PEER-REVIEWED

  • Golandouz, H., Doupe, M., Zhou, Z., & Lix, L. (2026). Evaluating accuracy and fairness of machine-learning osteoporosis case definitions in linked administrative data. 2026 International Population Data Linkage Network Conference (IPDLN), in press.
  • Zhou, Z., Deng, Y., Liu, L., Jiang, H., Peng, Y., Yang, X., Zhao, Y., Ning, H., Allen, N., Wilkins, J., Liu, K., Lloyd-Jones, D., & Zhao, L. (2025). Deep neural network with a smooth monotonic output layer for dynamic risk prediction. Statistics in Medicine, in press. doi:10.1002/sim.70401 (with Python code at github.com/ZhiyangGeeZhou/DDH-SMOL)
  • Liu, J., Zhou, Z., Cheng, X., Zhang, D., Li, L., Zhang, X., & Vangeepuram, N. (2024). Food insecurity trends and disparities according to immigration status in the US households, 2011–2021. Preventive Medicine 187:108121. doi:10.1016/j.ypmed.2024.108121
  • Liu, J., Zhou, Z., Cheng, X., & Vangeepuram, N. (2023). Geographic and sociodemographic variations in prevalence of mental health symptoms among US youths, 2022. American Journal of Public Health 113:1116–1119. doi:10.2105/AJPH.2023.307355
  • Deng, Y., Liu, L., Jiang, H., Peng, Y., Wei, Y., Zhou, Z., Zhong, Y., Zhao, Y., Yang, X., Yu, J., Lu, Z., Kho, A., Ning, H., Allen, N. B., Wilkins, J. T., Liu, K., Lloyd-Jones, D. M., & Zhao, L. (2023). Comparison of state-of-the-art neural network survival models with the pooled cohort equations for cardiovascular disease risk prediction. BMC Medical Research Methodology 23:22. doi:10.1186/s12874-022-01829-w
  • Zhou, Z., & Sang, P. (2022). Continuum centroid classifier for functional data. Canadian Journal of Statistics 50:200–220. doi:10.1002/cjs.11624 (with R code at github.com/ZhiyangGeeZhou/CCC)
  • Zhao, Y., Wang, Y., Liu, J., Xia, H., Xu, Z., Hong, Q., Zhou, Z., & Petzold, L. (2021). Empirical quantitative analysis of COVID-19 forecasting models. 2021 International Conference on Data Mining Workshops (ICDMW) 517–526. (Best Paper Award) doi:10.1109/ICDMW53433.2021.00069
  • Zhou, Z. (2021). Fast implementation of partial least squares for function-on-function regression. Journal of Multivariate Analysis 185:104769. doi:10.1016/j.jmva.2021.104769 (with R code at github.com/ZhiyangGeeZhou/fAPLS)
  • Zhou, Z. (2019). Functional continuum regression. Journal of Multivariate Analysis 173:328–346. doi:10.1016/j.jmva.2019.03.006 (with R code at github.com/ZhiyangGeeZhou/Functional-continuum-regression)
  • Zhou, Z., & Zhang, R. (2014). A generalized general minimum lower order confounding criterion for nonregular designs. Journal of Statistical Planning and Inference 148:95–100. doi:10.1016/j.jspi.2013.12.003 (with R code at github.com/ZhiyangGeeZhou/G-GMC)
  • Wang, W., Gong, D., Zhou, Z., & Guo, Y. (2012). Robustness of the aerosol weekly cycle over Southeastern China. Atmospheric Environment 61:409–418. doi:10.1016/j.atmosenv.2012.07.029

UNDER-REVIEW

  • Zhou, Z., & Zhao, L. (2025). Parsimonious joint model of survival outcome and multiple longitudinal biomarkers.

PREPRINTS

INVITED PRESENTATIONS

FUNDING

  • Principal Investigator, NSERC Discovery Grants (with the Discovery Launch Supplement, 2022/Apr/01–2027/Mar/31; terminated early on 2023/Sep/01 due to relocation)