Biography
I am Philippe Brouillard, a PhD student cosupervised by Dhanya Sridhar and Alexandre Drouin at the Université de Montréal (UdeM) and at Mila, the Quebec Artificial Intelligence Institute.
My research interests include causal discovery, causal representation learning, machine learning, and how to combine them!
Interests
- Causal discovery
- Causal representation learning
- Machine learning
Education
PhD in Computer Science, 2025 (expected)
UdeM
MSc in Computer Science, 2021
UdeM
BSc in Mathematics, 2017
UdeM
BSc in Psychology, 2014
UQAM
Publications
(2025).
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications.
In CLeaR 2025.
(2023).
Climateset: A large-scale climate model dataset for machine learning.
In NeurIPS 2023 - Datasets and Benchmarks.
(2022).
Typing Assumptions Improve Identification in Causal Discovery.
In CLeaR 2022.
(2020).
Differentiable Causal Discovery with Interventional Data.
In NeurIPS 2020.
(2020).
Gradient-based Neural DAG Learning with Intervention.
In Causal Learning for Decision Making workshop, ICLR 2020.
(2020).
Gradient-Based Neural DAG Learning.
In ICLR 2020.
Talks
Contact
- philippebrouillard@gmail.com
- 2900 Edouard Montpetit Blvd, Montreal, CA