Interactive learning and interventional representations

This program aims to advance interactive models of learning by integrating causal reasoning into adaptive intelligent systems. Its research pillars include causal modeling for interventional learning, bridging observational and experimental data, interactive decision-making, robustness in high-stakes environments, and principled foundations of reliable learning-based systems.