Research

Network science is interdisciplinary. Focusing on improving current analytical strategies, I try to absorb influences of other disciplines to inform and improve understandings about human behaviors with applications in neuroscience, psychiatry, psychology and others. Broadly speaking, I model real-world networks with statistically sound principles and methods—reduce network complexity, perform intuitive visualization and test critical hypotheses with improved statistical power and controlled type I errors. I am particularly interested in the topological structures of networks and the roles they play in (neuro)degeneration, (neuro)development and resilience.

Brain Networks

Zhang, X., Hulvershorn, L. A., Constable, T., Zhao, Y., & Wang, S. (2025). Cost Efficiency of fMRI Studies Using Resting‐State Vs. Task‐Based Functional Connectivity. Human Brain Mapping, 46(9), e70260.

Wang, S., Wang, Y., Xu, F., Tian, X., Fredericks, C., Shen, L., Zhao, Y., & Alzheimer’s Disease Neuroimaging Initiative (In press). Sex-specific topological structure associated with dementia via latent space estimation. Alzheimer's & Dementia, in press.

Tian, X., Wang, Y., Wang, S., Zhao, Y., & Zhao, Y. (2024). Bayesian mixed model inference for genetic association under related samples with brain network phenotype. Biostatistics, in press.

Wang, S., Zhang, X., Liu, Y., Xu, W., Tian, X., & Zhao, Y. (2025). Neuroimaging connectivity analysis needs network science for brain-behavior linking. Nature Methods, in press.

Wang, S., Wang, Y., Xu, F. H., Shen, L., Zhao, Y., & Alzheimer’s Disease Neuroimaging Initiative. (2025). Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling. Medical Image Analysis, 99, 103309.

Wang, S., Powla, P., Sweet, T., & Paul, S. (2024). The co-varying ties between networks and item responses via latent variables. arXiv preprint arXiv:2409.19400.

Wang, S., Paul, S., & De Boeck, P. (2023). Joint latent space model for social networks with multivariate attributes. Psychometrika, 1–31.

Sweet, T., & Wang, S. (2024). Network Science in Psychology. Psychological Methods, in press.

Bipartite Networks, Multivariate and Psychometric Analysis

Wang, S, & Edgerton, J. (2022). Resilience to stress in bipartite networks: application to the islamic state recruitment network. Journal of Complex Networks, 10(4), cnac017.

Wang, S., De Boeck, P., & Yotebieng, M. (2023). Heywood cases in unidimensional factor models and item response models for binary data. Applied Psychological Measurement, 47 (2), 141–154.

Wang, S, & De Boeck, P. (2022). Understanding the role of subpopulations and reliability in between-group studies. Behavior Research Methods, 1–16.

Topics I am currently working on

Network-based neuroimaging methodology development

Trajectory research, normative modeling, interplay between function and structure, brain-age research, imaging harmonization and imaging genetics

Imaging transcriptomics

Neuroimaging linked with genetics and other biological outcomes

Data science and machine learning topics

Hypergraph, prediction versus inference