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