He received his PhD in Pharmaceutical Socioeconomics in 2015 from the University of Iowa. His research primarily involves the surveillance and modelling of infectious diseases using large administrative data sources. His work has also involved the use of novel data sources, including smartphone-connected digital thermometers, for real-time forecasting of influenza outbreaks. In addition, his research has explored the use statistical learning approaches to identify and study diagnostic errors and missed diagnostic opportunities associated with infectious diseases and other acute conditions. He is interested in a wide variety of statistical learning and inferential methods.