In graduate school, my research has focused on medical decision making. I formulate, analyze, and solve models regarding prediction, screening, and treatment decisions. Since such problems tend to be probabilistic in nature, much of my work has used stochastic models such as Markov decision processes, bandit models, and stochastic optimization. Simulation is a keystone of being able to evaluate my solutions. I have also used statistical methodologies such as survival analysis and changepoint detection.
In addition to operations research and math, I have assisted with research on STEM education, studying effective rubric design and alternative classroom teaching environments (such as the flipped classroom).
In undergraduate at Oberlin College, I had a much wider range of research topics. I spent a great deal of time conducting ecology research; with different projects on fire ants and crayfish. In my senior year I studied convex optimization for my math honors project.