Brains, Minds and Machines
Gabriel Kreiman · Tomaso Poggio · Maximilian Nickel

Thu Dec 10th 03:00 -- 09:00 PM @ Level 5 Room 510 BD
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The science of today enables engineering solutions of tomorrow. In this symposium we will discuss state-of-the-art results in the scientific understanding of intelligence and how these results enable new approaches to replicate intelligence in engineered systems.

Understanding intelligence and the brain requires theories at different levels, ranging from the biophysics of single neurons to algorithms, computations, and a theory of learning. In this symposium, we aim to bring together researchers from machine learning, artificial intelligence, neuroscience, and cognitive science to present and discuss state-of-the-art research that is focused on understanding intelligence at these different levels.

Central questions of the symposium include how intelligence is grounded in computation, how these computations are implemented in neural systems, how intelligence can be described via unifying mathematical theories, and how we can build intelligent machines based on these principles.

Our core goal is to develop a science of intelligence, which means understanding human intelligence and its basis in the circuits of the brain and the biophysics of neurons. We also believe that the engineering of tomorrow will need the science of today, in the same way as the basic research of Hubel and Wiesel in the ‘60s was the foundation for today's deep learning architectures.

The symposium will consist of talks by invited speakers and a panel discussion.
Invited speakers and panelists at the symposium include

- Surya Ganguli (Stanford University)
- Demis Hassabis (Google DeepMind)
- Christof Koch (Allen Institute for Brain Science)
- Gabriel Kreiman (Harvard University)
- Gary Marcus (New York University)
- Tomaso Poggio (MIT)
- Andrew Saxe (Harvard University)
- Terrence Sejnowski (Salk Institute)
- Joshua Tenenbaum (MIT)

Author Information

Gabriel Kreiman (Harvard Medical School)

Gabriel Kreiman is Associate Professor at Children's Hospital, Harvard Medical School and leads the thrust to study neural circuits in the Center for Brains, Minds and Machines (MIT/Harvard). He received the NSF Career Award, the NIH New Innovator Award and the Pisart Award for Vision Research. Research in the Kreiman laboratory combines computational, neurophysiological and behavioral tools to further our understanding of how intelligent computations are implemented by neural circuits in the brain. His work has shed light on the biological codes to represent information in cortex and the fundamental principles underlying computations involved in vision and learning. For further details about his work, please visit

Tomaso Poggio (MIT)

Tomaso A. Poggio, is the Eugene McDermott Professor in the Dept. of Brain & Cognitive Sciences at MIT and the director of the new NSF Center for Brains, Minds and Machines at MIT of which MIT and Harvard are the main member Institutions. He is a member of both the Computer Science and Artificial Intelligence Laboratory and of the McGovern Brain Institute. He is an honorary member of the Neuroscience Research Program, a member of the American Academy of Arts and Sciences, a Founding Fellow of AAAI and a founding member of the McGovern Institute for Brain Research. Among other honors he received the Laurea Honoris Causa from the University of Pavia for the Volta Bicentennial, the 2003 Gabor Award, the Okawa Prize 2009, the AAAS Fellowship and the 2014 Swartz Prize for Theoretical and Computational Neuroscience. He is one of the most cited computational scientists with contributions ranging from the biophysical and behavioral studies of the visual system to the computational analyses of vision and learning in humans and machines. With W. Reichardt he characterized quantitatively the visuo-motor control system in the fly. With D. Marr, he introduced the seminal idea of levels of analysis in computational neuroscience. He introduced regularization as a mathematical framework to approach the ill-posed problems of vision and the key problem of learning from data. In the last decade he has developed an influential hierarchical model of visual recognition in the visual cortex. The citation for the recent 2009 Okawa prize mentions his “…outstanding contributions to the establishment of computational neuroscience, and pioneering researches ranging from the biophysical and behavioral studies of the visual system to the computational analysis of vision and learning in humans and machines.” His research has always been interdisciplinary, between brains and computers. It is now focused on the mathematics of learning theory, the applications of learning techniques to computer vision and especially on computational neuroscience of the visual cortex. A former Corporate Fellow of Thinking Machines Corporation and a former director of PHZ Capital Partners, Inc., he is a director of Mobileye and was involved in starting, or investing in, several other high tech companies including Arris Pharmaceutical, nFX, Imagen, Digital Persona and Deep Mind. Tomaso Poggio Eugene McDermott Professor Director NSF Science & Technology Center for Brains, Minds and Machines(CBMM) Core founding scientific advisor, MIT Quest for Intelligence McGovern Institute CSAIL (Computer Science and Artificial Intelligence Lab) Brain Sciences Department M.I.T., 46-5177B see 43 Vassar Street Cambridge, MA 02142 E-mail: Phone: 617-253-5230 Fax: 617-253-2964 Web: PoggioLab Web page:

Maximilian Nickel (Massachusetts Institute of Technology)

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