LabCompass

Francesco De Pretis

Computer Science · Indiana University

OpenAlex ORCID
Computational Drug Discovery MethodsComplex Systems and Time Series AnalysisBayesian Modeling and Causal InferencePharmacovigilance and Adverse Drug ReactionsPharmaceutical Economics and Policy

Publications

35

Citations

166

Est. group size

—

Recurring co-author estimate

Active years

13

Publishing since 2014

Research summary
AI-generated

Francesco De Pretis works at the intersection of computer science, statistics, and applied economics, developing quantitative and probabilistic models for problems ranging from drug safety monitoring to financial markets and economic systems. A recurring focus is Bayesian and uncertainty-based reasoning (including handling ambiguous or imprecise information) applied to real-world decision-making. His work also spans pharmacovigilance (tracking adverse drug reactions) and the study of open science and publishing.

Bayesian modeling and reasoning under uncertaintyPharmacovigilance and drug safetyStatistical physics models of economic and financial systemsOpen science and publication systemsMachine learning for economic estimation

Publication activity has grown from a couple of papers per year around 2019 to a steadier output of roughly five to seven per year in recent years, averaging about 4.6 over the last five years.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 4.6/year recently
17182019: 2 publications192020: 2 publications202021: 6 publications212022: 3 publications222023: 6 publications232024: 5 publications242025: 7 publications7252026: 2 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×3
  • Journal of Evaluation in Clinical Practice×2
  • International Journal of Environmental Research and Public Health×2
  • International Journal of Approximate Reasoning×2
  • Risk Analysis×2

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 11, 2026.

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