Frontiers in Causal Inference

Causal inference underpins research across the social, health and environmental sciences. This workshop gathers researchers and practitioners advancing its methods and applications to address the design of complex experiments, overt and hidden bias in observational studies, data integration from diverse sources, treatment-effect heterogeneity, and the use of AI to scale and enhance causal analysis. Bringing together experts from statistics, biostatistics, epidemiology, economics, computer science and related fields, it highlights recent progress, fosters cross-disciplinary dialogue and looks for new directions in designing and analysing causal studies in data-rich settings, with implications for evidence-based policy and decision-making in health, economics and the social sciences. All registrants, online and in person, receive Zoom links and can attend online. In-person seats are limited and in-person registrants must wait for an invitation from IMSI before travelling; invited in-person participants pay a non-refundable fee of $25 (students) or $50 (non-students).