The Resilient Networks Group focuses on learning and decision-making for resilient and sustainable societal-scale infrastructures such as transportation, energy, and logistics systems.
Our research is driven by the inefficiencies and disruptions faced by societal-scale infrastructure systems, including congestion and environmental externalities, reliability and security failures, and climate risks. We build analytic techniques and computational tools in data-driven optimization, stochastic control, game theory, and theory of economic incentives. Our work is aimed at helping users and operators of infrastructure systems make better decisions in the presence of uncertainties, both random and adversarial.