Dr. Barrios earned his Ph.D. in Neuroscience from the University of Utah, where his work focused on dopaminergic modulation of sensorimotor behavior. His interest in computational and systems neuroscience and love for engineering naturally led him to study artificial deep neural networks. Currently, his work in the Tison lab involves development of deep learning systems for clinical and biomedical applications.

Research interests: Dr. Barrios brings together expertise in physiology, systems neuroscience, and advanced machine learning algorithms to automate clinical processes, expand diagnostic utility of existing clinical tests, and elucidate mechanisms of disease. He has developed multiple deep learning based systems for automated detection of diseases such as mitral valve prolapse, hypertrophic cardiomyopathy, and pulmonary hypertension from electrocardiograms, echocardiograms, and other clinical data modalities. His work aims to improve the sensitivity of our health system as a whole, increasing early detection of disease and the efficacy of preventative care.