Dr. Mahdi Panahi 

Short Abstract / Description
This workshop examines the role of Artificial Intelligence in improving natural hazard prediction in the context of climate-driven environmental change. Participants will learn modern AI methods including traditional natural artificial intelligence, hybrid ensembles, deep learning architectures, and optimization techniques applied to global hazard datasets. The workshop highlights best practices for integrating remote sensing, climate reanalysis products, and geospatial variables into unified predictive frameworks. Through demonstrations and guided exercises, attendees will gain practical experience implementing robust, interpretable AI models for hazard susceptibility, exposure analysis, and spatial risk mapping across diverse geographic regions.