About

Welcome to the Neuroimaging Imaging with Deep Learning Lab (NIDLL)!

The Neuroimaging with Deep Learning Lab (NIDLL) focuses on developing and applying advanced artificial intelligence methods to understand brain health, aging, and disease. Our research integrates multimodal neuroimaging, biosignals, and longitudinal clinical data to characterize individual variability in brain structure and function across the lifespan. A central theme of the lab is the use of deep learning and data-driven modeling to derive biologically meaningful markers—such as regional brain age and system-level brain health indices—that can predict clinical outcomes and treatment response.

A major emphasis of NIDLL is on sleep, cerebrovascular function, and the glymphatic system as key modulators of brain aging and neurodegeneration. We develop MRI-based metrics to quantify perivascular spaces, cerebrospinal fluid dynamics, and glymphatic function, and study how their disruption relates to poor sleep quality, accelerated brain aging, and neurodegenerative processes. These methods are applied across diverse populations and neurological conditions, including Alzheimer’s disease, Parkinson’s disease, stroke, epilepsy, and sleep disorders, with the goal of identifying early, noninvasive biomarkers of disease vulnerability and progression.

Ultimately, NIDLL aims to bridge computational neuroscience and translational medicine by building predictive models that support precision diagnosis and personalized intervention. By combining large-scale neuroimaging datasets, longitudinal designs, and interpretable AI, our work seeks to inform clinical decision-making and optimize therapeutic strategies for neurological and sleep-related disorders. The lab is led by Dr. Hosung Kim, who mentors trainees and collaborators in developing rigorous, impactful research at the intersection of neuroimaging, artificial intelligence, and brain health. We welcome you to join the lab and participate in our valuable research.