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

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., Liu, Y., Xu, W., Tian, X., & Zhao, Y. (2023). Inference-based statistical network analysis uncovers star-like brain functional architectures for internalizing psychopathology in children. arXiv preprint arXiv:2309.11349.

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. arXiv preprint arXiv:2410.00301.

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