2026 David P. Woodruff: 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	57	3872	3762	1831	1765	371	11952

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Computer Science

3872

3762

1831

1765

371

11952

Overview

David P. Woodruff is affiliated with Carnegie Mellon University in the United States. Their research primarily focuses on computer science, with an extensive body of work spanning various subfields and topics.

The main fields of study for Woodruff include:

Computer Science

Within this broad area, their contributions span several subfields:

Artificial Intelligence
Computational Mechanics
Computational Theory and Mathematics
Computer Networks and Communications
Computer Vision and Pattern Recognition

Regarding specific research topics, Woodruff has worked extensively on:

Stochastic Gradient Optimization Techniques
Sparse and Compressive Sensing Techniques
Machine Learning and Algorithms
Complexity and Algorithms in Graphs
Optimization and Search Problems
Algorithms and Data Compression
Tensor decomposition and applications

Woodruff has authored numerous scientific papers, including recent publications such as:

"How to Reduce Dimension With PCA and Random Projections?" (2021), published in IEEE Transactions on Information Theory
"A Framework for Adversarially Robust Streaming Algorithms" (2022), published in Journal of the ACM
"Tight Bounds for Sketching the Operator Norm, Schatten Norms, and Subspace Embeddings" (2022), published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
"Perfect Lₚ Sampling in a Data Stream" (2021), published in SIAM Journal on Computing
"Querying a Matrix through Matrix-Vector Products" (2021), published in ACM Transactions on Algorithms

The scientist frequently collaborates with other researchers, including:

Samson Zhou
Taisuke Yasuda
Praneeth Kacham
Honghao Lin
Rajesh Jayaram

Their work appears regularly in established venues, with multiple publications found in:

arXiv (Cornell University)
Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
ACM Transactions on Algorithms
Proceedings of the ACM on Management of Data
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)

Best Publications

Sketching as a Tool for Numerical Linear Algebra

David P. Woodruff

1056
Citations
Low-Rank Approximation and Regression in Input Sparsity Time

Kenneth L. Clarkson;David P. Woodruff

717
Citations
Fast approximation of matrix coherence and statistical leverage

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

483
Citations
Numerical linear algebra in the streaming model

Kenneth L. Clarkson;David P. Woodruff

395
Citations
An optimal algorithm for the distinct elements problem

Daniel M. Kane;Jelani Nelson;David P. Woodruff

365
Citations
Optimal approximations of the frequency moments of data streams

Piotr Indyk;David Woodruff

296
Citations
Optimal space lower bounds for all frequency moments

David Woodruff

196
Citations
Optimal bounds for Johnson-Lindenstrauss transforms and streaming problems with sub-constant error

T. S. Jayram;David P. Woodruff

184
Citations
Lower bounds for sparse recovery

Khanh Do Ba;Piotr Indyk;Eric Price;David P. Woodruff

176
Citations
Optimal CUR Matrix Decompositions

Christos Boutsidis;David P. Woodruff

169
Citations
Tight lower bounds for the distinct elements problem

P. Indyk;D. Woodruff

163
Citations
On the exact space complexity of sketching and streaming small norms

Daniel M. Kane;Jelani Nelson;David P. Woodruff

161
Citations
Frequent Directions: Simple and Deterministic Matrix Sketching

Mina Ghashami;Edo Liberty;Jeff M. Phillips;David P. Woodruff

160
Citations
Sublinear optimization for machine learning

Kenneth L. Clarkson;Elad Hazan;David P. Woodruff

159
Citations
A Geometric Approach to Information-Theoretic Private Information Retrieval

David Woodruff;Sergey Yekhanin

153
Citations
Communication lower bounds for statistical estimation problems via a distributed data processing inequality

Mark Braverman;Ankit Garg;Tengyu Ma;Huy L. Nguyen

148
Citations
1-pass relative-error Lp-sampling with applications

Morteza Monemizadeh;David P. Woodruff

134
Citations
New Lower Bounds for General Locally Decodable Codes.

David P. Woodruff

131
Citations
Polylogarithmic private approximations and efficient matching

Piotr Indyk;David Woodruff

125
Citations
Fast approximation of matrix coherence and statistical leverage

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

118
Citations
Improved Distributed Principal Component Analysis

Yingyu Liang;Maria-Florina F Balcan;Vandana Kanchanapally;David Woodruff

90
Citations

Frequent Co-Authors

Kenneth L. Clarkson IBM (United States)

Zhao Song Adobe Systems (United States)

Piotr Indyk MIT

Maria-Florina Balcan Carnegie Mellon University

Marten van Dijk University of Connecticut

Petros Drineas Purdue University West Lafayette

Yingyu Liang University of Wisconsin–Madison

Christian Sohler University of Cologne

Michael W. Mahoney University of California, Berkeley

Malik Magdon-Ismail Rensselaer Polytechnic Institute

External Links

Personal website of David P. Woodruff Google Scholar page

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