Nan Xu, PhD
Dept. of Biomedical Engineering
Georgia Institute of Technology and Emory University
Title: Statistical learning and dynamic analysis in functional neuroimaging data
Abstract:The Blood Oxygen Level Dependent (BOLD) brain dynamic processes measured by functional MRI have served as sensitive indicators of various brain disorders. Traditional methods focus mainly on the temporal variability of the resting brain, which limits insights into causal dynamics and their role in conditions such as post-concussive visual motion sensitivity (PCVMS). My research bridges this gap by introducing innovative statistical learning and analytical techniques to elucidate the spatiotemporal causal dynamics within brain networks in different brain conditions. The findings have illuminated key brain functions, such as attention control, and have identified potential biomarkers for PCVMS. These new methods advance our understanding of brain function and the mechanisms underlying disorders, thereby enhancing the fields of neuroimaging and therapeutic intervention.
Bio: Dr. Nan Xu is currently a postdoctoral fellow in Biomedical Engineering at the Georgia Institute of Technology and Emory University. With a strong background as a computational scientist, her research intersects statistical learning, applied mathematics, neuroscience, and various biomedical applications. Her recent effort focuses on developing advanced machine learning models and analysis in functional neuroimaging data to provide novel insights in brain functions and diseases. Nan earned her B.S. in Electrical and Computer Engineering and B.A. in Mathematics, with a minor in Music, from the University of Rochester (2011), and received her M.Sc. (2015) and Ph.D. (2017) in Electrical and Computer Engineering with minors in Applied Mathematics and Cognitive Neuroscience from Cornell University.