World's Best Scientists 2026 revealed!
Chi-Man Vong

Chi-Man Vong

D-Index & Metrics

Computer Science

D-Index
40
Citations
7210
World Ranking
9268
National Ranking
1177

Chi-Man Vong 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 Chi-Man Vong 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: 185 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Chi-Man Vong 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 Chi-Man Vong 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

Chi-Man Vong is affiliated with the University of Macau in China and specializes in computer science with a specific focus on artificial intelligence and computer vision. Their research spans a broad range of subfields including media technology, electrical and electronic engineering, and neurology.

The scientist has contributed extensively to topics related to machine learning and Extreme Learning Machines (ELM), text and document classification technologies, face and expression recognition, advanced neural network applications, advanced image and video retrieval techniques, domain adaptation and few-shot learning, as well as image retrieval and classification techniques.

Chi-Man Vong's frequent co-authors include Chuangquan Chen, Jintao Huang, Jie Du, Shitong Wang, and Pak Kin Wong, reflecting a pattern of collaborative research.

Their work appears predominantly in the following publication venues:

  • arXiv (Cornell University)
  • Neurocomputing
  • IEEE Transactions on Fuzzy Systems
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • IEEE Transactions on Neural Networks and Learning Systems

Some of the recent papers by Chi-Man Vong include:

  • "Novel Efficient RNN and LSTM-Like Architectures: Recurrent and Gated Broad Learning Systems and Their Applications for Text Classification" (2020), published in IEEE Transactions on Cybernetics
  • "Novel up-scale feature aggregation for object detection in aerial images" (2020), published in Neurocomputing
  • "Fuzzy KNN Method With Adaptive Nearest Neighbors" (2020), published in IEEE Transactions on Cybernetics
  • "A Deep Forest-Based Fault Diagnosis Scheme for Electronics-Rich Analog Circuit Systems" (2020), published in IEEE Transactions on Industrial Electronics
  • "Intelligent diagnosis of gastric intestinal metaplasia based on convolutional neural network and limited number of endoscopic images" (2020), published in Computers in Biology and Medicine

Best Publications

  • Representational learning with ELMs for big data

    Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou;Guang-Bin Huang;Chi Man Vong

  • Extreme Learning Machine

    Erik Cambria;Guang-Bin Huang;Liyanaarachchi Lekamalage Chamara Kasun;Hongming Zhou

  • Local Receptive Fields Based Extreme Learning Machine

    Guang-Bin Huang;Zuo Bai;Liyanaarachchi Lekamalage Chamara Kasun;Chi Man Vong

  • SeqViews2SeqLabels: Learning 3D Global Features via Aggregating Sequential Views by RNN With Attention

    Zhizhong Han;Mingyang Shang;Zhenbao Liu;Chi-Man Vong

  • Sparse Bayesian Extreme Learning Machine for Multi-classification

    Jiahua Luo;Chi-Man Vong;Pak-Kin Wong

  • Kernel-Based Multilayer Extreme Learning Machines for Representation Learning

    Chi Man Wong;Chi Man Vong;Pak Kin Wong;Jiuwen Cao

  • Rate-Dependent Hysteresis Modeling and Control of a Piezostage Using Online Support Vector Machine and Relevance Vector Machine

    Pak-Kin Wong;Qingsong Xu;Chi-Man Vong;Hang-Cheong Wong

  • Real-time fault diagnosis for gas turbine generator systems using extreme learning machine

    Pak Kin Wong;Zhixin Yang;Chi Man Vong;Jianhua Zhong

  • 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation

    Zhizhong Han;Honglei Lu;Zhenbao Liu;Chi-Man Vong

  • Prediction of automotive engine power and torque using least squares support vector machines and Bayesian inference

    Chi-Man Vong;Pak-Kin Wong;Yi-Ping Li

  • Modeling and optimization of biodiesel engine performance using kernel-based extreme learning machine and cuckoo search

    Pak Kin Wong;Ka In Wong;Chi Man Vong;Chun Shun Cheung

  • Novel Efficient RNN and LSTM-Like Architectures: Recurrent and Gated Broad Learning Systems and Their Applications for Text Classification

    Jie Du;Chi-Man Vong;C. L. Philip Chen

  • Modeling and optimization of biodiesel engine performance using advanced machine learning methods

    Ka In Wong;Pak Kin Wong;Chun Shun Cheung;Chi Man Vong

  • Capturing High-Discriminative Fault Features for Electronics-Rich Analog System via Deep Learning

    Zhenbao Liu;Zhen Jia;Chi-Man Vong;Shuhui Bu

  • A Rotating Machinery Fault Diagnosis Method Based on Feature Learning of Thermal Images

    Zhen Jia;Zhenbao Liu;Chi-Man Vong;Michael Pecht

  • Case-based Reasoning and Adaptation in Hydraulic Production Machine Design

    C.M. Vong;T.P. Leung;P.K. Wong

  • Engine ignition signal diagnosis with Wavelet Packet Transform and Multi-class Least Squares Support Vector Machines

    C. M. Vong;P. K. Wong

  • Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis

    Pak Kin Wong;Jianhua Zhong;Zhixin Yang;Chi Man Vong

  • Engine idle-speed system modelling and control optimization using artificial intelligence

    P K Wong;L M Tam;K Li;C M Vong

  • A New Framework of Simultaneous-Fault Diagnosis Using Pairwise Probabilistic Multi-Label Classification for Time-Dependent Patterns

    Chi-Man Vong;Pak-Kin Wong;Weng-Fai Ip

  • Fast detection of impact location using kernel extreme learning machine

    Heming Fu;Chi-Man Vong;Pak-Kin Wong;Zhixin Yang

Frequent Co-Authors

Pak Kin Wong
Pak Kin Wong University of Macau
Zhizhong Han
Zhizhong Han Wayne State University
Junwei Han
Junwei Han Northwestern Polytechnical University
Shuhui Bu
Shuhui Bu Northwestern Polytechnical University
C. L. Philip Chen
C. L. Philip Chen South China University of Technology
Rui P. Martins
Rui P. Martins University of Macau
Michael Pecht
Michael Pecht University of Maryland, College Park
Guang-Bin Huang
Guang-Bin Huang Nanyang Technological University
Amaury Lendasse
Amaury Lendasse University of Houston
C.S. Cheung
C.S. Cheung Hong Kong Polytechnic University

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