2026 Gregory Valiant: 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	32	13117	12729	5273	5026	142	4756

Research.com Recognitions

2017 - Hellman Fellow
2016 - Fellow of Alfred P. Sloan Foundation

Overview

Gregory Valiant is affiliated with Stanford University in the United States and specializes primarily in the field of Computer Science. Their research contributions span multiple subfields, including Artificial Intelligence, Molecular Biology, Management Science and Operations Research, Computational Theory and Mathematics, and Computer Networks and Communications.

The scientist's work covers a variety of key topics such as Machine Learning and Algorithms, Advanced Bandit Algorithms Research, Domain Adaptation and Few-Shot Learning, Machine Learning and Data Classification, Natural Language Processing Techniques, Complexity and Algorithms in Graphs, and Stochastic Gradient Optimization Techniques.

Valiant's publication record includes papers appearing in venues like arXiv (Cornell University), Leibniz-Zentrum für Informatik (Schloss Dagstuhl), eLife, bioRxiv (Cold Spring Harbor Laboratory), and Cambridge University Press eBooks. The most frequent venue for their papers is arXiv, with 21 publications.

Recent papers authored or co-authored by Valiant include:

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes, 2022, arXiv (Cornell University)
On the Generalization Effects of Linear Transformations in Data Augmentation, 2020, arXiv (Cornell University)
ReporterSeq reveals genome-wide dynamic modulators of the heat shock response across diverse stressors, 2021, eLife
Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training, 2021, arXiv (Cornell University)

Frequent collaborators in their research include Vatsal Sharan, Shivam Garg, Annie Marsden, Mingda Qiao, and Percy Liang.

Gregory Valiant has been recognized with several awards, notably the Hellman Fellow award in 2017 and being named a Fellow of the Alfred P. Sloan Foundation in 2016.

Best Publications

Settling the Polynomial Learnability of Mixtures of Gaussians

Ankur Moitra;Gregory Valiant

336
Citations
An Automatic Inequality Prover and Instance Optimal Identity Testing

Gregory Valiant;Paul Valiant

336
Citations
Estimating the unseen: an n/log(n)-sample estimator for entropy and support size, shown optimal via new CLTs

Gregory Valiant;Paul Valiant

333
Citations
Learning from untrusted data

Moses Charikar;Jacob Steinhardt;Gregory Valiant

276
Citations
Efficiently learning mixtures of two Gaussians

Adam Tauman Kalai;Ankur Moitra;Gregory Valiant

237
Citations
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Unknown

211
Citations
Optimal algorithms for testing closeness of discrete distributions

Siu-On Chan;Ilias Diakonikolas;Gregory Valiant;Paul Valiant

177
Citations
The Power of Linear Estimators

Gregory Valiant;Paul Valiant

173
Citations
Learning Polynomials with Neural Networks

Alexandr Andoni;Rina Panigrahy;Gregory Valiant;Li Zhang

166
Citations
Estimating the Unseen: Improved Estimators for Entropy and Other Properties

Gregory Valiant;Paul Valiant

159
Citations
An Automatic Inequality Prover and Instance Optimal Identity Testing

Gregory Valiant;Paul Valiant

132
Citations
Estimating the Unseen: Improved Estimators for Entropy and other Properties

Paul Valiant;Gregory Valiant

129
Citations
Braess's Paradox in large random graphs

Gregory Valiant;Tim Roughgarden

115
Citations
Designing Network Protocols for Good Equilibria

Ho-Lin Chen;Tim Roughgarden;Gregory Valiant

109
Citations
Finding Correlations in Subquadratic Time, with Applications to Learning Parities and Juntas

Gregory Valiant

100
Citations
A CLT and tight lower bounds for estimating entropy.

Gregory Valiant;Paul Valiant

95
Citations
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers

Jacob Steinhardt;Moses Charikar;Gregory Valiant

88
Citations
Finding Correlations in Subquadratic Time, with Applications to Learning Parities and the Closest Pair Problem

Gregory Valiant

87
Citations
Testing k-modal distributions: optimal algorithms via reductions

Constantinos Daskalakis;Ilias Diakonikolas;Rocco A. Servedio;Gregory Valiant

82
Citations
Making AI Forget You: Data Deletion in Machine Learning

Antonio Ginart;Melody Guan;Gregory Valiant;James Y. Zou

81
Citations
On Learning Algorithms for Nash Equilibria

Constantinos Daskalakis;Rafael Frongillo;Christos H. Papadimitriou;George Pierrakos

79
Citations
Size and Treewidth Bounds for Conjunctive Queries

Georg Gottlob;Stephanie Tien Lee;Gregory Valiant;Paul Valiant

79
Citations
Disentangling Gaussians

Adam Tauman Kalai;Ankur Moitra;Gregory Valiant

76
Citations
Memory, Communication, and Statistical Queries

Jacob Steinhardt;Gregory Valiant;Stefan Wager

74
Citations
Finding Correlations in Subquadratic Time, with Applications to Learning Parities and Juntas with Noise.

Gregory Valiant

10
Citations

Frequent Co-Authors

Peter Bailis Stanford University

Sham M. Kakade Harvard University

Tim Roughgarden Columbia University

Constantinos Daskalakis MIT

James Zou Stanford University

Christos H. Papadimitriou Columbia University

Ankur Moitra MIT

Moses Charikar Stanford University

Ilias Diakonikolas University of Wisconsin–Madison

Daniel G. MacArthur Garvan Institute of Medical Research

External Links

Personal website of Gregory Valiant

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