Speaker: Ehsan Karim, UBC School of Population and Public Health

This talk will explore the distinct methodological approaches for prediction versus causal questions, highlighting the recent excitement around integrating prediction and machine learning tools into causal inference. We will demonstrate their application using real-world databases to address challenges such as residual confounding and model misspecification.

Ehsan Karim is an Assistant Professor in the UBC School of Population and Public Health. His current research focuses on developing causal inference and pharmacoepidemiological methodologies, and applying data science approaches to large healthcare data analysis to answer real-world comparative effectiveness research questions.