I'm a PhD student at Mila and University of Montreal, advised by Aishwarya Agrawal. This summer I'll join Qualcomm Research in Amsterdam as an intern. I work on generative models, world models, and reinforcement learning. My research is supported by the Fonds de recherche du Québec – Nature et technologies (FRQNT).
Research
Scaling on internet text has taken us remarkably far — and so the path to physical intelligence is now vivid. I believe in the manifesto for the era of experience, and I work on generative world models. To make them work for agents in a big world, we need better representations and better policy-gradient algorithms for scaling experience.
A few deep-learning "topics" I like the most: diffusion and flow-based models; the target network trick from RL; and SSL, including asymmetric views in BYOL.
Selected publications
See Google Scholar for the full list. *denotes equal contribution.
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One Flow-Transformer for Imagination and Control
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Grounding Computer-Use Agents from Demonstrations
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The Promise of RL for Autoregressive Image Editing
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Rendering-Aware RL for Vector Graphics
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CTRL-O: Language-Controllable Object-Centric Representations
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VisMin: Visual Minimal-Change Understanding
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Hard Negatives to Enhance Visio-Linguistic Compositional Understanding
Misc
Talks
Slides from a few talks I put extra care into. Mostly for our group at Mila.
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Few-step diffusion modeling
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Score-based generative models and diffusion models
Academic Service
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Co-organizerMila, 2026
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IFT 6765 – Links between Computer Vision and LanguageGraduate Student InstructorMila, 2025