LabCompass

Weibin Mo

Mathematics · Purdue University West Lafayette

OpenAlex
Early career · publishing since 2020
Statistical Methods and InferenceAdvanced Causal Inference TechniquesFace and Expression RecognitionStatistical Methods and Bayesian InferenceStatistical Methods in Clinical Trials

Publications

12

Citations

54

Est. group size

—

Recurring co-author estimate

Active years

6

Publishing since 2020

Research summary
AI-generated

Weibin Mo works in statistics and data science, developing methods for making personalized decisions from data, such as choosing optimal treatments or product assortments while accounting for uncertainty and robustness to model errors. This research combines statistical theory with tools like causal inference and graphical models to help analyze complex data in areas such as healthcare and business decision-making.

Individualized treatment decision rulesDistributionally robust statistical learningCausal inferenceGraphical models for statistical dependenceAssortment and decision optimization

Publication activity began around 2020 and has continued at a modest, fairly steady pace of roughly one to three papers per year through 2025.

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

Publication cadence
Publications per year over the last 10 years — averaging 1.4/year recently
1718192020: 2 publications202021: 3 publications3212022: 1 publication222023: 1 publication232024: 3 publications3242025: 2 publications2526
Recent publications
Publishes in
  • arXiv (Cornell University)×5
  • Journal of the American Statistical Association×2
  • Chemico-Biological Interactions×1
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)×1
  • ICSA book series in statistics×1
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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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