School of Chemical Engineering
Forney Hall of Chemical Engineering
480 Stadium Mall Drive
West Lafayette, IN 47907
Parameter estimation for infectious diseases plays an important role in the understanding of disease dynamics and decision-making in public health policies. Generally, parameters of interest are estimated by solving large-scale nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) optimization problems based on discrete- or continous-time disease models. Such problems, however, are very challenging due to their large scale and strong nonlinearity. This research focuses on developing advanced modeling techniques and solution strategies for disease-related optimization problems.
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