Why is visual information transmitted through many parallel channels in the optic nerve, with each channel encoding a different feature-map of the visual scene? Why do neurons in the retina prefer disk-shaped light dots and in the brain oriented lines? In this talk we will see how these simple questions can be investigated using artificial neural networks and a bit of maths.

Bio: After completing my PhD in computational neuroscience at Pierre and Marie Curie University (Paris), and a postdoc in theoretical neuroscience in the department of Applied Physics of Stanford, I am currently working at the interface of neuroscience and artificial intelligence at Facebook AI Research in NYC. I develop mathematical theories inspired by physics and machine learning to understand the structure and organization of the brain, and also use insights from neuroscience to build more robust, flexible and energy-efficient AI systems.