2026 Michael W. Mahoney: 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	74	1471	1426	766	738	307	25651

Michael W. Mahoney 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 Michael W. Mahoney sits on this spectrum.

32 publications 991+

This scientist: 307 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Michael W. Mahoney 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 Michael W. Mahoney sits on this spectrum.

30 D-Index 131+

This scientist: 74 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.

Overview

Michael W. Mahoney is affiliated with the University of California, Berkeley in the United States. Their research primarily concerns the domain of Computer Science, with a focus on Artificial Intelligence. Their scholarship extends into related subfields including Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Computational Mechanics, and Signal Processing.

The extent of Mahoney's published work includes 284 contributions within Computer Science, with 199 specifically in Artificial Intelligence, 45 in Computer Vision and Pattern Recognition, 33 in Statistical and Nonlinear Physics, 30 in Computational Mechanics, and 17 in Signal Processing.

Topics frequently addressed in their research include:

Stochastic Gradient Optimization Techniques
Neural Networks and Applications
Sparse and Compressive Sensing Techniques
Model Reduction and Neural Networks
Advanced Neural Network Applications
Topic Modeling
Domain Adaptation and Few-Shot Learning

Mahoney has contributed papers to multiple publication venues, notably:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
Nature Communications
INFORMS Journal on Optimization
SIAM Journal on Matrix Analysis and Applications

Some of the recent papers associated with Mahoney's research include:

"Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT" (2020), Proceedings of the AAAI Conference on Artificial Intelligence
"Characterizing possible failure modes in physics-informed neural networks" (2021), arXiv (Cornell University)
"Shallow neural networks for fluid flow reconstruction with limited sensors" (2020), Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
"ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning" (2021), Proceedings of the AAAI Conference on Artificial Intelligence
"AI and Memory Wall" (2024), IEEE Micro

Frequent collaborators in their academic work include Kurt Keutzer, Amir Gholami, N. Benjamin Erichson, Zhewei Yao, and Liam Hodgkinson. The collaborations with these coauthors indicate ongoing engagement with several experts in the fields of machine learning and computational science.

Best Publications

Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters

Jure Leskovec;Kevin J. Lang;Anirban Dasgupta;Michael W. Mahoney

2315
Citations
Empirical comparison of algorithms for network community detection

Jure Leskovec;Kevin J. Lang;Michael Mahoney

1227
Citations
Statistical properties of community structure in large social and information networks

Jure Leskovec;Kevin J. Lang;Anirban Dasgupta;Michael W. Mahoney

1162
Citations
On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning

Petros Drineas;Michael W. Mahoney

1027
Citations
CUR matrix decompositions for improved data analysis

Michael W. Mahoney;Petros Drineas

972
Citations
A Survey of Quantization Methods for Efficient Neural Network Inference

Amir Gholami;Sehoon Kim;Zhen Dong;Zhewei Yao

947
Citations
Randomized Algorithms for Matrices and Data

Michael W. Mahoney

841
Citations
Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix

Petros Drineas;Ravi Kannan;Michael W. Mahoney

659
Citations
Relative-Error $CUR$ Matrix Decompositions

Petros Drineas;Michael W. Mahoney;S. Muthukrishnan

598
Citations
Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication

Petros Drineas;Ravi Kannan;Michael W. Mahoney

542
Citations
Faster least squares approximation

Petros Drineas;Michael W. Mahoney;S. Muthukrishnan;Tamás Sarlós

536
Citations
Fast approximation of matrix coherence and statistical leverage

Petros Drineas;Malik Magdon-Ismail;Michael W. Mahoney;David P. Woodruff

483
Citations
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT

Sheng Shen;Zhen Dong;Jiayu Ye;Linjian Ma

463
Citations
HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision

Zhen Dong;Zhewei Yao;Amir Gholami;Michael Mahoney

458
Citations
An improved approximation algorithm for the column subset selection problem

Christos Boutsidis;Michael W. Mahoney;Petros Drineas

453
Citations
Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition

Petros Drineas;Ravi Kannan;Michael W. Mahoney

394
Citations
ZeroQ: A Novel Zero Shot Quantization Framework

Yaohui Cai;Zhewei Yao;Zhen Dong;Amir Gholami

366
Citations
Revisiting the Nyström method for improved large-scale machine learning

Alex Gittens;Michael W. Mahoney

365
Citations
PCA-correlated SNPs for structure identification in worldwide human populations.

Peristera Paschou;Elad Ziv;Esteban G Burchard;Shweta Choudhry

347
Citations
Sampling algorithms for l2 regression and applications

Petros Drineas;Michael W. Mahoney;S. Muthukrishnan

338
Citations
Sampling algorithms for l 2 regression and applications

Petros Drineas;Michael W. Mahoney;S. Muthukrishnan

233
Citations
Fast approximation of matrix coherence and statistical leverage

Petros Drineas;Malik Magdon-ismail;David Woodruff;Michael W. Mahoney

118
Citations

Frequent Co-Authors

Petros Drineas Purdue University West Lafayette

Kurt Keutzer University of California, Berkeley

David F. Gleich Purdue University West Lafayette

Ravi Kannan Microsoft (United States)

David P. Woodruff Carnegie Mellon University

Joseph E. Gonzalez University of California, Berkeley

James Demmel University of California, Berkeley

Ananth Grama Purdue University West Lafayette

Malik Magdon-Ismail Rensselaer Polytechnic Institute

Subbaratnam Muthukrishnan Kansas State University

External Links

Personal website of Michael W. Mahoney Google Scholar page

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