characterization of carbon nanotube protein corona by using quantitative proteomics.

    Xiaoning Cai;Rajkumar Ramalingam;Hau San Wong;Jinping Cheng

  • Incremental Weighted Ensemble Broad Learning System For Imbalanced Data

    Kaixiang Yang;Zhiwen Yu;C. L. Philip Chen;Wenming Cao

  • A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

    Xiang Li;Yang Zhang;Hau-San Wong;Zhongfeng Qin

  • Adaptive fuzzy consensus clustering framework for clustering analysis of cancer data

    Zhiwen Yu;Hantao Chen;Jane You;Jiming Liu

  • Dynamic resource allocation via video content and short-term traffic statistics

    Min Wu;R.A. Joyce;Hau-San Wong;Long Guan

  • METHOD AND SYSTEM FOR DYNAMICALLY ALLOTTING NETWORK RESOURCES DURING BIT STREAM TRANSFER IN NETWORK

    Wu Min;Joyce Robert A;Anthony Vetro;Wong Hau-San

  • Self-Supervised Graph Completion for Incomplete Multi-View Clustering

    Unknown

  • Double selection based semi-supervised clustering ensemble for tumor clustering from gene expression profiles

    Zhiwen Yu;Hongsheng Chen;Jane You;Hau-San Wong

  • Clustering by Local Gravitation

    Zhiqiang Wang;Zhiwen Yu;C. L. Philip Chen;Jane You

  • Hybrid clustering solution selection strategy

    Zhiwen Yu;Le Li;Yunjun Gao;Jane You

  • SC³: Triple Spectral Clustering-Based Consensus Clustering Framework for Class Discovery from Cancer Gene Expression Profiles

    Zhiwen Yu;Le Li;Jane You;Hau-San Wong

  • A neural learning approach for adaptive image restoration using a fuzzy model-based network architecture

    Hau-San Wong;Ling Guan

  • Incremental semi-supervised clustering ensemble for high dimensional data clustering

    Zhiwen Yu;Peinan Luo;Si Wu;Guoqiang Han

Frequent Co-Authors

Zhiwen Yu
Zhiwen Yu Northwestern Polytechnical University
Jane You
Jane You Hong Kong Polytechnic University
Ling Guan
Ling Guan Toronto Metropolitan University
Horace H. S. Ip
Horace H. S. Ip City University of Hong Kong
De-Shuang Huang
De-Shuang Huang Tongji University
C. L. Philip Chen
C. L. Philip Chen South China University of Technology
Jiming Liu
Jiming Liu Hong Kong Baptist University
Yong Xu
Yong Xu Harbin Institute of Technology
Xiao-Yuan Jing
Xiao-Yuan Jing Wuhan University
Ronald A. Li
Ronald A. Li University of Hong Kong

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