Xiaowu Dai (戴晓æ¦)
E-mail: dai@stat.ucla.edu
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, which blends game theory with online learning and provides statistical models for microeconomics. Another area of focus is statistical machine learning, especially in kernel-based learning, dynamical models, and uncertainty quantification. I am also interested in biostatistics applications, including 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.
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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Uncertainty Quantification and Causality: Kernel methods, Conformal prediction, Causal inference.
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Biomedical Discovery and Applications: Neuroimaging data analysis, Diabetes, Kidney exchanges.
Editorial Service​
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Associate Editor, Stat, 2022-
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Editorial Board, Journal of Machine Learning Research, 2022-