Disaster Risk Analysis Lab
Probabilistic modeling and decision support for resilient infrastructure systems
Engineering resilient infrastructure under extreme events
We develop scalable probabilistic and AI-enabled methods to understand and reduce the impacts of rare, uncertain, and cascading hazards on interconnected infrastructure systems. Our work supports more resilient decisions for infrastructure planning, adaptation, and recovery.
Research
We study how extreme hazards disrupt infrastructure systems and develop computational methods to improve resilience. Our work spans healthcare, transportation, energy, housing, and the scientific methods needed to analyze rare and cascading events.
Healthcare Infrastructure & Earthquake Emergency Response
Connecting seismic damage, transportation, hospitals, and patient access.
Transportation Infrastructure & Mobility
Understanding mobility, access, and infrastructure disruption during disasters.
Energy Infrastructure
Modeling power-system damage, outages, recovery, and distributed resilience.
Housing Infrastructure & Community Resilience
Studying how housing vulnerability, adaptation, and recovery evolve over time.
Computational Methods, Scientific AI & Digital Twins
Developing scalable methods for rare-event analysis, uncertainty, optimization, and infrastructure digital twins.
Our Team
Our team brings together researchers working across infrastructure resilience, disaster risk, scientific AI, and decision-making under uncertainty.
