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My primary research interests are on the use of Benders decomposition, column generation, and graphical models to solve complex large-scale problems encountered in real-world applications including personnel staffing and scheduling and attended home services operations management (e.g. home healthcare and attended home delivery). Moreover, I am also interested in decision making under uncertainty, specifically on the use of stochastic programming to solve problems involving stochasticity in the model parameters (e.g. uncertainty in the demand for services) and on the use of data science/machine learning, for data-driven decision making.