Hires, Samuel Andrew
Associate Professor of Biological Sciences
The Hires lab is investigating the basis of biological intelligence. Over the past decade we developed numerous imaging tools to record large-scale patterns of neural activity that are used by thousands of neuroscience labs. These have resulted in hundreds of publicly available datasets embedded with rich representations of neural activity. We are now developing analytical tools, using recent AI developments, to ultimately distill undiscovered principles of biological intelligence from these datasets.
Ichida, Justin
Associate Professor of Stem Cell Biology and Regenerative Medicine
We are interested in understanding mechanisms underlying neurodegenerative and neurodevelopmental diseases. We also aim to develop new therapeutic strategies for these disorders.
Kaplan, Jonas
Associate Professor of Psychology
I study self, consciousness, and meaning-making in all of its forms, with a focus on understanding the neural systems that integrate information to form high level models of the world and of the self. This includes a focus on narrative cognition, and naturalistic fMRI methods that allow for the analysis of the real-time, ongoing neural dynamics that support our understanding of the people, events, and stories that make up our worlds.
Kim, Hosung
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.
Lepore, Natasha
Associate Professor of Research Radiology
My lab, the Computational Imaging of Brain Organization Research Group (CIBORG), focuses on developing advanced numerical methods to study brain anatomy and function using magnetic resonance imaging. Our work aims to deepen understanding of typical and atypical brain development, across both high- and low-resource settings. In parallel, we are creating software tools to support clinicians by providing quantitative assessments of medical images to enhance clinical decision-making.
