Hernan is a neuroscientist and data scientist specializing in aging, brain health, and neurodegenerative diseases. Trained in engineering and neuroscience, Hernán bridges computational modeling, machine learning, and brain signal analysis to investigate how biological, behavioral, and exposomic factors shape cognitive and brain aging across diverse populations.
His research focuses on functional brain dynamics, exposome-driven aging gaps, and the development of computational biomarkers using EEG, fMRI, and bio-behavioral data. He has made notable contributions to understanding structural inequality and its impact on brain aging, and has developed open-access software for brain tractography. His scientific production includes high-impact publications in Nature Medicine, Nature Aging, and NeuroImage.
Hernan has been involved in key international initiatives, including ReDLat, and his research has been supported by the NIH/NIA. During his postdoctoral fellowship with the US–South American Initiative for Genetic-Neural-Behavioral Interactions in Neurodegeneration, he contributed significantly to the development of aging models that reflect regional diversity.
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