Xuan Bi

Dr. Xuan Bi is an Associate Professor at the Department of Information and Decision Sciences, Carlson School of Management, University of Minnesota, with an affiliate appointment at the School of Statistics and core membership in the Data Science and AI Hub. He focuses on trustworthy machine learning, particularly in

• Recommender Systems
• Data Ethics
• AI Trustworthiness

His academic background includes a B.S. in Mathematics from Tsinghua University (2011) and a Ph.D. in Statistics from University of Illinois at Urbana-Champaign (2016) under Prof. Annie Qu, followed by postdoctoral work at Yale University (2016-2018) under Prof. Heping Zhang.

Dr. Bi's research addresses real-world business and scientific challenges through statistical and machine learning methodologies, with recent publications covering

• Large-scale tensor factorization
• Adversarial learning in AI
• Differential privacy mechanisms
• Imaging genetics
• Genomic studies of schizophrenia

His work has been published in top-tier venues including JASA, Annals of Statistics, Management Science, and NeurIPS, with funding from the National Science Foundation and Cisco Systems.

Scientific accolades include

• Gordon B. Davis Young Scholar Award (2024)
• ASA Student Paper Award (2016, 2017)
• Horace W. Norton Prize (2014)
• Multiple teaching awards (2019-2021)