Xuan Bi
Contact
Education:
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BS 2011Mathematics, Tsinghua University
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PhD 2016Statistics, University of Illinois at Urbana-Champaign
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Postdoctoral Associate 2018Biostatistics, Yale University
Expertise:
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Statistics & Machine Learning
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Data Privacy
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AI Safety and Security
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Recommender Systems
Biography
Dr. Xuan Bi is an Associate Professor of Information and Decision Sciences at the Carlson School of Management, University of Minnesota. His research centers on the development and application of statistical machine learning methods and AI technologies to address large-scale, real-world, business and scientific problems. His research interests lie broadly in trustworthy machine learning and AI, with a particular focus on data privacy, AI safety and security, and recommender systems. His works have been published in leading academic journals and conferences, including Journal of the American Statistical Association, Annals of Statistics, Management Science, Information Systems Research, Journal of Machine Learning Research, INFORMS Journal on Computing, Journal of Econometrics, NeurIPS, ICML, and ICLR. And he serves as Associate Editor for the Journal of the American Statistical Association.
Dr. Xuan Bi holds a Bachelor of Science in Mathematics from Tsinghua University, and a Ph.D. in Statistics from the University of Illinois at Urbana-Champaign. During his doctoral training, Dr. Xuan Bi provided statistical consulting services to over 60 clients across academia and industry. Prior to joining the University of Minnesota, Dr. Xuan Bi was a Postdoctoral Associate at Yale University.
Selected Works & Activities
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Tang, X., Bi, X. and Qu, A. (2020). Individualized Multilayer Tensor Learning with An Application in Imaging Analysis. Journal of the American Statistical Association.
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Feng, L., Bi, X. and Zhang, H. (2020). Brain Regions Identified as Being Associated with Verbal Reasoning through the Use of Imaging Regression via Internal Variation. Journal of the American Statistical Association.
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Bi, X., Feng, L., Li, C. and Zhang, H. (2021). Modeling pregnancy outcomes through sequentially nested regression models. Journal of the American Statistical Association.
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Zhang, Y., Bi, X., Tang, N.-S. and Qu, A. (2021). Dynamic tensor recommender systems. Journal of Machine Learning Research.
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Bi, X., Adomavicius, G., Li, W. and Qu, A. (2021). Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness. INFORMS Journal on Computing.
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Bi, X., Gupta, A. and Yang, M. (2023). Understanding partnership formation and repeated contributions in federated learning: An analytical investigation. Management Science.
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Chen, J., He, L., Liu, H., Yang, Y. and Bi, X. (2023). Background music recommendation on short video sharing platforms. Information Systems Research.