Machine learning for social good in environment: Developing an advanced warning system for predicting extreme weather events
Floods, the most prevalent of natural disasters, impact over 250 million people annually, leading to economic damages of approximately $10 billion. Our project aims to address this pressing issue by developing an advanced warning system that leverages multi-modality generative machine learning. By investigating the potential of extreme weather events, particularly flooding, and integrating valuable data on green, grey, and blue infrastructure, we strive…
Read More