Tomaso Poggio

Tomaso Poggio

Tomaso Poggio is Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and at the Artificial Intelligence Laboratory. He is a founding member of the McGovern Institute, and is also the director of the Center for Brains, Minds, and Machines, a multi-institutional collaboration headquartered at the McGovern Institute. He joined the MIT faculty in 1981, after ten years at the Max Planck Institute for Biology and Cybernetics in Tubingen, Germany. He received a Ph.D. in 1970 from the University of Genoa. Poggio is a Foreign Member of the Italian Academy of Sciences and a Fellow of the American Academy of Arts and Sciences. He was awarded the 2014 Swartz Prize for Theoretical and Computational Neuroscience.

  1. Poggio, T. and Anselmi F. "Visual Cortex and Deep Networks" MIT Press, 2016
  2. J. Z. Leibo, Liao, Q., Freiwald, W., Anselmi, F., and Poggio, T., "View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation" to appear in Current Biology, 2016
  3. T. Serre, A. Oliva and T. Poggio. "A Feedforward Architecture Accounts for Rapid Categorization," Proceedings of the National Academy of Science, 104(15), pp. 6424-6429, 2007.
  4. T. Poggio, Mutch, J., and Isik, L., "Computational role of eccentricity dependent cortical magnification." CBMM memo 17, 2014
  5. Poggio T. and Masker H. "Deep vs. shallow networks : An approximation theory perspective" to appear in Analysis and Applications, special issue on Learning Theory, 14, 829, 2016
  6. Poggio, T. and S. Smale. "The Mathematics of Learning: Dealing with Data," Notices of the American Mathematical Society (AMS), Vol. 50, No. 5, 537-544, 2003.
  7. Hung, C., G. Kreiman, T. Poggio and J. DiCarlo. "Fast Readout of Object Identity from Macaque Inferior temporal Cortex," Science, Vol. 310, 863-866, 2005.
  8. Poggio, T. and E. Bizzi. "Generalization in Vision and Motor Control," Nature, Vol. 431, 768- 774, 2004.
  9. Poggio, T., R. Rifkin, S. Mukherjee and P. Niyogi. "General Conditions for Predictivity in Learning Theory," Nature, 428, 419-422, March 2004.
  10. Poggio, T. and F. Girosi. "Regularization Algorithms for Learning that are Equivalent to Multi- layer Networks," Science, 247, 978-982, 1990.