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Weibin Mo

Weibin Mo

Assistant Professor in Management
Quantitative Methods


Ph.D. in Statistics, University of North Carolina at Chapel Hill, 2021
B.B.A. in Business Administration, B.S. in Mathematics, Nankai University, 2016


Weibin Mo is an Assistant Professor of Management in Quantitative Methods area at Purdue School of Business. His research interests mainly focus on statistical methodologies in machine learning, personalized decision making, causal inference and semiparametric inference, and robust optimization. The major application areas of his research are precision medicine, inventory management, and assortment. 

Before joining Purdue, Weibin Mo has been working as an Applied Scientist on overstock inventory management at Supply Chain Optimization Technologies (SCOT), Amazon

  • MGMT 30500 (Spring 2023)
  • MGMT 69000 (Fall 2022)

Phone: (765) 494-4855
Office: KRAN 711

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