Thomas Jiralerspong

I am a first year Master’s student in computer science co-supervised by Yoshua Bengio and Doina Precup at Mila and Université de Montréal.

My primary research interests are:

• LLMs as well as how their common sense capabilities can be exploited to train other AI models

• Incorporating ideas from causality, neuroscience and cognitive science into our AI models in order to give them more human-like capabilities such as out-of-distribution generalization and long-term planning/reasoning

• Applying AI to projects that have a concrete positive impact on society, by tackling problems related to drug discovery, healthcare, climate change, autonomous driving, etc.

I completed my Bachelor’s in Honours Computer Science at McGill University where I worked with Professor Blake Richards and Dr. Chen Sun on identifying important states for reinforcement learning in sparse reward environments, as well as with Professor Doina Precup and Dr. Khimya Khetarpal on temporally extended models and planning using option models in pixel environments.

I was also previously an intern at Expedia, Square Enix, Amazon, the Vector Institute and Waabi, as well as a Technical Project Manager for the McGill A.I. Society, where I helped to organize, run, and teach MAIS 202, the Accelerated Introduction to ML Bootcamp every semester.

In 2022, I was a part of McGill’s team in Project X, a machine learning research competition organized by the University of Toronto. Our paper on using deep conservative reinforcement learning for mechanical ventilation treatment (which I co-first authored) received the highest score out of all 25 papers submitted to the competition, winning in the clinical practice category.

I was also fortunate to be selected to participate in the 10th Heidelberg Laureate Forum.

Reach out at thomas.jiralerspong@mila.quebec if there is anything you want to discuss, I’m always happy to talk!