Bing Li, professor of statistics at Penn State, has been selected as the Verne M. Willaman Professor of Statistics. The appointment is awarded by the Office of the President of the University, based on the recommendation of the dean of the Eberly College of Science, in recognition of Li’s national and international reputation for excellence in research and teaching
Li's research interests in statistics include sufficient dimension reduction, statistical graphical models, functional data analysis, independent component analysis, order determination, the envelope model, and estimating equations.
Li’s fundamental and pioneering work on dimension reduction for the mean function, for tensor-valued data, for functional data, for categorical data, and his work on nonlinear dimension reduction, have helped to shape the development of the field of Sufficient Dimension Reduction. High dimensionality is a hallmark of modern data, and the demands for efficient dimension reduction methods arise in such diverse applications as pattern recognition, classification, statistical learning, medical research, and bioinformatics. In addition, Li and his coauthors introduced the popular methods such as Contour Regression and Directional Regression, as well as the Envelope Model, which is a general way of conducting dimension reduction in multivariate regression and has undergone momentous development over the recent years.
In the area of statistical graphical models, Li and his coauthors introduced the novel nonparametric functional graphical model where observations on vertices are random functions. This type of data is common in medical research, including fMRI and EEG. They also pioneered the conditional graphical model, which can be used to construct gene networks while taking into account of the effect of a set of predictors. In the area of estimating equation, Li and his coauthors introduced the quadratic inference function, which has been widely used in longitudinal data analysis.
Li was elected a Fellow of the Institute of Mathematical Statistics (IMS) in 2008 and a Fellow of the American Statistical Association (ASA) 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, Journal of the American Statistical Association, Statistica Sinica, and 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.
The Willaman Professorships were established in 1999 by Verne M. Willaman, a 1951 graduate of Penn State. The professorships provide outstanding faculty members with a supplemental source of support to further their research, teaching, writing, and public service.