معرفی
Shuoyang Wang is an Assistant Professor in the Department of Bioinformatics and Biostatistics at the University of Louisville's School of Public Health and Information Sciences (SPHIS). He holds a PhD in Mathematics and Statistics from Auburn University (2022), an MS in Statistics from the University of Wisconsin-Madison (2017), and a BS from Shandong University's Mathematics School (2016). His postdoctoral training (2022-2023) was at Yale University's Department of Biostatistics.
His research focuses on advancing statistical methodologies for functional data analysis, deep learning applications in biostatistics, high-dimensional data classification, and causal inference in public health contexts. Key areas include integration of deep neural networks with functional data frameworks, mediation effect estimation with complex mediators, and spatial epidemiology models addressing health disparities.
Recent work emphasizes classification challenges in functional data, particularly through innovative neural network architectures and robust statistical learning techniques. His 2024 reviews and 2025 multi-class classification studies highlight methodological contributions to this growing field.
Publications span prestigious journals like Biostatistics, Statistica Sinica, and Electronic Journal of Statistics, with applied work addressing obesity disparities and upper airway thermoregulation. His research bridges theoretical advancements with practical healthcare applications.
