Miguel Liu-Schiaffini

I’m a second-year PhD student in the Computer Science Department at Stanford, advised by Prof. Stefano Ermon. I’m broadly interested in generative modeling and developing mathematically-principled methods for scientific applications.

Previously, I was a member of Anima Anandkumar’s AI + Science lab at Caltech, where I did my undergraduate studies. In 2024, I was a research intern in the Learning and Perception group at NVIDIA Research. Prior to Caltech, I also spent two years as a research intern at the University of Texas Institute for Geophysics.

During my undergrad, my research focused on the theory and applications of neural operators and operator learning, particularly in their application to solving partial differential equations (PDEs). For instance, I have worked on developing neural operators for forecasting in chaotic, non-stationary, and stochastic time-dependent systems.

I am grateful to be supported by the NSF Graduate Research Fellowship. During my undergraduate studies, I was supported by the Mellon Mays Undergraduate Fellowship and was honored to receive the 2024 Barry Goldwater scholarship.