
I am a tenure-track Assistant Professor at Department of Statistics and Data Science (primary) and 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, 2019-2022; Advisor: Michael I. 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: Game theory and LLM, Mechanism design, Incentive theory, Matching markets.
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Statistical Foundations for Dynamical Models: Optimization dynamics, ODE and PDE methods.
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Uncertainty Quantification with ML Systems: Multimodal inference, Distribution-free inference, Kernel-based learning.
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Biomedical Discovery and Applications: Neuroimaging data analysis, Diabetes study, Kidney exchange.
Editorial Service​
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Associate Editor, Stat, 2022-
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Editorial Board, Journal of Machine Learning Research, 2022-
News​
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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