LabCompass

Paul Valiant

Computer Science · Purdue University West Lafayette

OpenAlex ORCID
Mid career · publishing since 2002
Machine Learning and AlgorithmsComplexity and Algorithms in GraphsStatistical Methods and InferenceAuction Theory and ApplicationsAlgorithms and Data Compression

Publications

71

Citations

1,777

Est. group size

—

Recurring co-author estimate

Active years

25

Publishing since 2002

Research summary
AI-generated

Paul Valiant works in theoretical computer science, focusing on the mathematical foundations of statistics, learning, and algorithms. His work includes topics like trace reconstruction (recovering an original signal from noisy, corrupted copies), estimating unknown probability distributions and mixtures efficiently, and understanding the theoretical capabilities and limitations of neural networks. Much of this research aims to find provably optimal algorithms for statistical estimation and testing problems.

Trace reconstruction and signal recoveryStatistical estimation theory (mean estimation, distribution testing)Theoretical limits of neural networksAlgorithmic learning theoryOptimal algorithm design for probability and statistics problems

Publication output has been fairly steady over the last decade, generally producing 2-3 papers per year with a temporary peak in 2019, and this pace continues into recent years.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 2.4/year recently
2017: 2 publications17182019: 6 publications6192020: 3 publications202021: 2 publications212022: 2 publications222023: 3 publications232024: 3 publications242025: 2 publications252026: 2 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×17
  • Society for Industrial and Applied Mathematics eBooks×2
  • SIAM Journal on Computing×1
  • Journal of the ACM×1
  • Nature Communications×1
Similar researchers
By research-topic overlap

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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