I develop computational tools and methods in disaster risk analysis for identifying, analyzing, and communicating extreme events. In particular, I am interested in low-probability, high-impact, data-sparse events at the intersection of natural hazards, the built environment, and society. I focus on the nonlinear impacts in disasters that can have significant implications for our understanding of past, current, and future risk at the city and regional scales. I use both probabilistic and event-based approaches to study risk through multiple lenses, including engineering, hazard science, and social science. This work contributes towards disaster preparedness and mitigation, ultimately as a way to build more resilient communities.