Liqun Diao

Research Assistant Professor
Liqun Diao

Contact Information:
Liqun Diao

Research Interests

I am interested in developing and applying data-driven statistical methods and machine learning algorithms to advance knowledge in fields including medicine, public health, and insurance. I have been working on a broad spectrum of areas including recursive partitioning learning, causal inference, dependence modelling, Bayesian methods, and two-phase design.

Education/biography

  • 2013 Ph.D. in Statistics - Biostatistics, University of À¶Ý®ÊÓƵ, À¶Ý®ÊÓƵ, Canada
  • 2009 M.Math in  Statistics - Biostatistics, University of À¶Ý®ÊÓƵ, À¶Ý®ÊÓƵ, Canada
  • 2007 B.Econ in Statistics, Renmin University of China, Beijing, China

Professor Diao has joined the Department of Statistics and Actuarial Science at the University of À¶Ý®ÊÓƵ since July, 2015 as an assistant professor.

Selected Publications

  • Yang, C., Cook, R.J., Diao, L., 2021+. Secondary Analysis and Sequential Design of Two-Phase Studies. Under Revision for Statistical Methods in Medical Research.    
  • Diao, L., Meng, Y., Weng, C., Wirjanto, T., 2021+. Common Mortality Trend Model and Mortality Prediction. Under Revision for North American Actuarial Journal. 
  • Diao, L., Yi, Y., 2021+. Classification Trees for Misclassified Responses. Under Revision for Journal of Classification.    
  • Yang, C., Diao, L., Cook, R.J., 2021+. Regression Trees for Interval-censored Failure Time Data Based on Censoring Unbiased Transformations and Pseudo-Observations. Under Revision for Canadian Journal of Statistics.
  • Yang, C., Cook, R.J., Diao, L., 2021+. Adaptive Two-Phase Designs: Some Results on Robustness and Efficiency. Revision Submitted to Statistics in Medicine.  
  • Zhuang, H., Diao, L., Yi, Y., 2021+. Polya Tree Based Nearest Neighbour Regression. Revision Submitted to Statistics and Computing.  
  • Cuerden, M., Diao, L., Cotton, C., Cook, R.J., 2021+. Multiple Imputation and Doubly Weighted Estimating Equations for Causal Inference with Incomplete Subgroup Data. Revision Submitted to Biostatistics and Epidemiology.
  • Zhuang, H., Diao, L., Yi, Y., 2021. A Bayesian Nonparametric Mixture Model for Grouping Dependence Structures and Selecting Copula Functions. Econometrics and Statistics (In Press).  
  • Diao, L. Cook, R.J., 2021. Nested Doubly Robust Estimating Equations for Causal Analysis with an Incomplete Effect Modifier. Canadian Journal of Statistics (In Press).
  • Yang, C., Diao, L., Cook, R.J., 2021. Survival Trees for Current Status Data. Proceedings of AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and Applications, Proceedings of Machine Learning Research 146, 83-94  
  • Zhuang, H., Diao, L., Yi, Y., 2021. A Vine Copula Model for Climate Trend Analysis using Canadian Temperature Data. Journal of Data Science. 19(1) 37–55.  
  • Diao, L., Meng, Y., Weng, C., 2021. A DSA Algorithm for Mortality Forecasting. North American Actuarial Journal. 25(3) 438-458 
  • Zhuang, H., Diao, L., Yi, Y., 2020. A Bayesian Hierarchical Copula Model. Electronic Journal of Statistics. 14(2), 4457-4488.
  • Steingrimsson, J.A.∗, Diao, L.*, Strawderman, R.L., 2019. Censoring Unbiased Regression Trees and Ensembles. Journal of the American Statistical Association 114(525), 370-383. 
  • Diao, L. and Weng, C., 2019. Regression Tree Credibility Model. North American Actuarial Journal 23(2), 169-196.
  • Steingrimsson, J.A., Diao, L., Molinaro, A.M., Strawderman, R.L., 2016. Double Robust Survival Trees. Statistics in Medicine 35(20), 3595-3612.   
  • Diao, L. and Cook, R.J., 2014. Composite Likelihood for Joint Analysis of Multiple Multistate Processes via Copulas. Biostatistics 15(4), 690-705. 
  • Diao, L., Cook, R.J. and Lee, K.-A., 2013. A Copula Model for Marked Point Processes. Lifetime Data Analysis 19(4), 463-489.