Tomaso Poggio began his career in collaboration with Werner Reichardt quantitatively characterizing the visuomotor control system in the fly. With David Marr, he introduced the seminal idea of levels of analysis in computational neuroscience. He introduced regularization as a mathematical framework to approach the ill-posed problems of vision and—more importantly—the key problem of learning from data. He has contributed to the early development of the theory of learning—in particular introducing the mathematics of radial basis functions (RBF)—and has supervised learning in reproducing kernel Hilbert spaces (RKHSs) and stability. In the last decade, he has developed an influential quantitative model of visual recognition in the visual cortex, recently extended in a theory of sensory perception. He is one of the most cited computational scientists with contributions ranging from the biophysical and behavioral studies of the visual system to the computational analyses of vision and learning in humans and machines.