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
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
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
We have formulated (with Steve Smale) a mathematical theory of
hierarchical networks for learning -- guided by knowledge of cortical
- Serre, T. and T. Poggio “A Neuromorphic Approach to Computer Vision”,
Communications of the ACM (online), Vol . 53, No. 10, October 2010 [doi
- 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
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.
Last Updated: February 28, 2011