Elias Issa

Elias Issa’s lab utilizes an interdisciplinary approach to studying visual cognition with focus on the problems of face recognition and scene understanding. High-density neural recordings from the primate cortex are coupled with decoding analyses to decipher the patterns of activity across large neural populations. Insights from experiments drive the creation of machine learning models engineered to perform visual learning and visual inference analogous to the brain. The lab also develops and integrates new tools for building a forward-looking experimental platform to measure and perturb the cerebral cortex during active visual behaviors.