Research

My research aims to understand how the human brain is organized at the individual level, how this organization changes across disease and intervention, and how multimodal neuroimaging can contribute to precision neuroscience.

01. Individualized Brain Organization & Connectome Geometry

I am interested in how a common large-scale brain architecture is instantiated differently in each individual. Rather than treating inter-individual variability as noise, I use connectome geometry, manifold-based representations, and spatially resolved network measures to characterize how structural and functional organization varies across people.

02. Computational Multimodal Neuroimaging

I work across the neuroimaging pipeline, from acquisition design to computational analysis, to extract complementary information from structural MRI, functional MRI, and diffusion MRI. My focus is on building multimodal representations that preserve biologically meaningful organization while remaining interpretable at the level of individual brains.

03. Precision Clinical Neuroscience

I use longitudinal and intervention-based neuroimaging to examine how brain systems reorganize across neurological and psychiatric conditions, treatment, and recovery. The aim is to move beyond group-average case-control differences toward individual trajectories that connect brain changes with symptoms, prognosis, and treatment response.

• ONGOING RESEARCH

1. Individualized Connectome Manifolds

2. Mapping inter-individual variation in multimodal brain organization within low-dimensional representational spaces.

3. Longitudinal Clinical Connectomics

4. Characterizing trajectories of brain reorganization associated with symptoms, treatment response, and recovery.

5. Multimodal Brain Representations

6. Integrating structural, functional, and diffusion MRI to construct individualized representations of brain architecture.

7. Advanced Diffusion and Functional Neuroimaging

8. Developing and evaluating high-resolution acquisition and analysis strategies for probing brain microstructure and function.

• APPROACH

  • Multimodal Neuroimaging

  • Connectome & Network Modeling

  • High-dimensional Neurodata Analysis

  • Representation & Manifold Learning

  • Statistical Learning & Machine Learning

  • Multimodal Data Integration

  • Longitudinal & Individualized Modeling

  • Reproducible Scientific Computing