I study principles of learning in the brain and mind. The interactions of billions of neurons ultimately give rise to our thoughts and actions. Remarkably, much of our behavior is learned starting in infancy and continuing throughout our lifespan. Understanding how learning at the level of behavior is linked to changes at the level of neurons and synapses is a key challenge for theory.
My lab aims to develop a mathematical toolkit suitable for analyzing and describing learning in complex multi-regional brain networks. Our current focus is on the theory of deep learning, a class of artificial neural network models that take inspiration from the brain.
Alongside this theoretical work, we develop close collaborations with experimentalists to test principles of learning in biological organisms.