Examines the impacts of natural hazards and human-induced crises on public health through the lens of Geospatial Artificial Intelligence (GeoAI). Students utilize machine learning, algorithms and predictive modeling to analyze events such as floods, hurricanes, wildfires, and disease outbreaks. The curriculum emphasizes using big data analytics to assess vulnerability, exposure, and resilience with greater precision than traditional methods. Students will apply Deep Learning Techniques to geospatial data to support real-time emergency response, automate damage assessment, and inform data-driven mitigation strategies. The course also critically examines algorithmic bias to ensure equity in disaster planning and recovery.