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Sang Michael Xie Image could not be loaded.

I am a Computer Science Ph.D. student studying Machine Learning at Stanford University, advised by Percy Liang and Tengyu Ma.
My research focuses on data-centric methods for language models and understanding pretraining and adaptation to downstream tasks, including emergent behavior such as in-context learning. I have also worked on pretraining and self-training methods for robust machine learning.

Previously, I was a FY2019 NDSEG Fellow and a Student Researcher at Google Brain, working with Adams Wei Yu, Hieu Pham, and Quoc Le. I received both my B.S. with departmental honors and M.S. in Computer Science from Stanford in 2017, where I am grateful to have worked with Stefano Ermon on the first deep learning and transfer learning methods for sustainability, particularly in poverty mapping using satellite imagery. My work has been recognized in Scientific American's 10 World Changing Ideas, publication in flagship venues such as Science, and covered by media outlets including the New York Times, The Washington Post, Reuters, BBC News, IEEE Spectrum, and The Verge.

[Music] Email: xie AT

Selected Publications


2023 2022 2021 2016-2020


I have mentored the following amazing undergraduate/master's researchers: