2026 Richard Peng: 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	37	10887	10585	4526	4339	167	4945

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Computer Science

10887

10585

4526

4339

167

4945

Overview

Richard Peng is affiliated with the University of Waterloo in Canada, specializing in the field of Computer Science. Their research primarily focuses on areas within computational theory and mathematics, with notable work spanning subfields such as Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications, Statistics and Probability, and Electrical and Electronic Engineering.

The scientist's research topics encompass:

Complexity and Algorithms in Graphs
Advanced Graph Theory Research
Optimization and Search Problems
Stochastic Gradient Optimization Techniques
Markov Chains and Monte Carlo Methods
Advanced Graph Neural Networks
Matrix Theory and Algorithms

Richard Peng has authored numerous papers, including recent works such as:

Maximum Flow and Minimum-Cost Flow in Almost-Linear Time, 2022, 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)
MathChat: Converse to Tackle Challenging Math Problems with LLM Agents, 2023, arXiv (Cornell University)
Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow, 2023, Communications of the ACM
Association of Circulating Fibrocytes With Fibrostenotic Small Bowel Crohn's Disease, 2021, Inflammatory Bowel Diseases
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation via Short Cycle Decompositions, 2020, SIAM Journal on Computing

Their frequent co-authors include:

Yang P. Liu
Sushant Sachdeva
Rasmus Kyng
Maximilian Probst Gutenberg
Jingbang Chen

Richard Peng's publications appear predominantly in venues such as:

arXiv (Cornell University)
Communications of the ACM
SIAM Journal on Computing
2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)
Inflammatory Bowel Diseases

Best Publications

Approaching Optimality for Solving SDD Linear Systems

Ioannis Koutis;Gary L. Miller;Richard Peng

523
Citations
A Nearly-m log n Time Solver for SDD Linear Systems

Ioannis Koutis;Gary L. Miller;Richard Peng

295
Citations
Maximum Flow and Minimum-Cost Flow in Almost-Linear Time

Unknown

262
Citations
Uniform Sampling for Matrix Approximation

Michael B. Cohen;Yin Tat Lee;Cameron Musco;Christopher Musco

208
Citations
Approaching Optimality for Solving SDD Linear Systems

Ioannis Koutis;Gary L. Miller;Richard Peng

197
Citations
Solving SDD linear systems in nearly mlog1/2n time

Michael B. Cohen;Rasmus Kyng;Gary L. Miller;Jakub W. Pachocki

189
Citations
Efficient Triangle Counting in Large Graphs via Degree-Based Vertex Partitioning

Mihail N. Kolountzakis;Gary L. Miller;Richard Peng;Charalampos E. Tsourakakis

174
Citations
A nearly-mlogn time solver for SDD linear systems

Ioannis Koutis;Gary L. Miller;Richard Peng

157
Citations
An efficient parallel solver for SDD linear systems

Richard Peng;Daniel A. Spielman

145
Citations
Fully Dynamic (1+ e)-Approximate Matchings

Manoj Gupta;Richard Peng

143
Citations
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling

Michael Mitzenmacher;Jakub Pachocki;Richard Peng;Charalampos Tsourakakis

142
Citations
Sparsified Cholesky and multigrid solvers for connection laplacians

Rasmus Kyng;Yin Tat Lee;Richard Peng;Sushant Sachdeva

137
Citations
Parallel graph decompositions using random shifts

Gary L. Miller;Richard Peng;Shen Chen Xu

124
Citations
Approaching optimality for solving SDD systems

Ioannis Koutis;Gary L. Miller;Richard Peng

111
Citations
Iterative Row Sampling

Mu Li;Gary L. Miller;Richard Peng

101
Citations
Partitioning Well-Clustered Graphs: Spectral Clustering Works!

Richard Peng;He Sun;Luca Zanetti

93
Citations
Approximate undirected maximum flows in o(mpolylog(n)) time

Richard Peng

92
Citations
Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs

Michael B. Cohen;Jonathan Kelner;John Peebles;Richard Peng

92
Citations
Lp Row Sampling by Lewis Weights

Michael B. Cohen;Richard Peng

86
Citations
Improved Parallel Algorithms for Spanners and Hopsets

Gary L. Miller;Richard Peng;Adrian Vladu;Shen Chen Xu

85
Citations
A Deterministic Algorithm for Balanced Cut with Applications to Dynamic Connectivity, Flows, and Beyond

Julia Chuzhoy;Yu Gao;Jason Li;Danupon Nanongkai

83
Citations
Nearly-Linear Work Parallel SDD Solvers, Low-Diameter Decomposition, and Low-Stretch Subgraphs

Guy E. Blelloch;Anupam Gupta;Ioannis Koutis;Gary L. Miller

74
Citations
Fully Dynamic $(1+psilon)$-Approximate Matchings

Manoj Gupta;Richard Peng

6
Citations

Frequent Co-Authors

Gary L. Miller Carnegie Mellon University

Aaron Sidford Stanford University

Yin Tat Lee Microsoft (United States)

Daniel A. Spielman Yale University

Santosh Vempala Georgia Institute of Technology

Guy E. Blelloch Carnegie Mellon University

Jie Tang Tsinghua University

Danupon Nanongkai Max Planck Institute for Informatics

Anupam Gupta Carnegie Mellon University

Monika Henzinger Institute of Science and Technology Austria

External Links

Personal website of Richard Peng

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