Taster Session: How Can AI Help to Reduce Disaster Risk? - Saman Ghaffarian

In this session, Saman will explore how AI-based tools and methods, including deep learning, explainable AI, digital twins, and AI-integrated simulation, can improve disaster preparedness, response, and recovery. The lecture will highlight how geospatial data, machine learning, and socio-economic modelling can provide deeper insights into disaster vulnerability and resilience, offering new approaches to reducing disaster risks. In addition to his research, Saman teaches across both undergraduate and postgraduate programmes at the Department of Risk and Disaster Reduction (RDR). He leads IRDR0047: Geospatial Data Science and IRDR0010: Advanced Hazards at the postgraduate level, focusing on the application of geospatial data and AI in understanding and managing complex disaster risks. At the undergraduate level, he teaches IRDR0021: Social and Geospatial Data Analysis, equipping students with the skills to analyse and apply geospatial data in disaster and social risk contexts.