Adaptive AI for Predicting Urban Dynamics under Climate Change

Focused on climate-induced data drift, this project develops AI models for transportation and urban prediction that remain robust during extreme events like hurricanes or heatwaves. By integrating continual and meta-learning with climate models, they aim to improve real-time forecasting for mobility and energy systems, supporting smart city resilience and policy planning.