Nitarshan is a PhD student at the University of Cambridge, where he is advised by Ferenc Huszár and David Krueger, and generously funded by a scholarship from Twitter.

His research focus is on empirical approaches to understanding how deep learning works, especially at scale, and he is also interested in policy considerations for the responsible development of AGI.

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