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Paul G Dupuis is the IBM Professor of Applied Mathematics at Brown University. He specializes in the applications of probability to control problems, focusing on deterministic and stochastic processes. His research interests prominently include large deviation theory, which explains the occurrence of rare events in random processes, as well as numerical methods such as Markov chain approximations and Monte Carlo simulations. Dupuis has contributed significantly to the field through various publications that explore optimal stopping problems, empirical measures, and risk-sensitive control in queueing networks. His educational background includes a PhD from 1985 and a Master’s from 1982, both in relevant mathematical fields.
Brown University • Providence, RI
Elected to the position of IBM Professor of Applied Mathematics.
Brown University • Providence, RI
Teaching and research in applied mathematics.
Brown University • Providence, RI
Teaching and research in applied mathematics.
Department: Department of Economics