I am a Lecturer for computational finance and operations research in the Department of Computing at Imperial College London.
My research is currently focussed on optimal decision making under uncertainty. Almost any real-life decision problem in economics, engineering, or finance depends on uncertain parameters, whose values are known only up to a probability distribution or (or a set of rival probability distributions). Typically, the uncertain parameters are revealed sequentially in time, and decisions are taken at each instant when new data is observed. Finding the best decision strategy over time with respect to some given objective criterion and on the basis of the available (incomplete) information about the uncertain parameters gives rise to a stochastic dynamic optimization problem, also referred to as a stochastic programming problem.
My primary research interests are focused on the development of efficient computational methods for the solution of large-scale stochastic programs and the design of approximation schemes which ensure their computational tractability. I am particularly interested in tackling those challenging problems which involve a large number of decision stages as well as a high-dimensional state vector. This research is primarily application driven, the main application areas being energy systems, finance, and engineering.