Postdoctoral Fellows

1. Tingxuan Wu
2. Ming-Ming Zhang
3. Jinhong Shi

Doctoral Students

1. Jing Wang, Ph.D in Biotatistics, Sept 2024-present, co-supervised with Prof. Li Xing
2. Tingxuan Wu, PhD in Biostatistics, 2023, co-supervised with Prof. Cindy Feng

   Thesis: Residual Diagnostics and Statistical Inference for Shared Frailty Models

   Employment: Forestry Statistical Analyst, Ministry of Environment, Government of Saskatchewan

   Publications:

   • Wu, T., Feng, C., Li, L. (2024). Cross-validatory Z-Residual for Diagnosing Shared Frailty Models. The American Statistician 0, 1–17. [PDF]; [Free Reprints]; [slides]; [Z-residual on Github]; [Demo]
   • Wu, T., Li, L., Feng, C. (2024). Z-residual diagnostic tool for assessing covariate functional form in shared frailty models. Journal of Applied Statistics 0, 1–31. [PDF]; [Z-residual on Github]; [Demo] [slides]
   • Wu, T., Feng, C., Li, L. (2024). A Comparison of Estimation Methods for Shared Gamma Frailty Models. Statistics in Biosciences 0, 1–22. [PDF]
3. Wutao Yin, Ph.D., September 2019 - December 2021, co-supervised with Prof. Fang-Xiang Wu

   Thesis: Artificial Intelligence Based Methods for Autism Spectrum Disorder Diagnosis from fMRI Data

   Current position: Associate Professor, Ocean Institute, Northwestern Polytechnical University, Taicang Jiangsu, China

   Publication:

   • Wutao Yin, Longhai Li, Fang-Xiang Wu, A semi-supervised autoencoder for autism disease diagnosis, Neurocomputing, Volume 483, 2022, Pages 140-147.
   • Yin, W., Li, L., Wu, F.-X., 2022. Deep learning for brain disorder diagnosis based on fMRI images. Neurocomputing 469, 332–345.
   • Yin, W., Li, L., Wu, F.-X., 2021. A Graph Attention Neural Network for Diagnosing ASD with fMRI Data, in: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). pp. 1131–1136.
4. Lai Jiang, Ph.D., 2015

   Thesis: Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure

   Employment: Postdoctoral fellow at Lady Davis Institute, Jewish General Hospital, McGill University in Montreal.

   Publication:

   • Jiang L, Greenwood CMT, Yao W, Li L. Bayesian Hyper-LASSO Classification for Feature Selection with Application to Endometrial Cancer RNA-seq Data. Scientific Reports. 2020 Jun 16;10(1):9747.

Master's Students

1. Dananji Shashiprabha, M.Sc. in Statistics, Sept 2023-present
2. Effie Wuqian Gao, M.Sc. in Biostatistics, Sept. 2022- August 2024

   Thesis: Z-residuals for Checking Bayesian Hurdle Models

   Employment: Senior Data and Forecasting Analyst, Health Ministry, Government of Saskatchewan

3. Hao Hu, M.Sc., 2022, co-supervised with Prof. Li Xing

   Thesis: Identifying Risk Factors for Cognitive Decline Using Statistical Learning Techniques and Functional Data Analysis

   First Employment: Senior Statistician in Health Ministry in a Chinese goverment

4. Lina Li, M.Sc, May 2021 to September 2021, MITACS project supervisor

   Publication: Real-time estimates of the reproduction rate (R_t) of Canadian provinces.

5. Man Chen, M.Sc., 2021.

   Thesis: Association between Gut Microbiome and Parkinson's Disease Revealed by Sparse Learning.

   Publication:

   • Dong M, Li L, Chen M, Kusalik A, Xu W. Predictive analysis methods for human microbiome data with application to Parkinson's disease. PLOS ONE. 2020 Aug 24;15(8):e0237779.

   First Employment: AI Engineer at Super GeoAI Technology Inc.

6. Mei Dong, M.Sc., 2019, co-supervised with Prof. Lloyd Balbuena

   Thesis: Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease

   Employment: Senior Research Analyst at the University of Toronto.

   Publications:

   • Dong M, Li L, Chen M, Kusalik A, Xu W. Predictive analysis methods for human microbiome data with application to Parkinson's disease. PLOS ONE. 2020 Aug 24;15(8):e0237779.
   • Bai, W., Dong, M., Li, L., Feng, C., Xu, W., 2021. Randomized quantile residuals for diagnosing zero-inflated generalized linear mixed models with applications to microbiome count data. BMC Bioinformatics 22, 564.
7. Xiaoying Wang, M.Sc., 2019

   Thesis: Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data

8. Tingxuan Wu, M.Sc. in biostatistics, 2018, co-supervised with Prof. Cindy Feng

   Thesis: Randomized Survival Probability Residuals for Assessing Parametric Survival Models

   Employment: PhD student at the University of Saskatchewan

   Publication:

   • Li, L., Wu, T., Feng, C. (2021). Model diagnostics for censored regression via randomized survival probabilities. Statistics in Medicine 40, 1482–1497. [PDF]; [R Functions and Demonstration]; [slides-1]; [slides-2];
9. Wei Bai, M.Sc., 2018, co-supervised with Prof. Cindy Feng

   Thesis: Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data

   First Employment: Statistical Programmer, Everest Clinical Research, Markham, Ontario.

