World's Best Scientists 2026 revealed!
Gene Cheung

Gene Cheung

D-Index & Metrics

Computer Science

D-Index
44
Citations
7691
World Ranking
7600
National Ranking
306

Gene 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 Gene 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: 383 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Gene 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 Gene 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: 44 D-Index — 48th percentile

48% 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

  • 2021 - IEEE Fellow For contributions to graph spectral image processing and interactive video streaming

Overview

Gene Cheung is affiliated with York University in Canada and specializes in research intersecting computer science and engineering. Their scholarly contributions encompass both theoretical and applied aspects within these domains.

Cheung's primary fields of study include:

  • Computer Science
  • Engineering

Within computer science, they concentrate largely on subfields related to:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computational Mechanics
  • Statistical and Nonlinear Physics
  • Radiology, Nuclear Medicine and Imaging

The main topics covered by Cheung's research work are:

  • Advanced Graph Neural Networks
  • Sparse and Compressive Sensing Techniques
  • Complex Network Analysis Techniques
  • Advanced Vision and Imaging
  • Face and Expression Recognition
  • Video Coding and Compression Technologies
  • 3D Shape Modeling and Analysis

Cheung has published extensively, with notable recent papers including:

  • "Sampling Signals on Graphs: From Theory to Applications" (2020) published in IEEE Signal Processing Magazine
  • "Feature Graph Learning for 3D Point Cloud Denoising" (2020) published in IEEE Transactions on Signal Processing
  • "Point Cloud Denoising via Feature Graph Laplacian Regularization" (2020) published in IEEE Transactions on Image Processing
  • "Fast Graph Sampling Set Selection Using Gershgorin Disc Alignment" (2020) published in IEEE Transactions on Signal Processing
  • "Graph Learning Based Head Movement Prediction for Interactive 360 Video Streaming" (2021) published in IEEE Transactions on Image Processing

The frequent publication venues in which Cheung appears are:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Image Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE International Conference on Image Processing (ICIP)

Frequent collaborators in Cheung's work include:

  • Chinthaka Dinesh
  • Cheng Yang
  • Fei Chen
  • Xue Zhang
  • Antonio Ortega

Recognition of Cheung's contributions includes being named an IEEE Fellow in 2021 for work relating to graph spectral image processing and interactive video streaming.

Best Publications

  • Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain

    Jiahao Pang;Gene Cheung

  • Multiresolution Graph Fourier Transform for Compression of Piecewise Smooth Images

    Wei Hu;Gene Cheung;Antonio Ortega;Oscar C. Au

  • Bit allocation for joint source/channel coding of scalable video

    G. Cheung;A. Zakhor

  • Graph-Based Blind Image Deblurring From a Single Photograph

    Yuanchao Bai;Gene Cheung;Xianming Liu;Wen Gao

  • 3D Point Cloud Denoising Using Graph Laplacian Regularization of a Low Dimensional Manifold Model

    Jin Zeng;Gene Cheung;Michael Ng;Jiahao Pang

  • Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures

    G Cheung;A Ortega;Ngai-Man Cheung

  • Medium streaming distribution system

    Gene Cheung;Takeshi Yoshimura

  • Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images

    Xianming Liu;Gene Cheung;Xiaolin Wu;Debin Zhao

  • Sampling Signals on Graphs: From Theory to Applications

    Yuichi Tanaka;Yonina C. Eldar;Antonio Ortega;Gene Cheung

  • Graph Spectral Image Processing

    Gene Cheung;Enrico Magli;Yuichi Tanaka;Michael K. Ng

  • Depth map denoising using graph-based transform and group sparsity

    Wei Hu;Xin Li;Gene Cheung;Oscar Au

  • Optimal routing table design for IP address lookups under memory constraints

    G. Cheung;S. McCanne

  • Graph-Based Blind Image Deblurring From a Single Photograph

    Yuanchao Bai;Gene Cheung;Xianming Liu;Wen Gao

  • Method for assigning a streaming media session to a server in fixed and mobile streaming media systems

    John G. Apostolopoulos;Sujoy Basu;Gene Cheung;Rajendra Kumar

  • Feature Graph Learning for 3D Point Cloud Denoising

    Wei Hu;Xiang Gao;Gene Cheung;Zongming Guo

  • On Dependent Bit Allocation for Multiview Image Coding With Depth-Image-Based Rendering

    Gene Cheung;Vladan Velisavljevic;Antonio Ortega

  • Point Cloud Denoising via Feature Graph Laplacian Regularization

    Chinthaka Dinesh;Gene Cheung;Ivan V. Bajic

  • Distribution of packets among a plurality of nodes

    Gene Cheung

  • Multimedia stream pre-fetching and redistribution in servers to accommodate mobile clients

    Gene Cheung;Tina Wong;Susie J. Wee

  • Distributed source coding techniques for interactive multiview video streaming

    Ngai-Man Cheung;Antonio Ortega;Gene Cheung

  • Method for distributing multiple description streams on servers in fixed and mobile streaming media systems

    John G. Apostolopulos;Sujoy Basu;Gene Cheung;Raj Kumar

  • Graph-based Dequantization of Block-Compressed Piecewise Smooth Images

    Wei Hu;Gene Cheung;Masato Kazui

  • Structured Network Coding and Cooperative Wireless Ad-Hoc Peer-to-Peer Repair for WWAN Video Broadcast

    Xin Liu;G. Cheung;Chen-Nee Chuah

  • Random Walk Graph Laplacian based Smoothness Prior for Soft Decoding of JPEG Images

    Xianming Liu;Gene Cheung;Xiaolin Wu;Debin Zhao

Frequent Co-Authors

Antonio Ortega
Antonio Ortega University of Southern California
Yusheng Ji
Yusheng Ji National Institute of Informatics
Pascal Frossard
Pascal Frossard École Polytechnique Fédérale de Lausanne
Zhi Liu
Zhi Liu University of Electro-Communications
Chen-Nee Chuah
Chen-Nee Chuah University of California, Davis
Bo Shen
Bo Shen Columbia University
Chia-Wen Lin
Chia-Wen Lin National Tsing Hua University
Ngai-Man Cheung
Ngai-Man Cheung Singapore University of Technology and Design
Dinei Florencio
Dinei Florencio Microsoft (United States)
Wei Hu
Wei Hu Nanjing University

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