Colloquium - Kean Ming Tan - October 23, 2025

Speaker: Kean Ming Tan, University of Michigan
Date/Time: Thursday, October 23, 2025, 10:00 AM - 11:00 AM ET

Title: Expected Shortfall Regression and Its Applications

Abstract: The expected shortfall is defined as the average over the tail below (or above) a certain quantile of a probability distribution. The expected shortfall regression provides powerful tools for learning the relationship between a response variable and a set of covariates while exploring the heterogeneous effects of the covariates. In the health disparity research, for example, the lower/upper tail of the conditional distribution of a health-related outcome, given covariates, is often of importance. Motivated by the idea of using Neyman-orthogonal scores to reduce sensitivity to nuisance parameters, we consider a computationally efficient two-step procedure for estimating the expected shortfall regression coefficients. We establish explicit non-asymptotic bounds on the resulting estimator that lay down the foundation for performing statistical inference under different scenarios.  

Bio: Kean Ming Tan is currently an associate professor at the University of Michigan.  His research interest focuses on developing methodologies for analyzing heterogeneous data.  

Website: www.keanmingtan.com