Expertise

Research Areas: Data Science

I am interested in the development of statistical methods for the analysis of brain imaging data.  My recent or ongoing projects include:

  • High-dimensional outlier detection methods for artifact removal in fMRI data
  • Empirical Bayes shrinkage estimation of subject-level resting-state functional connectivity
  • Bayesian spatial modeling in task activation studies using cortical surface fMRI
  • Empirical Bayesian techniques to account for spatial dependence in fMRI task activation studies
  • Leveraging big fMRI datasets for estimation of subject-level and group-level resting-state networks through “template” independent component analysis (ICA)
  • Synthesis of quantitative structural MR images (e.g. quantitative T1 maps, DTI, MTR) using conventional sequences (e.g. T1-weighted and FLAIR)

Subject Area

  • Statistics
Communities
Neuroscience, Statistics, Computer Science
Degrees
PhD, Johns Hopkins University, Biostatistics, 2016
MS, Georgia Institute of Technology, Industrial and Systems Engineering, 2011
BS, Georgia Institute of Technology, Industrial and Systems Engineering, 2007