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Department of Computer Science and Technology

I am a PhD student at the University of Cambridge, where I am advised by Ferenc Huszár and David Krueger, and generously funded by a scholarship from Twitter. My research focus is on empirical approaches to understanding how deep learning works, especially at scale. I am also interested in policy considerations for the responsible development of AGI.


I completed an MSc at the Université de Montréal and Mila, where I was advised by Laurent Charlin and worked at the intersection of self-supervised learning and deep reinforcement learning. I previously spent a few years working at Airbnb on site performance and anti-fraud initiatives. Prior to that, I did my undergrad in Software Engineering and Computer Science at the University of Waterloo. During that time I had the opportunity to study on exchange at the Hong Kong University of Science and Technology, and work at startups in Toronto and San Francisco as well as a financial services firm in New York.


Artificial General Intelligence


Pretraining Representations for Data-Efficient Reinforcement Learning (NeurIPS 2021)

Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Phil Bachman, Aaron Courville

In Search of Robust Measures of Generalization (NeurIPS 2020)

Karolina Dziugaite, Alex Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Dan Roy

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