About Me

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 models (Muse Spark, Muse Glimmer), focusing on agentic reinforcement learning and synthetic data generation for coding and tool use tasks.

• Fundamental LLM Research: I lead and conduct research projects covering topics like long-horizon reinforcement learning, agentic synthetic data generation, and recursive self-improvement. Previously I also published papers on multimodal reasoning and LLM post-training alignment.

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.