Eberly College of Science

Statistics department to host free public lecture on data reduction, March 23

Bing Li, Verne M. Willaman Professor of Statistics, will present a public lecture on data reduction on Thursday, March 23, 2023. Credit: Penn State. Creative Commons

UNIVERSITY PARK, Pa. — The Penn State Department of Statistics will host a free, public lecture presented by Verne M. Willaman Professor of Statistics Bing Li, titled “Sufficiency: A Brief History of Data Reduction,” from 4 to 5 p.m. on Thursday, March 23, in Berg Auditorium, 100 Huck Life Sciences Building, on the Penn State University Park campus and virtually on Zoom. A reception will follow the talk in the Verne M. Willaman Gateway to the Sciences on the third-floor bridge connecting the Huck Life Sciences and Chemistry Buildings.

Li’s talk will explore the ideas of data reduction — simplifying data without losing important information — and of data sufficiency — comprehensively summarizing data using relatively few statistics. Modern data is often complex and has high dimension, meaning more features are considered (e.g., height, weight, and genetic information in a medical study) than observations (e.g., individual patients). Statisticians develop methods to reduce this dimensionality and make analysis and interpretation easier. Efficient methods of dimension reduction are useful in a variety of applications, such as pattern recognition, classification, statistical learning, medical research, and bioinformatics. 

Li’s fundamental and pioneering work has helped to shape the development of the field of sufficient dimension reduction. He and his coauthors have introduced several popular statistical methods of dimension reduction, including contour regression, directional regression, and the envelope model. Li's other research interests include statistical graphical models, functional data analysis, independent component analysis, order determination, the envelope model, and estimating equations.

Li was elected a fellow of the Institute of Mathematical Statistics in 2008 and a fellow of the American Statistical Association in 2015. He is the author/coauthor of two recent books, a research monograph on Sufficient Dimension Reduction (CRC Press, 2018) and a textbook on advanced Statistical Inference (Springer, 2019). Li has served as an associate editor of the Annals of Statistics, the Journal of the American Statistical Association, Statistica Sinica, and the Journal of Statistical Planning and Inference. He also has served as a member of the board of directors of the International Chinese Statistical Association.

Li joined the faculty of the Penn State Department of Statistics in 1992. He earned a doctoral degree in statistics at the University of Chicago in 1992, a master's degree in statistics at the University of British Columbia in 1989, and a master's degree and a bachelor’s degree at the Beijing Institute of Technology in 1986 and 1982, respectively.

Last Updated March 16, 2023