My research goals are to be disconnected from technology and the internet – attending film festivals, drinking wine at a beach somewhere warm while reading interesting books, and enjoying the company of good friends. Please talk to me about movies, long-distance running, food and pastries, world events, Georgist socio-economic policy, or literally anything that is not focused on tech.

Testimonials

“Nitarshan is a PhD student in Cambridge, previously a student at MILA, a top machine learning lab in Canada. He is interested in topics of AI safety among others. He also has an impressive repertoire of about five things he can say in Hungarian (and maybe even more).”

“Beware of Nitarshan in general… He asks thought-provoking questions that will make you rethink your whole research agenda”

“Quite fun and interesting. Those are his parameters.”

“Nitarshan’s wardrobe is definitely proof of discerning consumption”

Bookshelf

Darwin among the Machines (1863)
Science, the Endless Frontier (1945)
The Human Use of Human Beings (1950)
Computing Machinery and Intelligence (1950)
Can We Survive Technology? (1955)
Spring Snow (1969)
Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983-1993 (2002)

Underpaid Labour

GitHub | Google Scholar | Semantic Scholar | OpenReview

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics
ICML 2022 Workshop (DataPerf)
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker

Evaluating the Text-to-SQL Capabilities of Large Language Models
arXiv Code
Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau

Myriad: A Real-World Testbed to Bridge Trajectory Optimization and Deep Learning
arXiv Code
Nikolaus Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon

Self-Supervision for Data Interpretability in Image Classification and Sample Efficiency in Reinforcement Learning
MSc Thesis
Nitarshan Rajkumar

Pretraining Representations for Data-Efficient Reinforcement Learning
arXiv Code NeurIPS 2021 ICLR 2021 Workshop (SSL-RL) (Rejected from ICML 2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Phil Bachman, Aaron Courville

In Search of Robust Measures of Generalization
arXiv Code NeurIPS 2020
Karolina Dziugaite, Alex Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Dan Roy

Unpaid Labour

Weight Uncertainty in Neural Networks