Thomas Jiralerspong
I am a graduate student in computer science co-supervised by Yoshua Bengio and Doina Precup at Mila and Université de Montréal. I previously completed my Bachelor’s in honours computer science at McGill University working with Blake Richards and Doina Precup.
My two main research goals are:
- Building AI systems that have more human-like capabilities such as system 2 thinking, out-of-distribution generalization, long-term planning, and efficient learning.
- Applying AI to projects that have a concrete positive impact on society
Concrete directions I am interested in (and have explored) include:
AI With Human-Like Capabilities
- LLMs and VLMs (papers on causal graph discovery with LLMs and compositionality in LLMs, internship at Occam AI)
- Input-driven learning (paper on bias-only learning)
- Compositionality (paper on compositionality in LLMs)
- Discrete Representations (paper on discovering discrete subgoals for RL)
- Causality (paper on causal graph discovery with LLMs)
- Taking inspiration from cognitive science, neuroscience, and psychology (papers on bias-only learning and discovering discrete subgoals for RL)
- Model-based reinforcement learning (paper on temporally extended tree-search planning)
AI for Positive Impact
- Healthcare (paper on RL for Mechanical Ventilation)
- Climate Change (paper on RL for HVAC Control)
- Autonomous Driving (Internship at Waabi)
- Drug Discovery
I am currently:
- Chairman of the Lab representatives at Mila
- Senior advisor for the McGill A.I. Society
I have previously been:
- Research intern at:
- Occam AI - working on automated SQL query generation using LLMs
- Waabi - working on variational autoencoders for controllable traffic simulation
- Vector Institute - working on reinforcement learning for HVAC control
- Software development intern at
- Undergraduate researcher with
- Selected to be a part of the MIT Brains Minds and Machines Summer Course
- Selected to attend the 10th Heidelberg Laureate Forum
- Co-leader of McGill’s team for Project X, where we received the highest score out of 25 submitted papers for our work on deep reinforcement learning for mechanical ventilation
- Co-organizer and teaching assistant for the McGill A.I. Society’s Accelerated Introduction to ML Bootcamp
- Teaching assistant for:
- Software Systems (COMP206) at McGill
- Representation Learning (IFT6135) at Université de Montréal
In my free time, I enjoy traveling, watching/analyzing good movies, and writing sad songs (check out my (very) amateur music here)!
Reach out at thomas.jiralerspong@mila.quebec if there is anything you want to discuss, I’m always happy to talk!