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Tomaso A. Poggio is one of the founders of computational neuroscience. He pioneered models of the fly's visual system and of human stereovision, introduced regularization theory to computational vision, made key contributions to the biophysics of computation and to learning theory, developed an influential model of recognition in the visual cortex. He is one of the most cited computational neuroscientists (with a h-index greater than 90 – based on GoogleScholar).
He is the Eugene McDermott Professor at the Department of Brain and Cognitive Sciences; Co-Director, Center for Biological and Computational Learning; Member for the last 27 years of the Computer Science and Artificial Intelligence Laboratory at MIT; since 2000, member of the faculty of the McGovern Institute for Brain Research. He received his Doctor in Theoretical Physics from the University of Genoa in 1971 and was a Wissenschaftlicher Assistant, Max Planck Institut für Biologische Kybernetik, Tüebingen, Germany from 1972 until 1981 when he became Associate Professor at MIT. He is an honorary member of the Neuroscience Research Program, a member of the American Academy of Arts and Sciences and a Founding Fellow of AAAI. He received several awards such as the Otto-Hahn-Medaille Award of the Max-Planck-Society, the Max Planck Research Award (with M. Fahle), from the Alexander von Humboldt Foundation, the MIT 50K Entrepreneurship Competition Award, the Laurea Honoris Causa from the University of Pavia in 2000 (Volta Bicentennial), the 2003 Gabor Award, the 2009 Okawa prize, and named an American Association for the Advancement of Science (AAAS) Fellow (2009).
The quest for a theory of vision: from the level framework (revised) to the invariances of the ventral stream
as author at 12th European Conference on Computer Vision (ECCV), Firenze 2012,
together with: Pietro Perona (moderator),
Hierarchical Learning Machines and Neuroscience of Visual Cortex
as author at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Barcelona 2010,
Learning in Hierarchical Architectures: from Neuroscience to Derived Kernels
as author at Machine Learning Summer School (MLSS), Chicago 2009,