Dr. Panos Parpas of Credit Suisse will present a seminar in the Engineering Systems Division. Abstract: Most decision models contain some element of uncertainty, either because some important parameters affecting the decision are unknown (e.g. consumer demand for a particular product) or due to model risk (e.g. unobservable parameters of a mathematical model describing a physical process). These situations can be handled within the framework of stochastic programming, optimal control, chance constrained and robust optimization. In this talk we provide an overview of these methodologies and their application to problems from finance, economics and engineering. We also briefly discuss the challenges posed by problems arising from environmental economics, as well as the development of new mathematical modelling and computational tools to address these issues. Numerical algorithms to solve and analyse complex decision making models lie in the core of any successful modelling effort. Therefore, we also discuss algorithms for the solution of such models, including some deterministic and stochastic algorithms for global optimization. The modelling and algorithmic aspects of decision making under uncertainty forms a large part of operations research and therefore attention will be given to the areas where we have made original contributions.