2026 Roman Vershynin: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	52	938	801	441	352	118	18785

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

938

801

441

352

118

18785

Research.com Recognitions

2005 - Fellow of Alfred P. Sloan Foundation

Overview

Roman Vershynin is affiliated with the University of California, Irvine in the United States. Their research contributions are primarily situated within the field of Computer Science, with significant focus on subfields such as Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics, Molecular Biology, and Computer Science Applications.

The primary topics addressed in their work include:

Privacy-Preserving Technologies in Data
Cryptography and Data Security
Random Matrices and Applications
Mobile Crowdsensing and Crowdsourcing
Neural Networks and Applications
Advanced Memory and Neural Computing
Stochastic processes and statistical mechanics

Roman Vershynin's publication record includes papers published across several journals and venues. Frequent outlets for their work are:

arXiv (Cornell University)
SIAM Journal on Mathematics of Data Science
Foundations of Computational Mathematics
The Annals of Probability
Random Matrices Theory and Application

Recent notable papers include:

Memory Capacity of Neural Networks with Threshold and Rectified Linear Unit Activations, 2020, SIAM Journal on Mathematics of Data Science
Marchenko-Pastur law with relaxed independence conditions, 2020, Random Matrices Theory and Application
Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data, 2022, Foundations of Computational Mathematics
The smallest singular value of inhomogeneous square random matrices, 2021, The Annals of Probability
Memory capacity of neural networks with threshold and ReLU activations, 2020, arXiv (Cornell University)

Collaborative work features frequent coauthors such as:

Thomas Strohmer
March T. Boedihardjo
Yizhe Zhu
Pierre Baldi
Yiyun He

Roman Vershynin was recognized as a Fellow of the Alfred P. Sloan Foundation in 2005. This distinction is noted without additional citation details.

Best Publications

Introduction to the non-asymptotic analysis of random matrices.

Roman Vershynin

3302
Citations
High-Dimensional Probability: An Introduction with Applications in Data Science

Roman Vershynin

1762
Citations
Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit

Deanna Needell;Roman Vershynin

1341
Citations
Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit

Deanna Needell;Roman Vershynin

1257
Citations
A Randomized Kaczmarz Algorithm with Exponential Convergence

Thomas Strohmer;Roman Vershynin

1009
Citations
On sparse reconstruction from Fourier and Gaussian measurements

Mark Rudelson;Roman Vershynin

993
Citations
Hanson-Wright inequality and sub-gaussian concentration

Mark Rudelson;Roman Vershynin

700
Citations
Robust 1-bit Compressed Sensing and Sparse Logistic Regression: A Convex Programming Approach

Y. Plan;R. Vershynin

515
Citations
One-Bit Compressed Sensing by Linear Programming

Yaniv Plan;Roman Vershynin

455
Citations
The Littlewood-Offord problem and invertibility of random matrices

Mark Rudelson;Roman Vershynin

429
Citations
Non-asymptotic Theory of Random Matrices: Extreme Singular Values

Mark Rudelson;Roman Vershynin

399
Citations
Sampling from large matrices: An approach through geometric functional analysis

Mark Rudelson;Roman Vershynin

391
Citations
Smallest singular value of a random rectangular matrix

Mark Rudelson;Roman Vershynin

388
Citations
Error correction via linear programming

Emmanuel Candes;Mark Rudelson;Terence Tao;Roman Vershynin

379
Citations
One sketch for all: fast algorithms for compressed sensing

A. C. Gilbert;M. J. Strauss;J. A. Tropp;R. Vershynin

375
Citations
How Close is the Sample Covariance Matrix to the Actual Covariance Matrix

Roman Vershynin

361
Citations
Sparse reconstruction by convex relaxation: Fourier and Gaussian measurements

Mark Rudelson;Roman Vershynin

301
Citations
Geometric approach to error-correcting codes and reconstruction of signals

Mark Rudelson;Roman Vershynin

218
Citations
Community detection in sparse networks via Grothendieck's inequality

Olivier Guédon;Roman Vershynin

218
Citations
The Generalized Lasso With Non-Linear Observations

Yaniv Plan;Roman Vershynin

207
Citations
The smallest singular value of a random rectangular matrix

Mark Rudelson;Roman Vershynin

10
Citations

Frequent Co-Authors

Mark Rudelson University of Michigan–Ann Arbor

Elizaveta Levina University of Michigan–Ann Arbor

Pierre Baldi University of California, Irvine

Deanna Needell University of California, Los Angeles

Joel A. Tropp California Institute of Technology

Shahar Mendelson Texas A&M University

Martin J. Strauss University of Michigan–Ann Arbor

Anna C. Gilbert Yale University

Thomas Strohmer University of California, Davis

Raja Giryes Tel Aviv University

External Links

Personal website of Roman Vershynin Google Scholar page

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