World's Best Scientists 2026 revealed!
Richard S. Zemel

Richard S. Zemel

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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
75
Citations
51239
World Ranking
1368
National Ranking
47

Richard S. Zemel 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 Richard S. Zemel 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Richard S. Zemel 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 Richard S. Zemel 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: 75 D-Index — 90th percentile

90% 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

Richard S. Zemel is affiliated with the University of Toronto in Canada and has contributed extensively to research in computer science, with a focus on artificial intelligence and related subfields.

The research work spans multiple areas within computer science, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Language and Linguistics

Key research topics covered in their publications include:

  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Adversarial Robustness in Machine Learning
  • Multimodal Machine Learning Applications
  • Topic Modeling
  • Anomaly Detection Techniques and Applications
  • Natural Language Processing Techniques

Richard S. Zemel has published in a variety of venues, with a significant number of contributions to:

  • arXiv (Cornell University)
  • Nature Machine Intelligence
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Computer
  • Journal of Vision

Notable recent papers include:

  • Shortcut learning in deep neural networks, 2020, Nature Machine Intelligence
  • Exploring Models and Data for Image Question Answering, 2024, arXiv (Cornell University)
  • Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data, 2020, arXiv (Cornell University)
  • Variational Model Inversion Attacks, 2022, arXiv (Cornell University)
  • Deep Ensembles Work, But Are They Necessary?, 2022, arXiv (Cornell University)

The researcher has frequently collaborated with a core group of co-authors, notably:

  • Thomas P. Zollo
  • Elliot Creager
  • Ninareh Mehrabi
  • Kai-Wei Chang
  • Aram Galstyan

Best Publications

  • Prototypical Networks for Few-shot Learning

    Jake Snell;Kevin Swersky;Richard S. Zemel

  • Siamese Neural Networks for One-shot Image Recognition

    Gregory Koch;Richard Zemel;Ruslan Salakhutdinov

  • Fairness through awareness

    Cynthia Dwork;Moritz Hardt;Toniann Pitassi;Omer Reingold

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • Gated Graph Sequence Neural Networks.

    Yujia Li;Daniel Tarlow;Marc Brockschmidt;Richard S. Zemel

  • Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books

    Yukun Zhu;Ryan Kiros;Rich Zemel;Ruslan Salakhutdinov

  • Skip-thought vectors

    Ryan Kiros;Yukun Zhu;Ruslan Salakhutdinov;Richard S. Zemel

  • Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

    Ryan Kiros;Ruslan Salakhutdinov;Richard S. Zemel

  • The helmholtz machine

    Peter Dayan;Geoffrey E. Hinton;Radford M. Neal;Richard S. Zemel

  • Understanding the effective receptive field in deep convolutional neural networks

    Wenjie Luo;Yujia Li;Raquel Urtasun;Richard S. Zemel

  • Shortcut learning in deep neural networks

    Robert Geirhos;Jörn-Henrik Jacobsen;Claudio Michaelis;Richard S. Zemel

  • Autoencoders, Minimum Description Length and Helmholtz Free Energy

    Geoffrey E. Hinton;Richard S. Zemel

  • Multiscale conditional random fields for image labeling

    Xuming He;R.S. Zemel;M.A. Carreira-Perpinan

  • Information processing with population codes

    Alexandre Pouget;Peter Dayan;Richard Zemel

  • Generative Moment Matching Networks

    Yujia Li;Kevin Swersky;Rich Zemel;Rich Zemel

  • Meta-Learning for Semi-Supervised Few-Shot Classification

    Eleni Triantafillou;Hugo Larochelle;Jake Snell;Josh Tenenbaum

  • Exploring models and data for image question answering

    Mengye Ren;Ryan Kiros;Richard S. Zemel

  • Meta-Learning for Semi-Supervised Few-Shot Classification

    Mengye Ren;Eleni Triantafillou;Sachin Ravi;Jake Snell

  • INFERENCE AND COMPUTATION WITH POPULATION CODES

    Alexandre Pouget;Peter Dayan;Richard S. Zemel

  • Learning and Incorporating Top-Down Cues in Image Segmentation

    Xuming He;Richard S. Zemel;Debajyoti Ray

  • The Variational Fair Autoencoder

    Christos Louizos;Kevin Swersky;Yujia Li;Max Welling;Max Welling;Max Welling

  • Causal Effect Inference with Deep Latent-Variable Models

    Christos Louizos;Uri Shalit;Joris M. Mooij;David A. Sontag

  • Advances in Neural Information Processing Systems 5

    Richard S Zemel;Christopher Williams;Michael C Mozer

Frequent Co-Authors

Raquel Urtasun
Raquel Urtasun University of Toronto
Renjie Liao
Renjie Liao University of British Columbia
Kevin Swersky
Kevin Swersky Google (United States)
Peter Dayan
Peter Dayan Max Planck Institute for Biological Cybernetics
Toniann Pitassi
Toniann Pitassi Columbia University
Max Welling
Max Welling University of Amsterdam
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto
Michael C. Mozer
Michael C. Mozer Google (United States)
Ryan P. Adams
Ryan P. Adams Princeton University
Ruslan Salakhutdinov
Ruslan Salakhutdinov Carnegie Mellon University

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