👋 Hello there, welcome to Kan Chen’s homepage
Kan Chen is a postdoctoral research fellow jointly mentored by Prof. Xihong Lin at the Biostatistics Department of Harvard T.H. Chan School of Public Health, and Prof. Zhonghua Liu at the Biostatistics Department of Columbia University. Prior to this, Kan recieved his PhD in Applied Mathematics and Computational Science from University of Pennsylvainia and dual MA in Statistics and Data Science from the Wharton School, jointly mentored by Prof. Dylan Small and Prof. Qi Long. Kan’s research spans causal inference, causal machine learning and AI, and collaborative scientific applications.
Recent News
[July 2025] Paper pulished by Biometrics: Sensitivity Analysis for Attributable Effects in Case-2 Studies.
[June 2025] Paper published by Journal of the Royal Statistical Society Series A: Using Case Description Information to Reduce Sensitivity to Bias for the Attributable Fraction Among the Exposed.
[May 2025] Presented at ACIC 2025. Titles: “The Blessing of Multiple Mediators: Taming Unmeasured Confounding Bias via Factor Analysis.” and “Sensitivity Analysis for Attributable Effects in Case2 Studies.”
[May 2025] Presented at NJIT statistics seminar. Title: “The Blessing of Multiple Mediators: Taming Unmeasured Confounding Bias via Factor Analysis.”
[January 2025] Paper published in Nature Medicine: Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.
[December 2024] Paper published at JASA: Combining Broad and Narrow Case Definitions in Matched Case-Control Studies: Firearms in the Home and Suicide Risk.
[August 2024] Presented at JSM 2024 (Statistics and Health Policy Section). Title: “A Differential Effect Approach to Partial Identification of Treatment Effects.”
[April 2024] Spotlight paper accepted by ICML 2024 for the paper Discret: Synthesizing faithful explanations for treatment effect estimation.
[April 2024] Received the IMS New Researcher Travel Award.