Professor Elias Issa will be our newest Grossman-Kavli Scholar.
Professor Issa's work uses a combined computational / empirical approach, and seeks to understand how the brain recognizes visual objects. Modern machine learning methods now perform remarkably well on a wide variety of object recognition and categorization tasks. The Issa lab uses a reverse-engineering approach to understand the the strategies and principles used by such methods, and in doing so generates testable hypotheses regarding how the brain recognizes objects. These hypotheses are then evaluated through comparison with neural data collected from the visual cortices.