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Sang (Michael) Xie

I am a Computer Science Ph.D. student studying Machine Learning at Stanford University. Previously, I received my B.S.H., M.S. in Computer Science 2017 at Stanford University, specializing in Artificial Intelligence and Theory. My interests include making AI accessible to all potential application fields, increasing the interpretability of machine learning models, and increasing the robustness of AI models. My subject interests revolve around how theory from statistics, optimization, algorithms, and other math can be applied to machine learning. In my undergraduate career, I conducted research under Prof. Stefano Ermon in the Stanford Artificial Intelligence Laboratory, working on machine learning with limited data, including transfer learning and spatiotemporal machine learning models for semi-supervised learning, applied to predicting poverty measures in Africa from satellite imagery. I also helped to start the Sustainability and AI (SUSTAIN) lab at Stanford.




Workshop Papers