I am a tenure-track Assistant Professor at the Department of Statistics and Data Science and the Department of Biostatistics, UCLA.
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My research interest focuses on the area of economics and machine learning, blending game theory with online learning and developing predictive machine learning models in economic contexts. Another area of focus is statistical machine learning, especially in dynamical models, kernel-based learning, and uncertainty quantification, with applications to neuroimaging, diabetes, and kidney exchanges.
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Recruiting: UCLA graduate students and visitors interested in machine learning, mechanism design, or biostatistics research, feel free to contact me.
Xiaowu Dai (戴晓æ¦)
E-mail: dai@stat.ucla.edu
Education ​​
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University of California, Berkeley
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Postdoc in Computer Sciences and Economics, Berkeley AI Research (BAIR) Lab, 2019-2022; Advisor: Michael Jordan. I also worked with Lexin Li and Robert M. Anderson.
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University of Wisconsin-Madison
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Ph.D. Statistics, 2019; Advisor: Grace Wahba. M.S. Computer Sciences, 2018; M.S. Mathematics, 2015.
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Shanghai Jiao Tong University
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B.S. Mathematics, with distinction, 2014; Advisor: Ya-Guang Wang. B.A. Economics, double degree, 2014.
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Research Interests [Papers]​​
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Economics and Machine Learning: Matching markets, Mechanism design, Incentive Theory.
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Learning in Dynamical Models: ODE and PDE models and inference, Optimization dynamics.
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Learning and Uncertainty Quantification: Kernel methods, Uncertainty quantification, Causal machine learning.
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Biomedical Discovery and Applications: Neuroimaging data analysis, Diabetes study, Kidney exchanges.
Editorial Service​
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Associate Editor, Stat, 2022-
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Editorial Board, Journal of Machine Learning Research, 2022-
Contact​
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Office: 8917 Math Sciences Bldg
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Phone: 424-259-5110
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Email: dai@stat.ucla.edu
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Mail: 8125 Math Sciences Bldg #951554
University of California
Los Angeles, CA 90095-1554
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