I'm 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. Right now I'm trying to get models to learn what we want them to learn, 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've noticed that a lot of emails from future graduate students asking about applying to Oxford have been getting blocked by my spam filter, so if you're applying to Oxford and want to talk you can also DM me.
I spent the summer after my undergrad working on a theoretical analysis of distributional reinforcement learning at Google Brain, working with Pablo Castro and Marc Bellemare (who are both fantastic, and if you get a chance to intern at Brain Montreal you should definitely look into working with them). 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.