Header Return to Main Conference Page
Return to Home Page


To view the presenter's presentation, click on their talk title.

Dr. Eugene Feinberg

Stony Brook University

Professor Eugene A. Feinberg received Ph.D. in Probability and Statistics from Vilnius University, Lithuania, in 1979. Between 1976 and 1988 he held research and faculty positions in the Department of Applied Mathematics at Moscow University of Transportation. After holding a one-year visiting faculty position at Yale University, he joined Stony Brook University where he is currently Professor of Operations Research at the Department of Applied Mathematics and Statistics.His research interests include stochastic models of operations research, Markov Decision Processes, and industrial applications of Operations Research and Statistics. He has published more that 60 papers and edited the Handbook on Markov Decision Processes. His research is partially supported by the National Science Foundation, Department of Energy, Office of Naval Research, New York Office of Science, Technology and Academic Research, and industry. Since 1999, he has been working on electric energy applications. He has developed several accurate electric load forecasting methods and software that are being used by the industry.

Stochastic Modeling and Supercomputing for Smart Grids

Eugene Feinberg (Department of Applied Mathematics & Statistics, Stony Brook University), James Glimm (SBU), Janos Hajagos (LIPA), Jiaquao Hu (SBU), Eting Yuan (SBU) This talk discusses two aspects of Smart Grids. The first one is the processing of large data sets on energy consumption, transmission, and distribution in real time. The second is the handling of additional uncertainties due to intermittent energy generation. Supercomputing provides natural tools for dealing with large data sets and uncertainties. We shall describe several problems including load forecasting for distribution networks and the stochastic unit commitment problem.