2026 Richard S. Zemel: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	75	1368	1325	47	42	236	51239

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

5538
Citations
Siamese Neural Networks for One-shot Image Recognition

Gregory Koch;Richard Zemel;Ruslan Salakhutdinov

3697
Citations
Fairness through awareness

Cynthia Dwork;Moritz Hardt;Toniann Pitassi;Omer Reingold

3559
Citations
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

3024
Citations
Gated Graph Sequence Neural Networks.

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

2673
Citations
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books

Yukun Zhu;Ryan Kiros;Rich Zemel;Ruslan Salakhutdinov

2302
Citations
Skip-thought vectors

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

2155
Citations
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

Ryan Kiros;Ruslan Salakhutdinov;Richard S. Zemel

1966
Citations
The helmholtz machine

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

1763
Citations
Understanding the effective receptive field in deep convolutional neural networks

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

1601
Citations
Shortcut learning in deep neural networks

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

1594
Citations
Autoencoders, Minimum Description Length and Helmholtz Free Energy

Geoffrey E. Hinton;Richard S. Zemel

1466
Citations
Multiscale conditional random fields for image labeling

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

1296
Citations
Information processing with population codes

Alexandre Pouget;Peter Dayan;Richard Zemel

983
Citations
Generative Moment Matching Networks

Yujia Li;Kevin Swersky;Rich Zemel;Rich Zemel

686
Citations
Meta-Learning for Semi-Supervised Few-Shot Classification

Eleni Triantafillou;Hugo Larochelle;Jake Snell;Josh Tenenbaum

668
Citations
Exploring models and data for image question answering

Mengye Ren;Ryan Kiros;Richard S. Zemel

665
Citations
Meta-Learning for Semi-Supervised Few-Shot Classification

Mengye Ren;Eleni Triantafillou;Sachin Ravi;Jake Snell

619
Citations
INFERENCE AND COMPUTATION WITH POPULATION CODES

Alexandre Pouget;Peter Dayan;Richard S. Zemel

601
Citations
Learning and Incorporating Top-Down Cues in Image Segmentation

Xuming He;Richard S. Zemel;Debajyoti Ray

521
Citations
The Variational Fair Autoencoder

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

461
Citations
Causal Effect Inference with Deep Latent-Variable Models

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

424
Citations
Advances in Neural Information Processing Systems 5

Richard S Zemel;Christopher Williams;Michael C Mozer

237
Citations

Frequent Co-Authors

Raquel Urtasun University of Toronto

Renjie Liao University of British Columbia

Kevin Swersky Google (United States)

Peter Dayan Max Planck Institute for Biological Cybernetics

Toniann Pitassi Columbia University

Max Welling University of Amsterdam

Geoffrey E. Hinton University of Toronto

Michael C. Mozer Google (United States)

Ryan P. Adams Princeton University

Ruslan Salakhutdinov Carnegie Mellon University

External Links

Wikipedia of Richard S. Zemel Personal website of Richard S. Zemel Google Scholar page

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