About

I am on the job market for postdoc, faculty, and research scientist positions with a start date of late spring / early summer 2023.

I’m currently a Research Intern at Google Brain with Been Kim, working on theoretical guarantees for interpretable machine learning. I’m also a PhD candidate in Statistical Sciences at the University of Toronto, advised by Daniel Roy. My PhD was supported by an NSERC Doctoral Canada Graduate Scholarship and the Vector Institute. I received my BSc in Financial Modelling from Western University in 2018.

My research area is broadly the theoretical foundations of statistical decision making, with applications to both statistical methodology and machine learning algorithms. I develop new algorithms and provide provable guarantees with a focus on making principled, data-based decisions that balance the need for robustness in high-stakes settings with the need for strong performance in practice.