2026 Eli Upfal: 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	70	1865	1805	953	916	265	20690

Research.com Recognitions

2005 - ACM Fellow For contributions to parallel and stochastic networks.
2002 - IEEE Fellow For contributions to theoretical aspects of computer science and engineering.

Overview

Eli Upfal is affiliated with Brown University in the United States and has contributed extensively to the field of computer science. Their research spans 28 publications primarily focused on artificial intelligence, computer vision and pattern recognition, statistical and nonlinear physics, communication, and statistics and probability.

Their work covers various main topics, including:

Complex Network Analysis Techniques
Markov Chains and Monte Carlo Methods
Machine Learning and Algorithms
Data Stream Mining Techniques
Graph Theory and Algorithms
Social Media and Politics
Internet Traffic Analysis and Secure E-voting

Eli Upfal has published in a number of venues, with notable frequent publications in:

arXiv (Cornell University)
Algorithms
Data Mining and Knowledge Discovery
ACM Transactions on Knowledge Discovery from Data
Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Some recent papers by Eli Upfal include:

Distributed Graph Diameter Approximation, 2020, Algorithms
Reducing polarization and increasing diverse navigability in graphs by inserting edges and swapping edge weights, 2022, Data Mining and Knowledge Discovery
Tiered Sampling, 2021, ACM Transactions on Knowledge Discovery from Data
On the Complexity of Anonymous Communication Through Public Networks, 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds, 2021, arXiv (Cornell University)

Frequent collaborators in Eli Upfal's research include:

Shahrzad Haddadan
Alessio Mazzetto
Cristina Menghini
Cyrus Cousins
Matteo Riondato

Among the recognitions Eli Upfal has received are:

ACM Fellow, 2005, for contributions to parallel and stochastic networks
IEEE Fellow, 2002, for contributions to theoretical aspects of computer science and engineering

This profile reflects a research career characterized by contributions to theoretical and applied computer science, with a focus on complex networks, algorithms, and data mining methodologies.

Best Publications

Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Michael Mitzenmacher;Eli Upfal

3460
Citations
Stochastic models for the Web graph

R. Kumar;P. Raghavan;S. Rajagopalan;D. Sivakumar

1055
Citations
Balanced Allocations

Yossi Azar;Andrei Z. Broder;Anna R. Karlin;Eli Upfal

982
Citations
A trade-off between space and efficiency for routing tables

David Peleg;Eli Upfal

603
Citations
Efficient algorithms for all-to-all communications in multiport message-passing systems

J. Bruck;Ching-Tien Ho;S. Kipnis;E. Upfal

513
Citations
The Web as a graph

Ravi Kumar;Prabhakar Raghavan;Sridhar Rajagopalan;D. Sivakumar

506
Citations
De novo discovery of mutated driver pathways in cancer

Fabio Vandin;Eli Upfal;Benjamin J. Raphael

488
Citations
Building low-diameter peer-to-peer networks

G. Pandurangan;P. Raghavan;E. Upfal

484
Citations
Algorithms for detecting significantly mutated pathways in cancer.

Fabio Vandin;Eli Upfal;Benjamin J. Raphael

472
Citations
Multi-armed bandits in metric spaces

Robert Kleinberg;Aleksandrs Slivkins;Eli Upfal

469
Citations
Constructing a perfect matching is in random NC

R M Karp;E Upfal;A Wigderson

409
Citations
Computing with Noisy Information

Uriel Feige;Prabhakar Raghavan;David Peleg;Eli Upfal

361
Citations
Parallel hashing: an efficient implementation of shared memory

Anna R. Karlin;Eli Upfal

358
Citations
Efficient routing in all-optical networks

Prabhakar Raghavan;Eli Upfal

347
Citations
Randomized broadcast in networks

Uriel Feige;David Peleg;Prabhakar Raghavan;Eli Upfal

343
Citations
Building low-diameter P2P networks

G. Pandurangan;P. Raghavan;E. Upfal

288
Citations
Efficient Schemes for Parallel Communication

Eli Upfal

280
Citations
Machine Learning in High Energy Physics Community White Paper

Kim Albertsson;Piero Altoe;Dustin Anderson;Michael Andrews

274
Citations
Using PageRank to Characterize Web Structure

Gopal Pandurangan;Prabhakar Raghavan;Eli Upfal

266
Citations
A simple load balancing scheme for task allocation in parallel machines

Larry Rudolph;Miriam Slivkin-Allalouf;Eli Upfal

265
Citations
Learning-based Query Performance Modeling and Prediction

Mert Akdere;Ugur Çetintemel;Matteo Riondato;Eli Upfal

262
Citations
Probability and computing : an introduction to randomizedalgorithms and probabilistic analysis

Michael Mitzenmacher;Eli Upfal

0
Citations

Frequent Co-Authors

Prabhakar Raghavan Google (United States)

Andrei Z. Broder Google (United States)

Alan Frieze Carnegie Mellon University

David Peleg Weizmann Institute of Science

Gopal Pandurangan University of Houston

Michael Mitzenmacher Harvard University

Benjamin J. Raphael Princeton University

Tim Kraska MIT

Avi Wigderson Institute for Advanced Study

Ravi Kumar Google (United States)

External Links

Wikipedia of Eli Upfal Personal website of Eli Upfal Google Scholar page

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