Dr. Cheng-Han Yu

Dr. Cheng-Han YuMarquette University

Cudahy Hall, 353

MilwaukeeWI53201United States of America(414) 288-1701cheng-han.yu@marquette.eduPersonal Website

Assistant Professor, Applied Statistics Director

Department of Mathematical and Statistical Sciences

Courses Taught

• Statistical Methods

Research Interests

• Bayesian Computation
• Spatiotemporal Modeling
• Hierarchical Models
• Kernel methods
• Neuroimaging

Publications

• C.H. Yu and S. Wang. A Comparative Study of Bayesian Neural Networks and Machine Learning Based on COVID-19 Images. Statistics and Data Science in Imaging, 2(1), 1-12 (2025). DOI: 10.1080/29979676.2025.2497555.
• A.C. Ding and C.H. Yu. Serious Game-based Learning and Learning by Making Games: Types of Game-based Pedagogies and Student Gaming Hours Impact Students' Science Learning Outcomes. Computers & Education, 218, 105075 (2024). DOI: 10.1016/j.compedu.2024.105075.
• C.H. Yu, M. Li, and M. Vannucci. Semiparametric Latent ANOVA Model for Event-Related Potentials. Data Science in Science, 3(1) (2024). DOI: 10.1080/26941899.2023.2294204.
• M. Li, Z. Liu, C.H. Yu, and M. Vannucci. Semiparametric Bayesian Inference for Local Extrema of Functions in the Presence of Noise. Journal of the American Statistical Association, 119(548), 3127-3140 (2024). DOI: 10.1080/01621459.2024.2308333.
• C.H. Yu, R. Prado, H. Ombao, and D. Rowe. Bayesian Spatiotemporal Modeling via Kernel Convolution in Complex-valued fMRI. Biometrics, 79(2), 616-628 (2023). DOI: 10.1111/biom.13631.
• C.H. Yu, M. Li, C. Noe, S. Fischer-Baum, and M. Vannucci. Bayesian Inference for Stationary Points in Gaussian Process Regression Models for Event-Related Potentials Analysis. Biometrics, 79(2), 629-641 (2023). DOI: 10.1111/biom.13621.