Yuexuan Wu

Assistant Professor, Department of Statistics
University of South Carolina
yuexuan@sc.edu

I am an Assistant Professor in the Department of Statistics at the University of South Carolina.

Before joining USC, I completed a two-year Biostatistics postdoc at the National Alzheimer’s Coordinating Center (NACC) at the University of Washington, supervised by Prof. K.C. Gary Chan. I was also a Data Science Postdoctoral Fellow at the eScience Institute, University of Washington. I earned my Ph.D. in Statistics from Florida State University, under the supervision of Prof. Anuj Srivastava.

My research focuses on developing novel statistical and machine-learning methodologies for analyzing high-dimensional and complex data stemming from neuroimaging, neuroscience, and broader biological and medical research. Central to my research is learning underlying structures within complex data, statistically modeling the variability, and performing statistical inferences. Specifically, I aim to apply these statistical and computational tools to advance the understanding of the brain’s structural changes and their associations with brain functions, aging, and various diseases. My long-term research goal is to unravel the mechanisms of brain aging and diseases using multi-modality data, specifically aiming to detect and diagnose diseases before symptoms appear. My research interests lie in medical image analysis, shape and functional data analysis, computational neuroscience, and causal inference .


Education

Florida State University

Doctor of Philosophy, Statistics
Advisor: Prof. Anuj Srivastava

Dissertation: Computational Anatomy: Elastic Shape Analysis of Subcortical Structure Surfaces

August 2019 - July 2022

Florida State University

Master of Science, Applied Statistics
August 2017 - May 2019

Wuhan University (Wuhan, China)

Bachelor of Engineering, Bachelor of Commerce
Packaging Engineering, Economics
September 2013 - June 2017

Research

Elastic Shape Analysis of Brain Structures for Predictive Modeling of PTSD

Developing a comprehensive shape analysis framework to quantify the brain substructures surfaces shape differences using an elastic shape metric; training regression models with shape coefficients and predicting PTSD outcomes; applying the method to data from the Grady Trauma Project and yielding superior predictive performance.

February 2020 - August 2022

LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures

Developing an efficient framework and a unique toolbox for systematically quantifying the development and changes of longitudinal subcortical surface shapes by integrating ideas from elastic shape analysis, PCA, and statistical modeling of sparse longitudinal data; applying LESA to analyze three longitudinal neuroimaging data sets with estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups.

September 2020 - November 2022

Solving Optimal Surface Deformation Using Deep Residual Networks

Utilizing deep residual neural networks to solve the optimal shape deformation of surfaces under the square root normal field (SRNF) representation.

January 2021 - Present

Analysis and Generation of Bacteria Cellular Shapes

Analyzing the shape summaries of segmented 3D bacteria cellular surfaces; generating synthetic bacteria cellular surfaces based on the distribution of true surface shapes.

March 2021 - March 2023

Spatial-Temporal Analysis of 3D Human Body Movements Using Video Data

Developing a framework for reproducing smooth 3D human movement videos based on sparse time samples of movement; analyzing movement differences by conducting spatial-temporal surface registration.

November 2021 - Present

Topological and Geometrical Analysis of Brain Shape

Understanding the interplay between Aβ and tau proteins and their spatial distribution in the brain using PET images; investigating the topological and geometrical features of brain images in different groups to reveal complex underlying structures and identify potential biomarkers for disease progression.

September 2022 - Present

Causal Inference on Brain Structures and Cognitive Disorder

Developing a high-dimensional mediation analysis approach for complex brain structures; gaining more statistical power, identifying more significant SNPs associated with AD, and capturing the causality between deformations in brain structure shapes with genotypes and disease progression.

