This Partnerships for Innovation – Mid Career Advancement (PFI-MCA) project enhances disaster response and recovery by improving the capabilities of machine learning and autonomous systems for rapid damage assessment. Frequent, and increasingly severe, natural disasters—such as hurricanes, wildfires, and floods—threaten human health, infrastructure, and natural systems. All natural disasters leave a path of devastation necessitating effective management to mitigate their adverse effects on human life. Any delay in the decision-making process intensifies human suffering and wastes valuable resources. To make well-informed decisions promptly, robust and scalable hazard projection and damage assessment are needed. Using the wealth of available data, including powerful machine learning and autonomous systems, and traditional numerical hazard and vulnerability models, this project aims to build a smart technology with the potential to address the complex problems of rapid response and recovery. The methodologies and findings from this project will have broader applications in fields such as remote sensing, healthcare, and autonomous systems. The project will also contribute to workforce development by designing new curricula, conducting hands-on workshops, and offering lecture series and conference tutorials to engage all Americans. The project aims to build a generalizable model for natural disasters based on large data from autonomous systems and numerical models. The model w