I’m a research scientist at Meta Superintelligence Labs, in the Fundamental AI Research (FAIR) pillar. I work on Large Language Models (LLMs) and AI Agents. My current work includes:
Frontier LLM Development: I work on mid-/post-training of Meta’s Muse model family, focusing on agentic reinforcement learning for coding and tool use tasks.
Fundamental LLM Research: I lead and conduct research projects covering topics like long-horizon reinforcement learning, recursive self-improvement, and computational world models. Previously I also published work on multimodal reasoning, safety post-training, and hallucination mitigation.
I received my PhD in Computer Science from the University of Toronto, where I studied automated understanding and generation of creative language use. During my PhD, I was fortunate to intern at Meta FAIR and Google Research.
PhD in Computer Science
University of Toronto
MSc in Computer Science
University of Toronto
BSc in Computer Science and Statistics
McGill University