Abstract: Vinyas Harish's (University of Toronto, Expected MD/PhD 2025) research focuses on the ways in which machine learning can complement traditional epidemiological perspectives and methods applied at the population and clinical levels, with an emphasis on promoting health systems resilience in the context of emergencies. Vinyas explores these topics in several ways, including a qualitative study on the ethics of private sector ML4H collaborations with stakeholders across technical, ethics/governance, and clinical domains, an examination of the utility of pandemic preparedness indices through cluster analysis, and the high-resolution prediction of COVID-19 transmission using mobility data and environmental covariates. Historically, Vinyas has also examined medical device safety and feasibility testing as well as the efficacy of novel methods for teaching clinicians image-guided procedures.