White-matter fMRI
Voxel-wise and ICA-based detection of functional networks in white matter, validated against intracranial electrophysiology (SEEG).
Postdoctoral Research Scientist
Mary & Mark Stevens Neuroimaging and Informatics Institute
University of Southern California, Los Angeles, CA
I study the human brain through medical imaging. With more than 15 years of experience in medical image analysis and signal processing, my work focuses on functional MRI of brain white matter and its applications to brain development and disease, with first-author publications in NeuroImage, PNAS, and Nature Communications.
My research applies digital signal processing, machine learning, and neuroimaging to understand how the brain is organized and how it develops. A central thread is the detection and characterization of functional signals in white matter, a domain long thought to be silent in fMRI.
Voxel-wise and ICA-based detection of functional networks in white matter, validated against intracranial electrophysiology (SEEG).
How maternal health during pregnancy — weight, diet, activity, and mental health — shapes infant and children's brain development via fMRI and dMRI.
Segmentation, tracking, and feature extraction for microscopy and ultrasound using active contour models, optical flow, and multi-scale transforms.
Time-, frequency-, and spatial-domain analysis of 2–4D signals; MATLAB, Python, R, FSL, ANTs, and deep learning on HPC platforms.
Selected and complete list below. See Google Scholar for citations and the latest updates.
I welcome collaborations and conversations on brain imaging, white-matter function, and brain development.