I am a Senior Research Scientist at NVIDIA Research in the Language and Cognition Research Group working with Yejin Choi. Prior to this, I was the first full-time employee of the NV Toronto AI Lab led by Sanja Fidler. I obtained my PhD in Machine Learning and Computer Vision from the University of Toronto, where I was advised by Prof. Sanja Fidler. During my PhD, I was also affiliated with the Vector Institute for AI. In 2018, I completed my Master’s Degree in Applied Computing at the same institution. I am honored to have received the 2020 Microsoft Ada Lovelace Fellowship.

My current research focuses on reasoning models — synthetic data, inference-time scaling, agents, and RL — with specific interest in the role of data and reasoning on the path toward AGI and Physical AI. Over the last decade, much of my work has been shaped by the following question: what data do we need to scale intelligence, and how do we synthesize it? From early vision systems (Polygon-RNN++, Meta-Sim, f-DAL) to today’s reasoning models (Golden Goose, LPT, LGT) — data continues to be the lifeblood of AI. My PhD thesis, Visual Learning using Synthetic Data, laid the foundation for learning from synthetic data in the visual domain. More broadly, my research interests span representation learning, multimodal models, and generative modeling. I also have a long-standing interest in scene understanding and low-level vision.

Graduate students interested in internships at NVIDIA are welcome to contact me with a CV and summary of research interests.