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Tomaso Poggio, Ph.D.
Eugene McDermott Professor in the Brain Sciences and Human Behavior
Director of the Center for Biological and Computational Learning at MIT
Department of Brain and Cognitive Sciences
Building:46-5177
Lab: The Center for Biological & Computational Learning
Email: tp@ai.mit.edu
Eugene McDermott Professor in the Brain Sciences and Human Behavior
Director of the Center for Biological and Computational Learning at MIT
Department of Brain and Cognitive Sciences
Building:46-5177
Lab: The Center for Biological & Computational Learning
Email: tp@ai.mit.edu
Computational Neuroscience
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.
In computational neuroscience, the lab has developed a model of the ventral stream in visual cortex which accounts for many physiological data (in V1,
V4 and IT) and psychophysical experiments in difficult object recognition tasks. The model performs at the level of the best computer vision systems.
Read an Interview with Professor Poggio
"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.