October 2022 - Present

Publications

Y. Wu , C. Huang, A. Srivastava. Shape-Based Functional Data Analysis. TEST , 2024


Y. Wu , C. Huang, A. Srivastava. Rejoinder on: Shape-Based Functional Data Analysis. TEST , 2024


Z. Zhang, Y. Wu , D. Xiong, J. G. Ibrahim, A. Srivastava, H. Zhu. LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures. Published as a discussion paper in Journal of the American Statistical Association , 2023


Z. Zhang, Y. Wu , D. Xiong, J. G. Ibrahim, A. Srivastava, H. Zhu. Rejoinder: LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures. Journal of the American Statistical Association , 2023


Y. Wu , S. Kundu, J. S. Stevens, N. Fani, A. Srivastava. Elastic Shape Analysis of Brain Structures for Predictive Modeling of PTSD. Frontiers in Neuroscience , 2022


T. T. Toma, Y. Wu , J. Wang, A. Srivastava, A. Gahlmann, S. T. Acton. Realistic-Shape Bacterial Biofilm Simulator for Deep Learning-Based 3D Single-Cell Segmentation. Accepted in IEEE International Symposium on Biomedical Imaging (ISBI) , 2022


Y. Wu , H. Laga, A. Srivastava. Spatial-Temporal Analysis of 3D Human Body Movements Using Video Data. In preparation, 2024+


Y. Wu , K. Ormsby, D. Shibata, Y.C. Chen, S. Biber, W. Kukull, and K.C.G. Chan. Topological Network Analysis of Beta-Amyloid and Tau in Alzheimer’s Disease Using PET Imaging Data. Neuroinformatics , Submitted in the special volume, 2024+


Y. Wu , K.C.G. Chan. High-Dimensional Multivariate Mediation Analysis with Application to Brain Structural Data. In preparation, 2024+



Presentations

(05/2024) Topological Network Analysis of Protein Aggregates in Alzheimer’s Disease Using PET Imaging Data , The Statistical Methods in Imaging Conference 2024, Indianapolis


(02/2024) Data Science Approaches on Neuroimaging Analysis , Guest lecture (EPI 571 Neuroepidemiology & Environmental Risk Factors), Department of Epidemiology, University of Washington, Seattle


(11/2023) Statistical Shape Analysis of Brain Structure Surfaces , Colloquia, Department of Mathematics and Statistics, Texas Tech University (online)


(08/2023) Longitudinal Elastic Shape Analysis of Brain Subcortical Structures , The 6th International Conference on Econometrics and Statistics (EcoSta 2023), Tokyo (online)


(07/2023) Topological Network Analysis of Beta-Amyloid and Tau in Alzheimer’s Disease Using PET Imaging Data , The Alzheimer’s Association International Conference (AAIC) 2023 (Poster), online


(05/2023) LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures , The Statistical Methods in Imaging Conference 2023, Minneapolis


(10/2022) Statistical Shape Analysis and Transdisciplinary Applications , UW eScience Institute Postdoc Seminar, online


(06/2022) Longitudinal Elastic Shape Analysis of Brain Subcortical Structures , 2022 Treatment and Analysis of the Information Methods and Applications (TAIMA), Hammamet, Tunisia (online)


(04/2022) Longitudinal Elastic Shape Analysis of Brain Subcortical Structures , 2022 Annual Florida ASA Chapter Meeting, online


(05/2021) Elastic Shape Analysis of Brain Structures for Predictive Modeling of PTSD , The Statistical Methods in Imaging Conference (Poster), online


(03/2021) Elastic Shape Analysis of Post-Traumatic Stress Disorder on Subcortical Brain Structures , SIAM Conference on Computational Science and Engineering (Poster), online


Awards

  • Travel Award in 8th Workshop on Biostatistics and Bioinformatics 2023
  • Yongyuan and Anna Li Award for best graduate student presentations - Department of Statistics, Florida State University 2022
  • Best Student Presentation Award in Annual Florida ASA Chapter Meeting 2022
  • Best Student Poster Award in SIAM CSE (Conference on Computational Science and Engineering) 2021 (Top 1%)
  • 2 nd Place - Florida State University - ACM Programming Contest 2018
  • 1 st Class Scholarship - Wuhan Univeristy 2016 (Top %1)

Alzheimer's Awareness Through Film

The following films offer unique portrayals of dementia and Alzheimer's disease, aiming to shed light on the challenges faced by individuals and their families. While these movies provide valuable insight and raise awareness, they are for informational purposes only, and the depiction of Alzheimer's disease may vary from scientific reality.


  • A Moment to Remember (2004)
  • Song of Spring (2022)
  • Still Alice (2014)
  • The Father (2020)