Computation & AI for Risk and Resilience

The increasing frequency and severity of natural hazards, combined with aging infrastructure and growing interdependencies among critical systems, pose significant challenges to the safety and functionality of civil infrastructure and the communities they serve.

The CARR Lab at Rensselaer Polytechnic Institute develops advanced computational methods to address these challenges. We advance surrogate modeling, machine learning, and probabilistic analysis techniques to enable efficient uncertainty quantification, risk assessment, and resilience-informed decision making for complex infrastructure systems. Our work bridges methodological innovation in computational modeling with real-world applications spanning transportation networks, power systems, and urban communities exposed to earthquakes, hurricanes, floods, and other extreme events.