I am a founding AI Research Scientist at Prometheus building the Artificial General Engineer to fundamentally change how we design and engineer the physical world. My work spans generative modeling, model scaling, foundation models and open datasets, with the goal of using AI to accelerate scientific discovery and engineering.

Most recently at Meta FAIR, I led efforts on AI for Science — including universal machine-learning interatomic potentials (UMA), generative models for materials (FlowLLM, FlowMM), and some of the largest open datasets in the field. Together, these efforts accelerate materials discovery by orders of magnitude.

I also led fastMRI, a collaboration between Meta and NYU Langone to accelerate MRI scanning using AI. Our methods achieve up to 4× acceleration with no loss in diagnostic accuracy and have become the clinical standard for accelerated MRI worldwide.

Earlier, I built and led the speech research team at Meta FAIR, where we trained some of the earliest multi-billion parameter speech models and developed self-supervised methods that served billions of users across Meta's products. Before Meta, I was part of the team at Baidu that built Deep Speech 2, one of the first end-to-end neural speech recognition systems.

I hold a Master's in Language Technologies from Carnegie Mellon University.

Selected Publications