Lingzhou Xue is a Professor of Statistics and Associate Director of the National Institute of Statistical Sciences. He is the Core Faculty of both Statistical Learning and Data Mining (SLDM) Lab and Microbiome Data Science (MDS) Lab. He received his B.Sc. in Statistics from Peking University in 2008 and his Ph.D. in Statistics from the University of Minnesota in 2012. He was a postdoctoral research associate at Princeton University from 2012-2013.
His research interests include high-dimensional statistics, nonparametric statistics, statistical and machine learning, large-scale optimization, and statistical modeling in biomedical, environmental, and social sciences. His papers have been published in top-tier journals in statistics and data science, including The Annals of Statistics, Biometrics, Biometrika, eLife, IEEE Transactions on Signal Processing, INFORMS Journal on Optimization, Journal of the American Statistical Association, Journal of Machine Learning Research, Journal of Accounting & Economics, Journal of Business & Economic Statistics, Journal of Econometrics, Environmental Science & Technology, Monthly Weather Review, Nature Materials, Psychometrika, Proceedings of the IEEE, etc. His research has been supported by the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Health Effects Institute (HEI). Currently, he serves as an Associate Editor for the Journal of the American Statistical Association, Stat, ACM Transactions on Probabilistic Machine Learning, and Data Science in Science. He was a Guest Co-Editor for the Special Issue on the 2020 Symposium for Data Science and Statistics of Stat.
He was an Elected Fellow of the Institute of Mathematical Statistics (IMS) in 2024, an Elected Fellow of the American Statistical Association (ASA) in 2023, and an Elected Member of the International Statistical Institute (ISI) in 2016. He received the inaugural Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award in 2021, the inaugural Bernoulli Society New Researcher Award in 2019, and the International Consortium of Chinese Mathematicians Best Paper Award in 2019.
His advisees have received the 2023 Nonparametric Statistics Best Student Paper Award, 2021 Physical and Engineering Sciences + Quality & Productivity Best Student Paper Award, 2019 Statistics in Imaging Best Student Paper Award, 2018 Risk Analysis Best Student Paper Award, 2018 Business and Economic Statistics Best Student Paper Award, and 2016 Statistical Learning and Data Science Best Student Paper Award from the American Statistical Association (ASA), 2016 Best Student Paper Award from the International Chinese Statistical Association (ICSA), 2018 Science for Social Good Fellowship from IBM Research, 2021 Alfred P. Sloan Minority Ph.D. Scholar, as well as 2021 Alumni Association Dissertation Award, 2020 Patil-Taillie Scholarship, 2018-2020 Computation, Bioinformatics, and Statistics Fellowship, 2019 Erickson Discovery Grant, 2019 Patil-Taillie Scholarship, 2018 J. Keith Ord Scholarship, and 2015-2017 Academic Computing Fellowship from Penn State University.