About Zihang
PhD, Biostatistics, Dalla Lana School of Public Health, University of Toronto, 2020
MSc, Biostatistics, Dalla Lana School of Public Health, University of Toronto, 2013
- Biostatistics and data science for kinesiology and health research
- Design and analysis of observational and cohort studies
- Statistical modeling of complex physical activity data from wearable devices
- Functional data analysis and joint modeling of high-resolution activity data
- Integrative analysis of physical activity, biological, behavioral, and environmental determinants of health
Kinesiology and Health Research
Lu, Z., Petersen, C., Dai, R., Vargas, M., Ahmadiankalati, M.†, Sifuentes, E., Miliku, K., Moraes, T., Mandhane, P., Becker, A., Azad, M., Simons, E., Lou, W., Ambalavanan, A., Duan, Q., Turvey, S., and Subbarao, P. (2025). Early preschool wheeze trajectories are predominantly non-allergic with distinct biologic and microbiome traits. Journal of Allergy and Clinical Immunology, 156 (6): 1556-1572. https://doi.org/10.1016/j.jaci.2025.07.034.
Taccardi, D., Zacharias, A.; Gowdy, H.; Knezic, M., Parisien, M., Bisson, E., Fang, Z., Stickley, S., Brown, E., Camire, D., Wilson, R., Singer, L., Daly-Cyr, J., Choiniere, M., Lu, Z., Diatchenko, L., Duan, Q., Ghasemlou, N. (2025). Circadian rhythmicity and neutrophil activation as biomarkers of pain intensity and opioid use. The Journal of Clinical Investigation, 135 (19). https://doi.org/10.1172/JCI188620.
Rossi, A., Chen, Z., Ahmadiankalati, M., Campisi, S., Myrtha, R., Dempsey, K., Jenkins, D., O’Connor, D., El-Sohemy, A., Mandhane, P., Simons, E., Turvey, S., Moraes, T., Lu, Z., Subbarao, P., Miliku, K. (2025). Determining the Interplay of Prenatal Parental BMI in Shaping Child BMI Trajectories: The CHILD Cohort Study. International Journal of Obesity, 49(6): 1-8. https://doi.org/10.1038/s41366-025-01792-8.
Soussi, S., Tarvasmaki, T., Kimmoun, A., Ahmadiankalati, M., Azibani, F., Santos, C., Duarte, K., Gayat, E., Jentzer, J., Harjola, V., Hibbert, B., Jung, C., Johan, L., Levy B., Lu, Z., Lawler, P., Marshall, J., Poss, J., Sadoune, M., Nguyen, A., Raynor, A., Peoc’h, K., Thiele, H., Mathew, R., Mebazaa, A. (2025). Identifying biomarker-driven subphenotypes of cardiogenic shock: Analysis of prospective cohorts and randomized controlled trials. The Lancet Discovery Science eClinicalMedicine, 79. https://doi.org/10.1016/j.eclinm.2024.103013.
Wai, G., Lu, Z., Gill, S., Henderson, I., Auais, M. (2024). Impact of the End PJ Paralysis interventions on patient health outcomes at the participating hospital units in Alberta. Disability and Rehabilitation, 46(26), 6391–6401. https://doi.org/10.1080/09638288.2024.2335662.
Statistical and Data Science Research
Alnajjar, A., Bian, H., Lu, Z. (2026). A Fast Integrative Clustering and Feature Selection for Multiview and High-Dimensional Data. Statistical Methods in Medical Research. In Press.
Lu, Z., Chandra, N. (2024). A Sparse Factor Model for Clustering High-Dimensional Longitudinal Data. Statistics in Medicine, 43(19): 3633-3648. https://doi.org/10.1002/sim.10151.
Ahmadiankalati, M., Boury, H., Subbarao, P., Lou, W., Lu, Z. (2024). Bayesian additive regression trees for predicting childhood asthma in the CHILD cohort study. BMC Medical Research Methodology, 24(1), p.262. https://doi.org/10.1186/s12874-024-02376-2.
Lu, Z., Subbarao, P., Lou, W. (2023). A Bayesian latent class model for integrating multi-source longitudinal data: application to the CHILD cohort study. Journal of the Royal Statistical Society Series C, 73(2): 398-419. https://doi.org/10.1093/jrsssc/qlad100.
Lu, Z., Lou, W. (2022). Bayesian consensus clustering for multivariate longitudinal data. Statistics in Medicine, 41(1): 108-127. https://doi.org/10.1002/sim.9225.
Reviews and Tutorials
Lu, Z. (2025). Clustering Longitudinal Data: A Review of Methods and Software Packages. International Statistical Review, 93(3): 425-458. https://doi.org/10.1111/insr.12588.
Lu, Z., Ahmadiankalati, M., Tan, Z. (2023). Joint Clustering Multiple Longitudinal Features: a Comparison of Methods and Software Packages with Practical Guidance. Statistics in Medicine, 42(29): 5513-5540. https://doi.org/10.1002/sim.9917.
Lu, Z., Lou, W. (2021). Bayesian approaches to variable selection: a comparative study from practical perspectives. International Journal of Biostatistics, 18(1): 83-108. https://doi.org/10.1515/ijb-2020-0130.
Software Packages
Alnajjar, A., Lu, Z. (2024). iClusterVB: an R package for fast integrative clustering and feature selection for high-dimensional data. https://cran.r-project.org/web/packages/iClusterVB/index.html
Tan, Z., Lu, Z., Shen, C. (2022). BCClong: an R package for performing the Bayesian Consensus Clustering model for clustering continuous, discrete and categorical longitudinal data. https://cran.r-project.org/web/packages/BCClong/index.html
KIN8325 Advanced Biostatistics