Hi! I'm a third-year PhD student in computer science (fast-tracked from masters) at Université de Montréal/Mila supervised by Gauthier Gidel and supported by NSERC.
Previously, I did my undergrad at McGill where I majored in computer science with minors in mathematics and economics. I also interned as a software engineer at Google, Amazon Robotics and Squarepoint Capital.
I am currently working on soft variants of reinforcement learning and potential applications to multi-agent problems. In the past, I've worked on generative models and their evaluation.
Generally, any topic that bridges computer science, economics and mathematics will be of interest!
News
- [August 2025] Passed my Predoc 3 (proposal) exam!
- [May 2025] Received the FRQNT Doctoral Scholarship (declined).
- [April 2025] Received the NSERC Postgraduate Scholarship – Doctoral (PGS D).
Selected Publications
1. Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning | [Github]
arXiv 2025 (under review).
2. General Causal Imputation via Synthetic Interventions
Workshop on Causal Representation Learning, NeurIPS 2024.
3. Expected Flow Networks in Stochastic Environments and Two-Player Zero-Sum Games | [Github]
ICLR 2024.
4. On the Stability of Iterative Retraining of Generative Models on their own Data
ICLR 2024 (spotlight).
Awards
- NSERC Postgraduate Scholarship – Doctoral (PGS D): $40 000/year.
- FRQNT Doctoral Scholarship (declined): $25 000/year.
Projects
Gale-Shapley Interactive Simulation | Interactive Simulation
An interactive, step-by-step, visualization of the Gale-Shapley algorithm in action for random preferences.
Python for Biologists | Github
An introductory Python course for biologists explaining how to get set up, the basic elements of the language and progressively harder exercises.