   Present Position: Lead Statistical Analyst, Bayer Pharmaceuticals, Ontario, Canada

   Publication:

   • Bai, W., Dong, M., Li, L., Feng, C., Xu, W., 2021. Randomized quantile residuals for diagnosing zero-inflated generalized linear mixed models with applications to microbiome count data. BMC Bioinformatics 22, 564.
10. Arash Shamloo, M.MATH (project-based), 2017

    Project: Randomized quantile residuals for accelerated failure time models

    Employment: Research assistant, College of Pharmacy and Nutrition, University of Saskatchewan.

11. Yunyang Wang, M.Sc., 2016

    Thesis: Comparison of Stochastic Volatility Models Using Integrated Information Criteria

    Employments: Statistician at Montreal office of Evidera (a PPD company), Montreal, QC

    First Employment: Intern at the PathWise Solutions, AON Securities, Toronto.

12. Alireza Sadeghpour, M.Sc., 2016, co-supervised with Prof. Cindy Feng

    Thesis: Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models

    First Employment: Statistician at Health Canada, Ottawa.

    Publication:

    • Feng C, Li L, Sadeghpour A. A comparison of residual diagnosis tools for diagnosing regression models for count data. BMC Medical Research Methodology. 2020 Jul 1;20(1):175.
13. Naorin Islam, M.Sc., 2016, co-supervised wtih Prof. Khan

    Thesis: Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects

    First Employment: Research assistant, College of Pharmacy and Nutrition, University of Saskatchewan.

14. Shi Qiu, M.Sc., 2015 (co-supervised with Cindy X. Feng)

    Thesis: Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping

    First Employment: "Data Service Specialist" at IRD Inc. in Saskatoon.

    Present Position: Statistician, Mabwell Therapeutics, Inc., Shanghai, China

    Publications:

    • Longhai Li, Cindy X. Feng, and Shi Qiu* (2017), Estimating Cross-validatory Predictive P-values with Integrated Importance Sampling for Disease Mapping Models. [slides], [R code], arXiv:1603.07668, Statistics in Medicine, Volume 36, Issue 14, Pages 2220-2236.
    • Li, L., Qiu, S.*, Zhang, B.*, and Feng, C.X. (2016). Approximating Cross-validatory Predictive Evaluation in Bayesian Latent Variables Models with Integrated IS and WAIC. arXiv 1404.2918, [slides], Statistics and Computing, Volume 26, Issue 4, pp 881-897.
15. Masud Rana, M.Sc., 2012 (co-supervised with Prof. Shahed Khan)

    Thesis: Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data

    First Employments: Biostatistician at Clinical Research Support Unit by College of Medicine of University of Saskatchewan.

    Publication:

    • A Statistical Investigation to Monitor and Understand Atmospheric CFC Decline with the Spatial-Longitudinal Bent-Cable Model.
16. Zhengrong Li, M.Sc., 2012.

    Thesis: A Non-MCMC Procedure for Fitting Dirichlet Process Mixture Models

    First Employment: Data Service Specialist at IRD Inc. in Saskatoon.

Undergraduate Students

1. Lina Li, undergraduate research assistant, 2020

   Project title: Investigation of Randomized Quantile Residuals

2. Xinyu Liu, undergraduate research assistant, 2019

   Project title: Development of an R package for Bayesian Hyper-LASSO Logistic Regression

   Software:
   HTLR: Bayesian Logistic Regression with Heavy-Tailed Priors, [CRAN page], [Github page]. HTLR was listed in the top 40 new packages in October 2019 by R views of Rstudio.

3. Jian Su, undergraduate research assistant, 2018

   Project title: Development of Bayes Predictive Models based on Generalized Linear Mixed Models with application to microbiome data

4. Jiaqi Xiao, undergraduate research assistant, 2015

   Project title: Application of iIS and iWAIC to Compare Models for Economic Data.

   Employment: M.Sc. student at Queen's University

5. Zhouji Zheng, undergraduate research assistant, 2014 and 2015

   Project title: Application of Importance Sampling to Compare Bayesian Stochastic Volatility Models.

   Employment: M.Sc. student at the University of Toronto

6. Bei Zhang, undergraduate research assistant, 2013

   Project title: Cross-validatory Model Checks with iIS for Logistic Random Effect Models

   Publication: Approximating Cross-validatory Predictive Evaluation in Bayesian Latent Variables Models with Integrated IS and WAIC.