I am an Assistant Professor in the Department of Statistics at Brigham Young University. I'm interested in applying inverse optimization to problems where observed human decisions diverge from "optimal" prescriptions estimated by statistical models. Inverse optimization provides a methodology to reconcile optimization models with observed decisions, which can help bridge gaps and create understanding between analysts and decision makers. Most of my experience with these problems have been in sports contexts. Other research interests include Bayesian methods and Markov decision processes.
Previously I was a postdoctoral fellow in the Department of Mechanical and Industrial Engineering at the University of Toronto, working with Timothy Chan on problems at the intersection of inverse optimization and strategy decisions in sports. In 2020, I completed my PhD in statistics under the supervision of Luke Bornn at Simon Fraser University. During my PhD I worked part-time as a basketball operations analyst for the Sacramento Kings.