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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
63
Citations
18327
World Ranking
2730
National Ranking
102

Greg Mori 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 Greg Mori 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: 196 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Greg Mori 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 Greg Mori 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: 63 D-Index — 81st percentile

81% 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

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Greg Mori is affiliated with Simon Fraser University in Canada, with a primary research focus in Computer Science. Their work spans several interconnected subfields, notably Computer Vision and Pattern Recognition, Artificial Intelligence, and Signal Processing, among others.

The scientist's main research topics include:

  • Generative Adversarial Networks and Image Synthesis
  • Anomaly Detection Techniques and Applications
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Domain Adaptation and Few-Shot Learning
  • Time Series Analysis and Forecasting
  • 3D Shape Modeling and Analysis

Among notable recent publications, the following papers stand out:

  • Activity Graph Transformer for Temporal Action Localization (2021, arXiv (Cornell University))
  • House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation (2020, arXiv (Cornell University))
  • Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows (2020, arXiv (Cornell University))
  • D3D-HOI: Dynamic 3D Human-Object Interactions from Videos (2021, arXiv (Cornell University))
  • RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression (2022, arXiv (Cornell University))

Research collaboration is an important aspect of their work, with frequent coauthors including:

  • Megha Nawhal
  • Frederick Tung
  • Ruizhi Deng
  • Hossein Hajimirsadeghi
  • Mengyao Zhai

Publication venues where they have frequently contributed include:

  • arXiv (Cornell University)
  • International Journal of Computer Vision

Greg Mori's body of work demonstrates extensive engagement with generative models, temporal and spatial modeling, and the application of deep learning methods to various complex data types, including video and graph structures.

Best Publications

  • Recognizing objects in adversarial clutter: breaking a visual CAPTCHA

    G. Mori;J. Malik

  • Similarity-Preserving Knowledge Distillation

    Fred Tung;Greg Mori

  • Recovering human body configurations: combining segmentation and recognition

    G. Mori;Xiaofeng Ren;A.A. Efros;J. Malik

  • Detecting Pedestrians by Learning Shapelet Features

    P. Sabzmeydani;G. Mori

  • End-to-End Learning of Action Detection from Frame Glimpses in Videos

    Serena Yeung;Olga Russakovsky;Greg Mori;Li Fei-Fei

  • Action recognition by learning mid-level motion features

    A. Fathi;G. Mori

  • Efficient shape matching using shape contexts

    G. Mori;S. Belongie;J. Malik

  • A Hierarchical Deep Temporal Model for Group Activity Recognition

    Mostafa S. Ibrahim;Srikanth Muralidharan;Zhiwei Deng;Arash Vahdat

  • Estimating Human Body Configurations Using Shape Context Matching

    Greg Mori;Jitendra Malik

  • Recognizing Action at a Distance

    Alexei A. Efros;Alexander C. Berg;Greg Mori;Jitendra Malik

  • Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos

    Serena Yeung;Olga Russakovsky;Olga Russakovsky;Ning Jin;Mykhaylo Andriluka;Mykhaylo Andriluka

  • Matching with Shape Contexts.

    Serge J. Belongie;Greg Mori;Jitendra Malik

  • Human Action Recognition by Semilatent Topic Models

    Yang Wang;G. Mori

  • Guiding model search using segmentation

    G. Mori

  • Recovering 3D human body configurations using shape contexts

    G. Mori;J. Malik

  • Discriminative Latent Models for Recognizing Contextual Group Activities

    Tian Lan;Yang Wang;Weilong Yang;S. N. Robinovitch

  • A discriminative latent model of object classes and attributes

    Yang Wang;Greg Mori

  • Recognizing human actions from still images with latent poses

    Weilong Yang;Yang Wang;Greg Mori

  • Discriminative figure-centric models for joint action localization and recognition

    Tian Lan;Yang Wang;Greg Mori

  • Social roles in hierarchical models for human activity recognition

    Tian Lan;Leonid Sigal;Greg Mori

  • Hierarchical Deep Temporal Models for Group Activity Recognition.

    Mostafa S. Ibrahim;Srikanth Muralidharan;Zhiwei Deng;Arash Vahdat

Frequent Co-Authors

Tian Lan
Tian Lan George Washington University
Leonid Sigal
Leonid Sigal University of British Columbia
Li Fei-Fei
Li Fei-Fei Stanford University
Tarek Sayed
Tarek Sayed University of British Columbia
Jitendra Malik
Jitendra Malik University of California, Berkeley
Mykhaylo Andriluka
Mykhaylo Andriluka Google (United States)
Christian Wolf
Christian Wolf Institut National des Sciences Appliquées de Lyon
Jason J. Corso
Jason J. Corso University of Michigan–Ann Arbor
Nicolas Saunier
Nicolas Saunier Polytechnique Montréal
Daphne Koller
Daphne Koller insitro Inc.

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