We are interested in analyzing Large-Scale Complex Systems under Uncertainty using stochastic modeling, Markov Decision Theory and Game Theory with applications in the transportation, supply chains, climate and health, production and manufacturing, and telecommunication networks.
Our current research and teaching programs focus on the areas of modeling, optimization and control of stochastic systems, such as transportation, telecommunication and supply chain networks. These are dynamical systems, operating under internal and external uncertainties, which are generally considered to be large-scale and complex. We are interested in developing new models that will realistically represent complex phenomena such as congestion; traffic flow randomly interrupted by incidents; or retailer’s behavior when selling substitutable products. We are also interested in developing optimization algorithms for adjustment of inventories in supply chains, for incident response and resource allocation in incident and emergency management, for dynamic traffic flow management under incidents, and for stochastic games.