Research

Our research is inherently interdisciplinary, drawing on a wide range of methods — including AI and machine learning, stochastic and computational simulation, engineering models, and social science approaches such as interviews and surveys — to tackle large-scale, uncertain, and complex risk problems across the themes below.

Stochastic Modeling & Simulation of Natural Hazards

Probabilistic models and simulations of wildfires, hurricanes, tornadoes, and earthquakes, incorporating machine learning and deep learning methods.

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Structural Performance & Reliability

Engineering models and simulation to assess the reliability of buildings, bridges, and transmission towers under hazard loads.

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Infrastructure Systems & Community Risk Assessment

Risk assessment of networked infrastructure systems and communities, including the role of insurance and policy.

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Human Decision-Making & Behavior

Understanding individual, community, and institutional decision-making under natural hazard risk using agent-based, game-theoretic, and AI-driven models.

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