INFRA Lab develops data-driven methods to improve the resilience, intelligence, and adaptability of transportation and other interdependent infrastructure systems. Our research integrates infrastructure resilience, transportation networks, network science, artificial intelligence, simulation, optimization, risk modeling, and adaptation.
We study cascading failures, infrastructure risk under uncertainty, multimodal network vulnerability, adaptive recovery, and resilience-aware resource allocation. We also develop AI-enabled methods for infrastructure condition assessment and decision support, with the goal of improving infrastructure planning, operations, and recovery under both routine and disruptive conditions.