2026 Avrim Blum: 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	84	826	796	448	429	259	42925

Research.com Recognitions

2007 - ACM Fellow For contributions to learning theory and algorithms.
1994 - Fellow of Alfred P. Sloan Foundation

Overview

Avrim Blum is affiliated with the Toyota Technological Institute at Chicago in the United States. Their research spans primarily across computer science, with focused contributions in several subfields including artificial intelligence, management science and operations research, computational theory and mathematics, computer networks and communications, and computer vision and pattern recognition.

The main topics of their work include:

Machine Learning and Algorithms
Adversarial Robustness in Machine Learning
Complexity and Algorithms in Graphs
Algorithms and Data Compression
Optimization and Search Problems
Markov Chains and Monte Carlo Methods
Advanced Bandit Algorithms Research

Recent papers by Avrim Blum demonstrate a breadth of study in theory and practical aspects of algorithm design and fairness in machine learning. Notable publications include:

"Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries" (2020) in Operations Research
"Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?" (2020) published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
"Random Smoothing Might be Unable to Certify ℓ∞ Robustness for High-Dimensional Images" (2020) on arXiv (Cornell University)
"Advancing Subgroup Fairness via Sleeping Experts" (2020) also appearing in Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
"Technical perspective: Algorithm selection as a learning problem" (2020) in Communications of the ACM

Avrim Blum's frequent co-authors include John E. Hopcroft, Ravindran Kannan, Kevin Stangl, Saba Ahmadi, and Keziah Naggita. Collaboration with these researchers occurs regularly across numerous publications.

The scholar has also contributed to book literature, publishing "Foundations of Data Science" in 2020 through Cambridge University Press, a work that has accumulated significant citations.

Publication venues where their work often appears include:

arXiv (Cornell University)
Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
Operations Research
Communications of the ACM
Proceedings of the AAAI Conference on Artificial Intelligence

Recognition of their contributions includes being named an ACM Fellow in 2007 for work in learning theory and algorithms, as well as a Fellow of the Alfred P. Sloan Foundation in 1994.

Best Publications

Combining labeled and unlabeled data with co-training

Avrim Blum;Tom Mitchell

7496
Citations
Selection of relevant features and examples in machine learning

Avrim L. Blum;Pat Langley

5158
Citations
Fast planning through planning graph analysis

Avrim L. Blum;Merrick L. Furst

3457
Citations
Correlation clustering

N. Bansal;A. Blum;S. Chawla

2116
Citations
Learning from Labeled and Unlabeled Data using Graph Mincuts

Avrim Blum;Shuchi Chawla

1445
Citations
Practical privacy: the SuLQ framework

Avrim Blum;Cynthia Dwork;Frank McSherry;Kobbi Nissim

1001
Citations
Noise-tolerant learning, the parity problem, and the statistical query model

Avrim Blum;Adam Kalai;Hal Wasserman

999
Citations
A learning theory approach to noninteractive database privacy

Avrim Blum;Katrina Ligett;Aaron Roth

843
Citations
A learning theory approach to non-interactive database privacy

Avrim Blum;Katrina Ligett;Aaron Roth

800
Citations
Training a 3-Node Neural Network is NP-Complete

Avrim Blum;Ronald L. Rivest

757
Citations
Original Contribution: Training a 3-node neural network is NP-complete

Avrim L. Blum;Ronald L. Rivest

747
Citations
Approximation Algorithms for Orienteering and Discounted-Reward TSP

Avrim Blum;Shuchi Chawla;David R. Karger;Terran Lane

449
Citations
Cryptographic Primitives Based on Hard Learning Problems

Avrim Blum;Merrick L. Furst;Michael J. Kearns;Richard J. Lipton

434
Citations
Linear approximation of shortest superstrings

Avrim Blum;Tao Jiang;Ming Li;John Tromp

430
Citations
The minimum latency problem

Avrim Blum;Prasad Chalasani;Don Coppersmith;Bill Pulleyblank

426
Citations
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges

David J. Abraham;Avrim Blum;Tuomas Sandholm

415
Citations
On-line Algorithms in Machine Learning

Avrim Blum

403
Citations
Beating the hold-out: bounds for K-fold and progressive cross-validation

Avrim Blum;Adam Kalai;John Langford

400
Citations
Empirical Support for Winnow and Weighted-MajorityAlgorithms: Results on a Calendar Scheduling Domain

Avrim Blum

365
Citations
Co-Training and Expansion: Towards Bridging Theory and Practice

Maria-florina Balcan;Avrim Blum;Ke Yang

349
Citations

Frequent Co-Authors

Maria-Florina Balcan Carnegie Mellon University

Yishay Mansour Tel Aviv University

Santosh Vempala Georgia Institute of Technology

Adam Tauman Kalai Microsoft (United States)

Ariel D. Procaccia Harvard University

John Langford Microsoft (United States)

Prabhakar Raghavan Google (United States)

Nikhil Bansal University of Michigan–Ann Arbor

Tuomas Sandholm Carnegie Mellon University

MohammadTaghi Hajiaghayi University of Maryland, College Park

External Links

Wikipedia of Avrim Blum Personal website of Avrim Blum Google Scholar page

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