World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
71
Citations
26642
World Ranking
1745
National Ranking
237

James T. Kwok 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 James T. Kwok 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: 277 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

James T. Kwok 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 James T. Kwok 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: 71 D-Index — 88th percentile

88% 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

  • 2017 - IEEE Fellow For contributions to computational algorithms for kernel methods

Overview

James T. Kwok is affiliated with the Hong Kong University of Science and Technology in China. Their main field of study is Computer Science, with an emphasis on Artificial Intelligence. Their research spans various subfields including Computer Vision and Pattern Recognition, Signal Processing, Media Technology, and Computational Mechanics.

The core topics covered in James T. Kwok's work include:

  • Domain Adaptation and Few-Shot Learning
  • Natural Language Processing Techniques
  • Topic Modeling
  • Machine Learning and Algorithms
  • Advanced Graph Neural Networks
  • Adversarial Robustness in Machine Learning
  • Advanced Image and Video Retrieval Techniques

James T. Kwok has collaborated frequently with several co-authors, including:

  • Jie Gui
  • Quanming Yao
  • Yuan Yan Tang
  • Weisen Jiang
  • Lanqing Hong

The scientist's recent papers include:

  • "Generalizing from a Few Examples," 2020, ACM Computing Surveys
  • "A Survey of Label-noise Representation Learning: Past, Present and Future," 2020, arXiv (Cornell University)
  • "Time Series Anomaly Detection with Multiresolution Ensemble Decoding," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "A Survey on Time-Series Pre-Trained Models," 2024, IEEE Transactions on Knowledge and Data Engineering
  • "MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models," 2023, arXiv (Cornell University)

James T. Kwok has published extensively in several academic venues. Most frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Information Forensics and Security
  • IEEE Transactions on Circuits and Systems for Video Technology

Additionally, James T. Kwok has contributed to book publications, including:

  • Neural Information Processing, published by Springer Science+Business Media, 2020

James T. Kwok was recognized as an IEEE Fellow in 2017 for contributions to computational algorithms for kernel methods.

Best Publications

  • Domain Adaptation via Transfer Component Analysis

    Sinno Jialin Pan;Ivor W Tsang;James T Kwok;Qiang Yang

  • Generalizing from a Few Examples: A Survey on Few-shot Learning

    Yaqing Wang;Quanming Yao;James T. Kwok;Lionel M. Ni

  • Core Vector Machines: Fast SVM Training on Very Large Data Sets

    Ivor W. Tsang;James T. Kwok;Pak-Ming Cheung

  • The pre-image problem in kernel methods

    J.T.-Y. Kwok;I.W.-H. Tsang

  • Transfer learning via dimensionality reduction

    Sinno Jialin Pan;James T. Kwok;Qiang Yang

  • Constructive algorithms for structure learning in feedforward neural networks for regression problems

    Tin-Yau Kwok;Dit-Yan Yeung

  • Combination of images with diverse focuses using the spatial frequency

    Shutao Li;Shutao Li;James Tin-Yau Kwok;Yaonan Wang

  • Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images

    Shutao Li;Shutao Li;James T Kwok;Yaonan Wang

  • Improved Nyström low-rank approximation and error analysis

    Kai Zhang;Ivor W. Tsang;James T. Kwok

  • Multifocus image fusion using artificial neural networks

    Shutao Li;James T. Kwok;Yaonan Wang

  • Mining customer product ratings for personalized marketing

    Kwok-Wai Cheung;James T. Kwok;Martin H. Law;Kwok-Ching Tsui

  • Asynchronous Distributed ADMM for Consensus Optimization

    Ruiliang Zhang;James Kwok

  • Multi-Label Learning with Global and Local Label Correlation

    Yue Zhu;James T. Kwok;Zhi-Hua Zhou

  • Maximum Margin Clustering Made Practical

    Kai Zhang;I.W. Tsang;J.T. Kwok

  • Objective functions for training new hidden units in constructive neural networks

    Tin-Yan Kwok;Dit-Yan Yeung

  • Texture classification using the support vector machines

    Shutao Li;Shutao Li;James T. Kwok;Hailong Zhu;Hailong Zhu;Yaonan Wang

  • Simpler core vector machines with enclosing balls

    Ivor W. Tsang;Andras Kocsor;James T. Kwok

  • A novel incremental principal component analysis and its application for face recognition

    Haitao Zhao;Pong Chi Yuen;J.T. Kwok

  • Generalized Core Vector Machines

    I.W.H. Tsang;J.T.Y. Kwok;J.A. Zurada

  • The evidence framework applied to support vector machines

    James Tin-Yau Kwok

Frequent Co-Authors

Ivor W. Tsang
Ivor W. Tsang Agency for Science, Technology and Research
Shutao Li
Shutao Li Hunan University
Dit-Yan Yeung
Dit-Yan Yeung Hong Kong University of Science and Technology
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Bao-Liang Lu
Bao-Liang Lu Shanghai Jiao Tong University
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Lionel M. Ni
Lionel M. Ni Hong Kong University of Science and Technology (Guangzhou)
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Changshui Zhang
Changshui Zhang Tsinghua University
Sinno Jialin Pan
Sinno Jialin Pan Chinese University of Hong Kong

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