LabCompass

Wojciech Szpankowski

Computer Science · Purdue University West Lafayette

Established · publishing since 1981

Publications

441

Citations

6,728

Est. group size

~3

Recurring co-author estimate

Active years

46

Publishing since 1981

Research summary
AI-generated

Wojciech Szpankowski works in information theory and theoretical computer science, focusing on how to precisely measure the complexity and compressibility of data and how to design algorithms that learn or make predictions with provable guarantees. Recent work centers on online learning (algorithms that update predictions as new data arrives), minimax regret analysis (bounding worst-case prediction error), data compression methods, and mathematical models of random graphs such as duplication-divergence network models used to describe biological or social networks.

Information theory and data compressionOnline and statistical learning theoryMinimax regret analysisRandom graph and network modelsAnalytic combinatorics applied to algorithms

Publication output rose through the late 2010s and peaked around 2020-2021, then became more variable and lower in the most recent years (2023-2026), suggesting a slowing pace after a period of steady, higher activity.

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

Publication cadence
Publications per year over the last 10 years — averaging 6.4/year recently
2017: 6 publications172018: 13 publications182019: 10 publications192020: 14 publications202021: 15 publications15212022: 10 publications222023: 7 publications232024: 12 publications242025: 2 publications252026: 1 publication26
Recent publications
Publishes in
  • arXiv (Cornell University)×34
  • IEEE Transactions on Information Theory×6
  • HAL (Le Centre pour la Communication Scientifique Directe)×4
  • IEEE Transactions on Molecular Biological and Multi-Scale Communications×2
  • Algorithmica×2
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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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