Junjie Wu

My work sits at the intersection of MRI neuroimaging, quantitative medical imaging, and AI-enabled biomarker development. I focus on translating complex MRI data into robust, reproducible, and interpretable imaging measures that support both scientific discovery and clinical translation.

A central theme of my work is developing and validating end-to-end pipelines for resting-state fMRI functional connectivity, network-level analyses, and quantitative MRI methodologies, alongside deep-learning segmentation for imaging-derived biomarkers. I prioritize rigor and generalizability—careful quality control, sensitivity analyses, and evaluation across heterogeneous scanners and acquisition protocols—so that resulting biomarkers and models remain reliable beyond a single dataset.

I enjoy collaborating with multidisciplinary teams across radiology, neurology, and data science to build tools and analyses that are not only methodologically sound, but also practical for downstream adoption in research studies and clinical workflows.