[visionlist] Brains, Minds and Machines Summer Course 2017

Gabriel Kreiman gkreiman at gmail.com
Wed Mar 8 09:40:18 EST 2017


The deadline is approaching to apply for the 2017 Brains, Minds and
Machines summer course at MBL, Woods Hole:



*Brains, Minds and Machines Summer Course 2017*

A Special Topics Course at MBL Woods Hole, MA

Directors: Gabriel Kreiman, Children’s Hospital, Harvard Medical School;
and Tomaso Poggio, Massachusetts Institute of Technology

Course Date: August 13 – September 3, 2017

*Application Deadline: March 14, 2017*

More information: http://cbmm.mit.edu/summer-school/2017



*Course Description*



The basis of intelligence – how the brain produces intelligent behavior and
how we may be able to replicate intelligence in machines – is arguably the
greatest problem in science and technology. To solve it, we will need to
understand how human intelligence emerges from computations in neural
circuits, with rigor sufficient to reproduce similar intelligent behavior
in machines. Success in this endeavor ultimately will enable us to
understand ourselves better, to produce smarter machines, and perhaps even
to make ourselves smarter. Today’s AI technologies, such as Watson and
Siri, are impressive, but their domain specificity and reliance on vast
numbers of labeled examples are obvious limitations; few view this as
brain-like or human intelligence. The synergistic combination of cognitive
science, neurobiology, engineering, mathematics, and computer science holds
the promise to build much more robust and sophisticated algorithms
implemented in intelligent machines. The goal of this course is to help
produce a community of leaders that is equally knowledgeable in
neuroscience, cognitive science, and computer science and will lead the
development of true biologically inspired AI.



The class discussions will cover a range of topics, including:

   - Neuroscience: neurons and models
   - Computational vision
   - Biological vision
   - Machine learning
   - Bayesian inference
   - Planning and motor control
   - Memory
   - Social cognition
   - Inverse problems & well-posedness
   - Audition and speech processing
   - Natural language processing



These discussions will be complemented in the first week by MathCamps and
NeuroCamps, to refresh the necessary background. Throughout the course,
students will participate in workshops and tutorials to gain hands-on
experience with these topics.



Core presentations will be given jointly by neuroscientists, cognitive
scientists, and computer scientists. Lectures will be followed by
afternoons of computational labs, with additional evening research
seminars. To reinforce the theme of collaboration between (computer science
+ math) and (neuroscience + cognitive science), exercises and projects
often will be performed in teams that combine students with both
backgrounds.



The course will culminate with student presentations of their projects.
These projects provide the opportunity for students to work closely with
the resident faculty, to develop ideas that grow out of the lectures and
seminars, and to connect these ideas with problems from the students’ own
research at their home institutions.



This course aims to cross-educate computer engineers and neuroscientists;
it is appropriate for graduate students, postdocs, and faculty in computer
science or neuroscience. Students are expected to have a strong background
in one discipline (such as neurobiology, physics, engineering, and
mathematics). Our goal is to develop the science and the technology of
intelligence and to help train a new generation of scientists that will
leverage the progress in neuroscience, cognitive science, and computer
science. The course is limited to 30 students.



*2017 Course Faculty*

Barbu, Andrei, MIT
DiCarlo, James Massachusetts Institute of Technology
Freiwald, Winrich, The Rockefeller University
Gershman, Samuel, Harvard University
Ghazanfar, Asif, Princeton University
Kanwisher, Nancy, MIT
Katz, Boris, MIT
Koch, Christof, Allen Institute for Brain Science
Kreiman, Gabriel, Harvard Medical School
Jeff Lichtman, Harvard University
Livingstone, Marge, Harvard Medical School
Mahadevan, L, Harvard University
McDermott, Josh, MIT
Meyers, Ethan, Hampshire College
Nakayama, Ken, Harvard University
Poggio Tomaso, MIT
Roig, Gemma, MIT
Rosasco, Lorenzo, MIT
Saxe, Rebecca, MIT
Schulz, Laura, MIT
Sompolinsky, Haim, Hebrew University
Spelke, Elizabeth, Harvard University
Tegmark, Max, MIT
Tenenbaum, Josh, MIT
Ullman, Shimon, Weizmann Institute
Wilson, Matt, MIT
Winston, Patrick, MIT
Wolfe, Jeremy, Harvard Medical School

-- 
Gabriel Kreiman
gkreiman at gmail.com
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