Dr. Hongxiao Zhu, Associate Professor, Virginia Tech presents Region Detection on Functional Data
Date: Thursday, November 2, 2023
Start time: 3:00 pm
End time: 4:00 pm
Location: On Zoom
Audience: All are welcome to attend
High-dimensional functional data, such as brain images, spectral curves, and engineering signals, often contain a wealth of information. However, the abundance of information does not automatically lead to a clearer understanding of the underlying mechanisms. In fact, a large portion of the information carried by functional data may be noise, unrelated to the issues of interest. This presentation focuses on the challenge of identifying important local regions within functional data. I will introduce a few statistical approaches that were developed by our research group, including Bayesian functional regression and testing approaches. Our goal is to detect local regions that can differentiate groups of samples, or are associated with covariates of interest. I will illustrate applications of these approaches using examples in brain imaging and cancer study.
Bio
Dr. Hongxiao Zhu is an Associate Professor in the Department of Statistics at Virginia Tech. She earned her PhD in Statistics from Rice University and completed postdoctoral training at the University of Texas MD Anderson Cancer Center, SAMSI, and Duke University. Dr. Zhu’s research is primarily concentrated on the domains of functional data analysis, Bayesian modeling, and machine learning. In recent years, she has dedicated her efforts to develop flexible statistical models to characterize intricate data structures, discover systematic patterns, and extract critical features from complex datasets.
Sponsor(s): SSOR
Event contact: Dr. Ya Su, suyaf@vcu.edu