Publications

An asterisk * is used to indicate corresponding author; An underline is used to indicate students under my supervision; A dagger † is used to indicate joint first author, equal contribution

Peer-Reviewed Articles

• Shi B, Liu Y, Xie S, Zhu X, Wang Y (2024). Network-Assisted Mediation Discovery with Neuroimaging Mediators. Machine Learning for Healthcare Conference. Proceedings of Machine Learning Research (PMLR). In Press.

• McDonnell E , Xie S, Marder K, Cui F, Wang Y (2024). Dynamic Undirected Graphical Models for Time-Varying Clinical Symptom and Neuroimaging Networks. Statistics in Medicine. In Press. (An earlier version won American Statistical Association (ASA) Statistics in Imaging Section First Prize Student Paper Award)

• Xie S^*, Zeng D, Wang Y (2024). Identifying Temporal Pathways Using Biomarkers in the Presence of Latent Non-Gaussian Components. Biometrics. In Press. [code]

• Xie S^*, Ogden RT (2024). Functional Support Vector Machine. Biostatistics. In Press. [code]

• Xie S^*, Tarpey T, Petkova E, Ogden RT (2022). Multiple Domain and Multiple Kernel Outcome-weighted Learning for Estimating Individualized Treatment Regimes. Journal of Computational and Graphical Statistics 31 (4), 1375-1383. [Matlab toolbox]

• Xie S^*, Wang W, Wang Q, Wang Y, Zeng D (2022). Evaluating Effectiveness of Public Health Intervention Strategies for Mitigating COVID-19 Pandemic. Statistics in Medicine 41 (9), 3820-3836. [Slides]

• COVID-19 Forecast Hub Consortium (2022). Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the US. Proceedings of the National Academy of Sciences 119 (15), e2113561119.

• COVID-19 Forecast Hub Consortium (2022). The United States COVID-19 Forecast Hub Dataset. Scientific Data 9, 462.

• Xie S^*, Mcdonnell E, Wang Y (2022). Conditional Gaussian Graphical Model for Estimating Personalized Disease Symptom Networks. Statistics in Medicine 41 (3), 543-553. (An earlier version won American Statistical Association (ASA) Mental Health Statistics Section Best Student Paper Award)

• Xie S^*, Zeng D, Wang Y (2021). Integrative Network Learning for Multi-modality Biomarker Data. Annals of Applied Statistics 15 (1), 64-87. [code]

• Xie S^*, Li X, McColgan P, Scahill RI, Zeng D, Wang Y (2020). Identifying Disease-associated Biomarker Network Features Through Conditional Graphical Model. Biometrics 76 (3), 995-1006. [code] (Cover story of Biometrics September 2020 issue; An earlier version won the International Conference on Health Policy Statistics (ICHPS) Student Travel Award)

• Goldman J, Xie S, Green D, Naini A, Mansukhani MM, Marder K (2021). Predictive Testing for Neurodegenerative Diseases in the Age of Next-generation Sequencing. Journal of Genetic Counseling 30, 553-562.

• Wang Q, Xie S, Wang Y, Zeng D (2020). Survival-Convolution Models for Predicting COVID-19 Cases and Assessing Effects of Mitigation Strategies. Frontiers in Public Health 8, 325. [code] (Our model is used by U.S. Center of Disease Control and Prevention (CDC) for COVID-19 Ensemble Forecast [our forecast website][CDC ensemble forecast website] )

• Li X^†, Xie S^†, McColgan P, Tabrizi SJ, Scahill RI, Zeng D, Wang Y (2018). Learning Subject-Specific Directed Acyclic Graphs with Mixed Effects Structural Equation Models from Observational Data. Frontiers in Genetics 9, 430.

• Li X, Xie S, Zeng D, Wang Y (2018). Efficient l₀-norm Feature Selection Based on Augmented and Penalized Minimization. Statistics in Medicine 37 (3), 473-486. [R package]

• Avissar M^†, Xie S^†, Vail B, Lopez-Calderon J, Wang Y, Javitt DC (2018). Meta-analysis of Mismatch Negativity to Simple versus Complex Deviants in Schizophrenia. Schizophrenia Research 19, 25-34.