World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
6866
World Ranking
9301
National Ranking
119

Ngai-Man Cheung 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 Ngai-Man Cheung 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: 199 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Ngai-Man Cheung 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 Ngai-Man Cheung 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

Ngai-Man Cheung is affiliated with the Singapore University of Technology and Design in Singapore. Their research spans primarily the field of Computer Science, with a strong focus on Computer Vision and Pattern Recognition, and Artificial Intelligence. They have also contributed to topics in Statistical and Nonlinear Physics, Cognitive Neuroscience, and General Social Sciences.

Their work covers several main topics, including:

  • Generative Adversarial Networks and Image Synthesis
  • Adversarial Robustness in Machine Learning
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Anomaly Detection Techniques and Applications
  • Advanced Image and Video Retrieval Techniques

Cheung has published frequently in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Neural Networks and Learning Systems

Recent significant publications include:

  • A Closer Look at Few-shot Image Generation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Multimodal Mutual Information Maximization: A Novel Approach for Unsupervised Deep Cross-Modal Hashing, 2022, IEEE Transactions on Neural Networks and Learning Systems
  • On Evaluating Adversarial Robustness of Large Vision-Language Models, 2023, arXiv (Cornell University)
  • Unsupervised Deep Cross-modality Spectral Hashing, 2020, IEEE Transactions on Image Processing
  • Explanation-Guided Training for Cross-Domain Few-Shot Classification, 2020, arXiv (Cornell University)

Frequent collaborators in their work include Milad Abdollahzadeh, Keshigeyan Chandrasegaran, Alexander Binder, Yunqing Zhao, and Ngoc-Bao Nguyen. These collaborations have resulted in numerous publications over time, reflecting continued joint research efforts.

Best Publications

  • On Data Augmentation for GAN Training

    Ngoc-Trung Tran;Viet-Hung Tran;Ngoc-Bao Nguyen;Trung-Kien Nguyen

  • Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study

    Bach Xuan Tran;Bach Xuan Tran;Giang Thu Vu;Giang Hai Ha;Quan Hoang Vuong

  • Mobile Visual Search

    B Girod;V Chandrasekhar;D M Chen;Ngai-Man Cheung

  • Learning to Hash with Binary Deep Neural Network

    Thanh-Toan Do;Anh-Dzung Doan;Ngai-Man Cheung

  • The stanford mobile visual search data set

    Vijay R. Chandrasekhar;David M. Chen;Sam S. Tsai;Ngai-Man Cheung

  • Adaptive Quantization for Deep Neural Network

    Yiren Zhou;Seyed-Mohsen Moosavi-Dezfooli;Ngai-Man Cheung;Pascal Frossard

  • Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures

    G Cheung;A Ortega;Ngai-Man Cheung

  • Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding

    Linxiao Yang;Ngai-Man Cheung;Jiaying Li;Jun Fang

  • Deepmole: Deep neural networks for skin mole lesion classification

    V. Pomponiu;H. Nejati;N.-M. Cheung

  • On classification of distorted images with deep convolutional neural networks

    Yiren Zhou;Sibo Song;Ngai-Man Cheung

  • DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

    Swee Kiat Lim;Yi Loo;Ngoc-Trung Tran;Ngai-Man Cheung

  • Video Coding on Multicore Graphics Processors

    Nagai-Man Cheung;Xiaopeng Fan;O.C. Au;Man-Cheung Kung

  • Image-based vehicle analysis using deep neural network: A systematic study

    Yiren Zhou;Hossein Nejati;Thanh-Toan Do;Ngai-Man Cheung

  • Enabling Adaptive High-Frame-Rate Video Streaming in Mobile Cloud Gaming Applications

    Jiyan Wu;Chau Yuen;Ngai-Man Cheung;Junliang Chen

  • Attentive Weights Generation for Few Shot Learning via Information Maximization

    Yiluan Guo;Ngai-Man Cheung

  • SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences

    Huu M. Le;Thanh-Toan Do;Tuan Hoang;Ngai-Man Cheung

  • Dist-GAN: An Improved GAN using Distance Constraints

    Ngoc-Trung Tran;Tuan-Anh Bui;Ngai-Man Cheung

  • Mobile product recognition

    Sam S. Tsai;David Chen;Vijay Chandrasekhar;Gabriel Takacs

  • Efficient and Deep Person Re-identification Using Multi-level Similarity

    Yiluan Guo;Ngai-Man Cheung

  • Delay-Constrained High Definition Video Transmission in Heterogeneous Wireless Networks with Multi-Homed Terminals

    Jiyan Wu;Chau Yuen;Ngai-Man Cheung;Junliang Chen

  • Cloud gaming: a green solution to massive multiplayer online games

    Seong-Ping Chuah;Chau Yuen;Ngai-Man Cheung

Frequent Co-Authors

Antonio Ortega
Antonio Ortega University of Southern California
Oscar C. Au
Oscar C. Au Hong Kong University of Science and Technology
Gene Cheung
Gene Cheung York University
Bernd Girod
Bernd Girod Stanford University
Chau Yuen
Chau Yuen Nanyang Technological University
Vijay Chandrasekhar
Vijay Chandrasekhar Agency for Science, Technology and Research
Yuval Elovici
Yuval Elovici Ben-Gurion University of the Negev
Radek Grzeszczuk
Radek Grzeszczuk Microsoft (United States)
Hongzhi Yin
Hongzhi Yin University of Queensland
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology

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