Dr. Gorgulu's research focuses on data-driven optimization with applications to healthcare and public operations. His research focuses on constructing data-driven, realistic models and developing predictive and prescriptive analytics to support decision-making under uncertainty. His research methodologies include stochastic modeling and optimization, queueing theory, interpretable machine learning, and Markov decision processes. From a practical point of view, he has been collaborating with practitioners from different healthcare organizations to identify problems with real-world impact and develop implementable solutions. His research has been funded by several funding agencies including NSERC and SSHRC. He teaches statistics, predictive analytics and optimization.
