Miguel Costa is a postdoctoral researcher at the Technical University of Denmark, where he develops decision-support tools for climate adaptation policy making. His current work combines reinforcement learning and agent-based simulation to identify optimal sets or sequences of adaptation strategies. This framework aims to reveal dynamic links between flooding events, transport systems, public health, and wellbeing – ultimately supporting decision-making that maximizes societal impact. Miguel holds a PhD (magna cum laude) in Transportation Systems and an MSc in Electrical Engineering from Instituto Superior Técnico. His research interests lie at the intersection of artificial intelligence and transport, focusing on how machine learning can be used to objectively characterize complex phenomena while also capturing individuals’ subjective experiences. By bridging this gap, he aims to inform planning and policy decisions that are both data-driven and human-centered.
This speaker will host a keynote on the 12th September