Her work explores data analytics and statistical methods to measure and analyze the risk, reliability, and resilience in critical infrastructure systems. In particular, she has studied data-driven Bayesian methods to predict the occurrence of disruptive events in infrastructure systems and stochastically model the recovery process of the physically disrupted system as well as other interdependent and indirectly impacted systems. She also developed decision analysis tools to assess different preparedness and recovery investment strategies for the protection of civil infrastructures.