optimal control theory

Epidemiological modeling and optimal control

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KAUST

Compartmental epidemiological models are one of the simplest models for the spread of a disease. They are based on statistical models of interactions in large populations and can be effective in the appropriate circumstances. Their application historically and in the present pandemic has sometimes been successful and sometimes spectacularly wrong. In this talk I will review some of these models and their application. I will also discuss the behavior of the corresponding dynamical systems, and discuss how the theory of optimal control can be applied to them. I will describe some of the challenges in using such a theory to make decisions about public policy.

David Evangelista

David Evangelista is a Ph.D. Candidate at King Abdullah University of Science and Technology (KAUST), working in the areas of partial differential equations, mean-field games (MFG), and market microstructure. He is expect to receive a Ph.D. from KAUST in June 2019, under the direction of Professor Diogo A. Gomes. David's research interests are in optimal control theory, nonlinear partial differential equations, MFG, and market microstructure. MFG is a framework to study interactions of a large number of indistinguishable players that play differential games. MFG has become an active research