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. (2026). Deep neural network with a smooth monotonic output layer for dynamic risk prediction. Statistics in Medicine 45:e70401. DOI: 10.1002/sim.70401; PMID: 41640287; PMCID: PMC12873558. Python code: 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; PMID: 39208951; PMCID: PMC12056756.
  • 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; PMID: 37672739; PMCID: PMC10484142.
  • 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; PMID: 36694118; PMCID: PMC9872364.
  • Zhou, Z., & Sang, P. (2022). Continuum centroid classifier for functional data. Canadian Journal of Statistics 50:200–220. DOI: 10.1002/cjs.11624. R code: 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. (Best Paper Award) 2021 International Conference on Data Mining Workshops (ICDMW) 517–526. 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. R code: 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. R code: 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. R code: 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.
  • Li, C., Xu, X., Zhong, S., Zhou, Z., & Lian, H. (2026). Tensor elliptical partial least squares under non-Gaussian distributions.
  • Yang, Y., & Zhou, Z. (2026). Asymmetric transfer in energy-based models for financial time series.

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)