I currently pursuing a DPhil in computer science at a small university just outside of London as a Rhodes Scholar. My over-arching research interest is in developing a theoretical understanding of machine learning algorithms. At the moment I'm looking at learning invariances exhibited by data, but I'm also interested in RL and robustness in machine learning more generally. My supervisors at Oxford are Marta Kwiatkowska and Yarin Gal.
I spent the previous summer working on a theoretical analysis of distributional reinforcement learning at Google Brain, working with Pablo Castro and Marc Bellemare. For examples of code written at 4 in the morning at a hackathon, visit my github profile. For a resume with the projects I actually want potential employers to see, visit my LinkedIn page.
Before I hopped across the pond, I did my undergrad in Math & CS at McGill University, doing research with the RL Lab. As a student there I got to work with some awesome organizations, including the university chapter of WUSC, a national NGO that runs some incredible programs, this super cool hackathon, and the McGill Tribune, McGill's best (although I'm slightly biased) student-run newspaper. If you're at McGill University right now, you should definitely check out all three.