Shuhao Jiao is a Postdoctoral Fellow of the KAUST Biostatistics Research Group. Before joining KAUST, Dr. Jiao received his Ph.D. in Statistics in 2019 from University of California, Davis. He is interested in statistical learning of complicated neuroimage data. He addresses these problems using novel statistical theory and methods in functional data analysis and machine learning.
Education
2019: Ph.D., Department of Statistics, University of California, Davis.
2014: BSc (Mathematics & Statistics), Shandong University, Jinan, China.
Research Interest
Functional data analysis, Time series analysis, Network model, and Statistical learning.
Selected Publications
Jiao, Shuhao, Alexander Aue, and Hernando Ombao. "Functional time series prediction under partial observation of the future curve." Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2021.1929248. (2021)
Jiao, Shuhao, and Hernando Ombao. "Shape-Preserving Prediction for Stationary Functional Time Series." Electronic Journal of Statistics (2021), Vol. 15, No. 2, 3996-4026.
Jiao, Shuhao, Ron D. Frostig, and Hernando Ombao. "Variation Pattern Classification of Functional data with Application to Brain Signals." arXiv preprint arXiv:2004.00855 (2020).
Jiao, Shuhao, Ron D. Frostig and Hernando Ombao. "Break Point Detection of Functional Covariance." arXiv preprint arXiv:2006.13887 (2020).
Jiao, Shuhao, Tong Shen, Zhaoxia Yu, and Hernando Ombao. "Change-point detection using spectral PCA for multivariate time series." arXiv:2101.04334. (2021)
Jiao, Shuhao, Ron D. Frostig and Hernando Ombao. "Filtrated Common Functional Principal Components for Multi-group Functional data." arXiv:2106.01104. (2021)
Professor,
Statistics