My work has two connected parts. In statistical methodology, I develop methods for functional, surface-based, network, and spatiotemporal data, along with inference tools that make AI-generated biomedical data reliable to use in scientific analysis. In scientific and collaborative work, I apply these methods with collaborators in neuroimaging (Alzheimer's disease, psychosis, and brain development), epidemiology and public health (COVID-19 forecasting), and experimental design for vaccine immunology.
Full list: Google Scholar | Selected publications are as follows.
Shao, Y., Gu, Z., Yu, S. (2026). Structured Nonparametric Variational Inference for Dependent Latent Modeling: Applications to Spatial Transcriptomics. Annals of Applied Statistics, accepted. [arXiv]
Consagra, W., Gu, Z., & Zhang, Z. (2026). NeuroPMD: Neural Fields for Density Estimation on Product Manifolds. Journal of Computational and Graphical Statistics (JCGS), 1–23. [arXiv][DOI]
Gu, Z., Yu, S., Wang, G., & Wang, L. (2025). Boosting AI-Generated Biomedical Images with Confidence through Advanced Statistical Inference. Journal of the American Statistical Association, Theory and Methods (JASA, T&M), 1–27. [arXiv][DOI]
Gao, S.*, Gu, Z.*, Ding, S.*, Wang, G., Zhang, Z., Zhao, H., Zhao, Y. (2026). Brain Functional-Structural Gradient Coupling Reflects Development, Behavior and Genetic Influences. Nature Communications. (* Equal Contribution) [DOI]
Gu, Z., Yu, S., Wang, G., Lai, M. J., & Wang, L. (2025). TSSS: a novel triangulated spherical spline smoothing for surface-based data. Journal of Nonparametric Statistics, 1–30. [DOI]
Gu, Z., Li, X., Wang, G. & Wang, L. (2025). Spatiotemporal Heterogeneity Learning: Generalized SpatioTemporal Semi-Varying Coefficient Models With Structure Identification. Journal of Time Series Analysis, 47(1), 8–24. [DOI]
Wang, G., Gu, Z., Li, X., Yu, S., Kim, M., Wang, Y., Gao, L., Wang, L. (2023). Comparing and integrating US COVID-19 data from multiple sources with anomaly detection and repairing. Journal of Applied Statistics, 50(11-12), 2408-2434. [DOI]
Cramer, E. Y., Ray, E. L., Lopez, V. K., [et al., including Gu, Z., as a member of the US COVID-19 Forecast Hub Consortium] (2022). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences, 119(15), e2113561119. [DOI]
Kim, M., Gu, Z., Yu, S., Wang, G., Wang, L. (2021). Methods, Challenges, and Practical Issues of COVID-19 Projection: A Data Science Perspective. Journal of Data Science, 19(2), 219-242. [DOI]
Ananya, A., Holden, K. G., Gu, Z., Nettleton, D., Mallapragada, S. K., Wannemuehler, M. J., Kohut, M. L., Narasimhan, B. (2023). “Just right” combinations of adjuvants with nanoscale carriers activate aged dendritic cells without overt inflammation. Immunity & Ageing, 20, 10. [DOI]