03 People

I develop machine learning methods for monitoring, simulating, and controlling manufacturing processes. My work focuses on physics-informed deep learning, generative models for uncertainty quantification, and foundation models that can generalize across engineering domains.

Before joining CMU, I was a postdoctoral associate at MIT working with Faez Ahmed and John Hart to study the use of machine learning to assess manufacturability in the design process. I received my Ph.D. from Carnegie Mellon University, where I was advised by Amir Barati Farimani and developed deep learning frameworks for laser powder bed fusion. I hold a B.S.E. in Chemical Engineering from Princeton University.