2026 Richard Nock: 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	34	11883	11541	362	361	250	12268

Richard Nock 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 Nock sits on this spectrum.

32 publications 991+

This scientist: 250 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Richard Nock 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 Nock sits on this spectrum.

30 D-Index 131+

This scientist: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Richard Nock is affiliated with the Australian National University in Australia and primarily works within the field of computer science. Their research extensively covers artificial intelligence, computer vision and pattern recognition, cognitive neuroscience, statistics and probability, as well as statistical and nonlinear physics.

Their scholarly output includes a significant focus on topics such as machine learning and data classification, machine learning and algorithms, adversarial robustness in machine learning, domain adaptation and few-shot learning, generative adversarial networks and image synthesis, explainable artificial intelligence (XAI), and human pose and action recognition.

Some of the recent publications attributed to Richard Nock include:

Advances and Open Problems in Federated Learning (2020), published in Foundations and Trends® in Machine Learning
Adversarial Vulnerabilities of Human Decision-Making (2020), published in Proceedings of the National Academy of Sciences
Manifold Learning Benefits GANs (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
SMINT (2020), published in ACM Transactions on the Web
Generalised Lipschitz Regularisation Equals Distributional Robustness (2020), published on arXiv (Cornell University)

Frequent co-authors include:

Frank Nielsen
Ehsan Amid
Manfred K. Warmuth
Sanmi Koyejo
Piotr Koniusz

Richard Nock's research has been disseminated through various publication venues, with multiple papers appearing in:

arXiv (Cornell University)
Proceedings of the National Academy of Sciences
bioRxiv (Cold Spring Harbor Laboratory)
Foundations and Trends® in Machine Learning
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Best Publications

Advances and Open Problems in Federated Learning

Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

4595
Citations
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach

Giorgio Patrini;Giorgio Patrini;Alessandro Rozza;Aditya Krishna Menon;Aditya Krishna Menon;Richard Nock;Richard Nock;Richard Nock

1463
Citations
Advances and open problems in federated learning

Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

1189
Citations
Statistical region merging

R. Nock;F. Nielsen

1181
Citations
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption.

Stephen Hardy;Wilko Henecka;Hamish Ivey-Law;Richard Nock

528
Citations
Adaptive Subspaces for Few-Shot Learning

Christian Simon;Piotr Koniusz;Richard Nock;Mehrtash Harandi

436
Citations
On weighting clustering

R. Nock;F. Nielsen

357
Citations
Sided and Symmetrized Bregman Centroids

F. Nielsen;R. Nock

214
Citations
A hybrid filter/wrapper approach of feature selection using information theory

Marc Sebban;Richard Nock

199
Citations
Bregman Voronoi Diagrams

Jean-Daniel Boissonnat;Frank Nielsen;Richard Nock

146
Citations
Learning and evaluation in the presence of class hierarchies: application to text categorization

Svetlana Kiritchenko;Stan Matwin;Richard Nock;A. Fazel Famili

133
Citations
Bregman Voronoi Diagrams: Properties, Algorithms and Applications

Jean-Daniel Boissonnat;Frank Nielsen;Richard Nock

125
Citations
A closed-form expression for the Sharma-Mittal entropy of exponential families

Frank Nielsen;Richard Nock

119
Citations
On Bregman Voronoi diagrams

Frank Nielsen;Jean-Daniel Boissonnat;Richard Nock

110
Citations
Almost) No Label No Cry

Giorgio Patrini;Richard Nock;Tiberio Caetano;Paul Rivera

101
Citations
Entropies and cross-entropies of exponential families

Frank Nielsen;Richard Nock

99
Citations
Entity Resolution and Federated Learning get a Federated Resolution.

Richard Nock;Stephen Hardy;Wilko Henecka;Hamish Ivey-Law

90
Citations
Bregman Divergences and Surrogates for Learning

R. Nock;F. Nielsen

85
Citations
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

Giorgio Patrini;Giorgio Patrini;Alessandro Rozza;Aditya Menon;Aditya Menon;Richard Nock;Richard Nock;Richard Nock

85
Citations
Fitting the smallest enclosing bregman ball

Richard Nock;Frank Nielsen

77
Citations
Loss factorization, weakly supervised learning and label noise robustness

Giorgio Patrini;Frank Nielsen;Richard Nock;Marcello Carioni

77
Citations
Impact of learning set quality and size on decision tree performances.

Marc Sebban;Richard Nock;Jean-Hugues Chauchat;Ricco Rakotomalala

77
Citations
A Real generalization of discrete AdaBoost

Richard Nock;Frank Nielsen

65
Citations

Frequent Co-Authors

Frank Nielsen Sony Computer Science Laboratories

Aditya Krishna Menon Google (United States)

Michel Barlaud Université Côte d'Azur

Robert C. Williamson University of Tübingen

Peter Dayan Max Planck Institute for Biological Cybernetics

Jean-Daniel Boissonnat Université Côte d'Azur

Simon Kornblith Google

Shun-ichi Amari RIKEN Center for Brain Science

Mehrtash Harandi Monash University

Piotr Koniusz University of New South Wales

External Links

Personal website of Richard Nock

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