Guan Yu

  • Associate Professor, Director of PhD Program
  • Faculty in Biostatistics

My primary research focuses on the methodological development and theoretical assessment of statistical machine learning and high-dimensional statistics driven by real biomedical problems. My current research interests include multi-modality data integration, high-dimensional inference, non-parametric/semi-parametric statistics, transfer learning, and uncertainty quantification for predictions. I have participated in various interdisciplinary collaborative research relevant to Alzheimer’s disease, cancer, autoimmune diseases, and environmental health.


2016 | University of North Carolina at Chapel Hill, Chapel Hill, NC | PhD in Statistics

2011 | Nankai University, Tianjin, China | MS in Statistics

2008 | Nankai University, Tianjin, China | BS in Mathematics


BIOST2025 | Biostatistics Seminar | Fall 2022, Spring 2023

BIOST2044 | Introduction to Statistical Theory 2 | Spring 2023

  • 2020 Outstanding Young Researcher Award, International Chinese Statistical Association
  • 2017 Travel Award, Biometrics Section, American Statistical Association (ASA)
  • 2015 Teaching Award, Department of Statistics and Operations Research, UNC
  • 2015 Student Paper Award, Statistical Learning and Data Mining Section, ASA
  • 2014 Young Statisticians in Business and Industry Award, ASA and National Institute of Statistical Sciences
  • 2014 Student Paper Award, Statistical Computing and Graphics Sections, ASA
  • 2012 Cambanis-Hoeffding-Nicholson Award, Department of Statistics and Operations Research, UNC
Selected Publications
  • Jialu Li, Guan Yu, Qizhai Li, and Yufeng Liu (2022). “Sample-Wise Combined Missing Effect Model with Penalization”, Journal of Computational and Graphical Statistics, accepted.
  • Guan Yu and Surui Hou (2022). “Integrative Nearest Neighbor Classifier for Block-missing Multi-modality Data”, Statistical Methods in Medical Research, 31(7), 1242-1262.
  • Guan Yu, Haoda Fu, and Yufeng Liu (2022). “High-dimensional Cost-constrained Regression via Non-convex Optimization”, Technometrics, 64(1), 52-64.
  • Yufei Wu and Guan Yu (2020). “Weighted Linear Programming Discriminant Analysis for High-dimensional Binary Classification”, Statistical Analysis and Data Mining, 13(5), 437-450.
  • Guan Yu, Liang Yin, Shu Lu, Yufeng Liu (2020). “Confidence Intervals for Sparse Penalized Regression with Random Designs”, Journal of the American Statistical Association, 115(530), 794-809.
  • Guan Yu, Quefeng Li, Dinggang Shen and Yufeng Liu (2020). “Optimal Sparse Linear Prediction for Block-missing Multi-modality Data without Imputation”, Journal of the American Statistical Association, 115(531), 1406-1419.
  • Jianyu Liu, Guan Yu, Yufeng Liu (2019). “Graph-based Sparse Linear Discriminant Analysis for High Dimensional Classification”, Journal of Multivariate Analysis, 171, 250-269.
  • Junlong Zhao, Guan Yu, and Yufeng Liu (2018). “Assessing Robustness of Classification using Angular Breakdown Point”, The Annals of Statistics, 46(6B), 3362-3389.
  • Guan Yu and Yufeng Liu (2016). “Sparse Regression Incorporating Graphical Structure among Predictors”, Journal of the American Statistical Association, 111, 707-720.
  • Ruizhang Huang, Guan Yu, Zhaojun Wang, Jun Zhang and Liangxing Shi (2013). “Dirichlet Process Mixture Model for Document Clustering with Feature Partition”, IEEE Transactions on Knowledge and Data Engineering, 25, 1748-1759.
  • Guan Yu, Changliang Zou, and Zhaojun Wang (2012). “Outlier Detection in the Functional Observations with Application to Profile Monitoring”, Technometrics, 54, 308-318.