Wang Xueqin is a Chair Professor at the Department of Statistics and Finance, School of Management, University of Science and Technology of China (USTC).  He earned his bachelor's degree in mathematics from Nankai University in 1997 and his Ph.D. in statistics from Binghamton University in 2003.

He has received support from the National Natural Science Foundation for Excellent  Young Scholars and was selected for the Ministry of Education's New Century Excellent Talents Program. He is an Elected Member of the International Statistical Institute (ISI), a member of the Teaching Steering Committee for Statistics Programs in Higher Education under the Ministry of Education, and an editorial board member for international statistical journals such as  SII and STARF. He has also received the Second Prize in Natural Science at the Higher Education Outstanding Scientific Research Achievement Award (ranking first).

Professor Wang’s research focuses on the statistical theory, methodology, and computation in artificial intelligence, particularly in optimal subset selection problems, statistical inference for non-Euclidean data, and statistical modeling and inference based on a combination of mechanical models and data-driven approaches. In the past five years, he has made original foundational and technological contributions to the field of variable selection. His work on the best subset selection, a longstanding classical problem, has led to significant standard-setting results. He proposed the concept of the metric distribution function, which lays the foundation for statistical inference in metric spaces and enriches the research toolkit in this area. He has developed several open-source R and Python packages, such as Ball and abess, with over 1.5 million downloads. He has authored over 120 research articles, with 20 published in top-tier journals in statistics, machine learning, and medicine, including JASA, AOS, JRSSB, PNAS, IJOC, JMLR, and Nature Genetics.