Yufeng Liu, PhD
Dr. Yufeng Liu’s research is focused on developing statistical/computational methods and tools with applications to complex and high dimensional data. In particular, he is interested in statistical machine learning methods and theory. His previous and current works include statistical machine-learning methods for classification, regression, graphical models, clustering and variable selection as well as various topics related to The Cancer Genome Atlas (TCGA) data and imaging. He is a member of the Cancer Genetics Program at the UNC Lineberger Comprehensive Cancer Center.
Honors and Awards
Ruth and Phillip Hettleman Prize for Artistic and Scholarly Achievement
2010, University of North Carolina at Chapel Hill
Faculty Early Career Development (CAREER) Award
2008–2013, National Science Foundation
Junior Faculty Development Award
2006, University of North Carolina at Chapel Hill
Ransom and Marian Whitney Research Award, Statistics
2004, The Ohio State University
Student Paper Competition Winner
2003, American Statistical Association’s Sections on Statistical Computing and Graphics
Distinguished University Fellowship
1999 & 2004, The Ohio State University
Dr. Liu teaches a variety of classes in the Department of Statistics and Operations Research.
High dimensional data analysis
Associate Editor (10/2011 – present), Statistica Sinica
Guest Editor (2011 – 2012), A Special Issue for Statistical and Its Interface
Associate Editor (1/2008 – 9/2011), Journal of the American Statistical Association (Theory and Methods)
Program Chair-Elect, Program Chair, Section on Statistical Learning and Data Mining of ASA, 2012-2013
Best paper award committee member for Journal of Nonparametric Statistics, 2009- 2010
Local Scientific Coordinator for the Program on Statistical and Computational Methodology for Massive Datasets at SAMSI, NC, 2012 – 2013
Faculty fellow on the Program of High Dimensional Inference and Random Matrices at SAMSI, NC, 2006 – 2007
Soft or hard classification? Large margin unified machines. Liu, Y., Zhang, H.H., Wu, Y. (2011). Journal of the American Statistical Association, 106.
Adaptive weighted learning for unbalanced multicategory classification. Qiao, X. and Liu, Y. (2009). Biometrics, 65.
Probability estimation for large margin classifiers. Wang, J., Shen, X., and Liu, Y. (2008). Biometrika, 95.
Quantile regression in Reproducing Kernel Hilbert Spaces. Li, Y., Liu, Y., and Zhu, J. (2007). Journal of the American Statistical Association, 102.
Multicategory psi-learning. Liu, Y. and Shen, X. (2006). Journal of the American Statistical Association, 101.
- PhD, Statistics, The Ohio State University, 2004
- MS, Statistics, The Ohio State University, 2001
- BS, Statistics, Nankai University, 1999