CHSPR Seminar | Can Causal Inference be Enhanced by Leveraging Machine Learning?

Insights from Real-world Health Data Analyses

Ehsan Karim, UBC School of Population and Public Health
Annie Wang, UBC Computer Science

Tuesday, Oct 15, 2024
12-1 pm PDT
View the presentation slides

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.

Annie Wang is a first-year master’s student in the Computer Science department in the UBC Faculty of Science. Her research interests include causal inference and human-centered AI.

Register in advance for this seminar. After registering, you will receive a confirmation email containing information about joining the meeting. A light lunch will be provided for in-person registrants.