Peer reviewed journal & conference articles:

Statistical Methodology (* corresponding author)

FIONNA: Functional Inference with Orthogonal Neural Network Adjustment for Mediation Analysis

Wang, S.* (2026+), under review at Biostatistics.

Deep Transformer Classification for Multivariate Functional Data with Structured Heterogeneity.

Wang, S.*, Tian, Y., Cao, G. (2026+), under review at Statistica Sinica.

Minimax-Optimal Transformer Classification for Functional Data with Dense-Sparse Phase Transition.

Wang, S.*, Tian, Y., Cao, G. (2026+), under review.

Comprehensive Neural Network Methods for Heteroscedastic Partial Linear Quantile Regression in Ultra-High Dimensions: Deep and Shallow Architectures.

Wang, S.*, Mou, Y., Xiao, Q., Huang, Y. (2026+), revision submitted at Electronic Journal of Statistics.

Heterogeneity-Aware Optimal Classification for Multi-source Imaging Data.

Wang, S., Cao, G. (2026+), revision submitted at The Annals of Applied Statistics.

Functional Imaging Data Classification with Crowdsourced Noisy Annotations. (PDF) (Code)

Wang, S., Yi, G., Cao, G. (2026+), Statistica Sinica, in press.

Empowering Classification for Multivariate Functional Data with Simultaneous Feature Selection. (PDF) (Code)

Wang, S., Cao, G., Huang, Y. (2026+), Statistical Methods in Medical Research, in press.

Inference for Quantile Mediation Effects in the Presence of Complex Confounding. (PDF)

Wang, S., Huang, Y. (2026), Electronic Journal of Statistics, 20(2).

Deep Neural Network for Functional Graphical Models Structure Learning. (PDF) (Code)

Wang, S., Cao, G. (2026), Journal of Computational and Graphical Statistics, 35(2).

Partially Linear Quantile Regression for Complex Nonlinear Component in Ultra-High Dimension. (PDF)

Wang, S.* (2025), Electronic Journal of Statistics, 19(2).

DP2LM: Deep Learning for Estimation and Inference on Mediation Effects with High-Dimensional Mediators and Complex Confounders. (PDF) (Code)

Wang, S., Huang, Y. (2024), Biostatistics, 25(3).

Functional Data Analysis Using Deep Neural Networks. (PDF)

Wang, S.*, Zhang, W., Cao, G., Yuan, H. (2024), WIREs Computational Statistics, 16(4).

Multiclass Classification for Multidimensional Functional Data through Deep Neural Networks. (PDF) (Code)

Wang, S., Cao, G.(2024), Electronic Journal of Statistics, 18(1).

Optimal Classification for Functional Data. (PDF)

Wang, S., Shang, Z., Cao, G., Liu, J.S. (2024), Statistica Sinica, 34(3).

Review on Functional Data Classification. (PDF)

Wang, S., Yuan, H., Cao, G. (2024), WIREs Computational Statistics, 16(1).

Deep Neural Network Classifier for Multidimensional Functional Data. (PDF) (Code)

Wang, S., Cao, G., Shang, Z. (2023), Scandinavian Journal of Statistics, 50(4).

Empirical Likelihood Ratio Tests for Varying Coefficient Geo Models. (PDF)

Wang, S., Wang, H., Zhao, Y., Cao, G., Li, Y. (2023), Statistica Sinica, 33(2).

Minimax Optimal High-Dimensional Classification Using Deep Neural Networks. (PDF)

Wang, S., Shang, Z. (2022), Stat, 11(1).

Robust Deep Neural Network Estimation for Multi-dimensional Functional Data. (PDF) (Code)

Wang, S., Cao, G. (2022), Electronic Journal of Statistics, 16(2).

Estimation of the Mean Function of Functional Data via Deep Neural Networks. (PDF) (R) (Python)

Wang, S., Cao, G., Shang, Z. (2021), Stat, 10(1).

Estimation and Inference for Functional Linear Regression Models with Partially Varying Regression Coefficients. (PDF)

Cao, G., Wang, S., Wang, L. (2020), Stat, 9(1).

Interdisciplinary research & case studies

Mediation Analysis of Workload and Emotion on the Performance of Supervision Tasks.

Chowdhury, M., Wang, S., Liu, Y. (2026+), Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

Improved Prognostic Survival Models Using High Dimensional Gene Expression Data. (PDF)

Jones, T., Sumy, M., Amona, E., Wang, S., Mistry, A., Donninger, H., Yaddanapudi, K., Kong, M. (2026+), BMC Medical Genomics.

Geographic Variation of Urban-Rural Differences in Cardiovascular Mortality Across States in United States.

Belcher, S., Wang, S., Ugiliweneza, B. (2026+), under review.

Uncovering the Mediating Role of Metabolomics in the Sleep–Cognition Pathway: A Case Study Using Deep Learning to Address Complex Confounding.

Li, D., Mou, Y., Xiao, Q., Wang, S., Huang, Y. (2026), accepted, Statistical Foundations and Applications of Artificial Intelligence, Machine Learning and Deep Learning, Springer.

Prioritizing Dietary Supplements that Prevent Ethanol-induced Impairment of Neural Crest Cells and Mitigate Fetal Alcohol Spectrum Disorders by Targeting Epigenetic Regulators through Biologically Informed Machine Learning Models.

Wang, X., Bai, M., Wang, S., Liu, J., Feng, W., Zhang, H., Wu, X. and Chen, S. (2025), 27(1), International Journal of Molecular Sciences. (PDF)

Disentangling Racial/Ethnic and Income Disparities of Food Retail Environments: Impacts on Adult Obesity Prevalence. (PDF)

Li, Y., Wang, S., Cao, G., Li, D. and Ng, B. (2021), Applied Geography, 137, 102607.

Upper Airway Thermoregulation During Singing Warm up. (PDF)

Sandage, M., Wang, S., Cao, G. (2019), Journal of Voice, 35(1), pp.157.e1-157.e6.

Funded grants:

2024-2026 University of Louisville, SOM-SPHIS Joint Pilot Project Program, Integrating artificial intelligence and gene editing to identify and validate epigenetic targets for nutrient-based interventions in Fetal Alcohol Spectrum Disorder. (MPI, with Dr. Shao-yu Chen).

2024-2026, 2026-2031 HRSA/University Hospitals Cleveland Medical Center, Center for Pediatric Everyday Readiness–Regional Pediatric Pandemic Network. (Co-I, with site PI Dr. Mary E. Fallat).