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Tomaso Poggio, Ph.D.

Department of Brain and Cognitive Sciences
Eugene McDermott Professor in the Brain Sciences and Human Behavior
Director of the Center for Biological and Computational Learning at MIT

Room 46-5177
617-253-5230 (phone)

Research Summary

The Center for Biological and Computational Learning at MIT was founded with the belief that learning is at the core of the problem of intelligence, both biological and artificial. Learning is thus the gateway to understanding how the human brain works and for making intelligent machines. CBCL studies the problem of learning within a multidisciplinary approach.

Research in the Center for Biological and Computational Learning is focused on the problem of learning in a) theory; b) engineering applications; c) neuroscience.

We have extended the CBCL model of the ventral stream to deal with cortical backprojections and control of attention and gaze. In a collaboration with the Desimone Lab we have characterized the computational role of attention in IT to allow recognition in clutter. In a paper in Nature Communication we describe a learning/vision system (inspired by a model of the dorsal stream in visual cortex) for the automatic, quantitative phenotyping of mice behavior – a useful tool for biologists.

We have formulated (with Steve Smale) a mathematical theory of hierarchical networks for learning -- guided by knowledge of cortical architectures.

Selected Publications

  • Serre, T. and T. Poggio “A Neuromorphic Approach to Computer Vision”, Communications of the ACM (online), Vol . 53, No. 10, October 2010 [doi :10.1145/1831407.1831425]
  • Chikkerur, S., T. Serre, C. Tan, and T. Poggio, "What and Where: A Bayesian inference theory of visual attention", Vision Research, [doi: 10.1016 /j.visres.2010.05.013], May 20, 2010 PDF
  • Jhuang, H., E. Garrote, J. Mutch, X. Yu, V. Khilnani, T. Poggio, A.D. Steele, and T. Serre."Automated home-cage behavioural phenotyping of mice" Nature Communications," 1, Article 68, September 7, 2010 [doi: 10.1038/ncomms1064] PDF Click here for software documentation.
  • Marr, David, Vision, MIT Press, with a new foreword by Shimon Ullman PDF and afterword by Tomaso Poggio PDF, ISBN-10: 0-262-51462-1; ISBN-13: 978-0-262-51462-0 1982, reissued July, 2010.
  • Smale, S., L. Rosasco, J. Bouvrie, A. Caponnetto, and T. Poggio, "Mathematics of the Neural Response", Foundations of Computational Mathematics, Vol. 10, 1, 67-92, 2010
  • Kouh M, Poggio T. A canonical neural circuit for cortical nonlinear operations. Neural Comput. 2008 Jun;20(6):1427-51.
  • "A Model of V4 Shape Selectivity and Invariance," (Cadieu, C., M. Kouh, A. Pasupathy, C. Connor, M. Riesenhuber, and T. Poggio) Journal of Neurophysiology, Vol. 98, 1733-1750, June, 2007. PDF
  • "Biologically Inspired System for Action Recognition," (Jhuang, H., T. Serre, L. Wolf and T. Poggio) In: Proceedings of the Eleventh IEEE International Conference on Computer Vision (ICCV), 2007 (in press). PDF
  • "A Feedforward Architecture Accounts for Rapid Categorization," (Serre, T., A. Oliva and T. Poggio) Proceedings of the National Academy of Sciences (PNAS), Vol. 104, No. 15, 6424-6429, 2007. PDF
  • "Recognition with Cortex-like Mechanisms," (Serre, T., L. Wolf, S. Bileschi, M. Riesenhuber and T. Poggio) IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 3, 411-426, 2007. PDF
  • TECHNOLOGY REVIEW by Fred Hapgood (July 11, 2006): Reverse-Engineering the Brain - At MIT, neuroscience and artificial intelligence are beginning to intersect. - Earl Miller, Jim DiCarlo and Tomaso Poggio. PDF
  • "Fast Readout of Object Identity from Macaque Inferior Temporal Cortex," (Hung, C.P., G. Kreiman, T. Poggio and J.J. DiCarlo). Science, Vol. 310, 863-866, 2005. PDF
  • "A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex," (Serre, T., M. Kouh, C. Cadieu, U. Knoblich, G. Kreiman and T. Poggio). CBCL Paper #259/AI Memo #2005-036, Massachusetts Institute of Technology, Cambridge, MA, October, 2005. PDF
  • "General Conditions for Predictivity in Learning Theory," (Poggio, T., R. Rifkin, S. Mukherjee and P. Niyogi). Nature, Vol. 428, 419-422, 2004. PDF
  • "Generalization in Vision and Motor Control," (Poggio, T. and E. Bizzi). Nature, Vol. 431, 768-774, 2004. PDF
  • "The Mathematics of Learning: Dealing with Data," (Poggio, T. and S. Smale). Notices of the AMS, Vol. 50, No. 5, 537-544, May 2003. PDF
  • "Models of Object Recognition," (Riesenhuber, M. and T. Poggio). Nature Neuroscience, 3 Supp., 1199-1204, 2000. PDF
  • "A theory of how the brain might work," (T. Poggio). In Cold Spring Harbor Symposia on Quantitative Biology, LV. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press, 899-910, 1990.
More publications

Last Updated: February 28, 2011