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Invited Speakers
The symposium will feature four invited talks on AI and education:
Attracting Students to Computer Science Using Artificial Intelligence,
Economics, and Linear Programming
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Vince Conitzer
(Duke University)
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Abstract
Artificial intelligence practitioners have always used techniques from
economics, but this trend has increased tremendously in more recent years.
Current AI research focuses increasingly on topics from microeconomics such
as game theory, auction theory, and social choice theory. This research
has reached a sufficient level of maturity that it is now possible to teach
a complete undergraduate course on computational microeconomics. Such a
course has great potential to attract new students to computer science. It
can include appealing topics such as computer poker. More importantly, it
can be taught effectively without requiring any programming background, by
focusing strictly on linear programming-based approaches. There are nice
modeling languages for linear programming, such as the GNU MathProg
language, which provide a gentle introduction to some basic programming
concepts. I will discuss the results of a course I taught last semester.
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Bio
Vincent Conitzer is an Assistant Professor of Computer Science and
Economics at Duke University. He received Ph.D. (2006) and M.S. (2003)
degrees in Computer Science from Carnegie Mellon University, and an
A.B. (2001) degree in Applied Mathematics from Harvard University. He
also received an Alfred P. Sloan Research Fellowship (2008), the
IFAAMAS Victor Lesser Distinguished Dissertation Award (2007), the
AAMAS Best Program Committee Member Award (2006), and an IBM
Ph.D. Fellowship (2005). He has published over 40 technical papers on
computational issues in game theory, mechanism design, auctions,
elections, and other negotiation settings.
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Sensor Nodes
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Phil Levis
(Stanford University)
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Abstract
Complexity is a hurdle to teaching introductory computer science.
Explaining how something in a computer today works, from the user to
the hardware, covers so many intermediate layers of technical
complexity that we're lucky if a graduate student understands them
all. In this talk, I argue that simplicity engenders a type of
excitement and interest which computer science education has, for the
most part, lost. But not all computers need to be complex: some are
simple by necessity. In particular, an emerging class of computing
device, embedded wireless sensors, are small, simple computers with
integrated storage, communication, computation, and sensing. Programs
on these devices must deal with all of the core problems we encounter
in complex software today, such as concurrency, ambiguity, lossy and
noisy data and distributed algorithms. Furthermore, they are hands-on:
being small devices, students can use them as physical interfaces to
larger systems. I'll present the capabilities and possibilities these
devices bring, and note some of their educational challenges.
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Bio
Philip Levis is an Assistant Professor in the Computer Science and
Electrical Engineering Departments of Stanford University. He
researches embedded wireless networks, including programming
languages, operating systems, network protocols, algorithms and
applications. His prior work includes TOSSIM, the TinyOS simulator,
the Trickle algorithm for data dissemination in wireless networks,
application-specific virtual machines, sensornet OS power management,
wireless measurement, and wireless protocol design. His software has
thousands of users and runs on millions of nodes.
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How to revolutionize education for AI, CS, and everything
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Peter Norvig
(Google)
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Bio
Peter Norvig is a Fellow of the American Association for Artificial
Intelligence and the Association for Computing Machinery. At Google
Inc he was Director of Search Quality, responsible for the core web
search algorithms from 2002-2005, and has been Director of Research
from 2005 on.
Previously he was the head of the Computational Sciences Division at
NASA Ames Research Center, making him NASA's senior computer
scientist. He received the NASA Exceptional Achievement Award in
2001. He has served as an assistant professor at the University of
Southern California and a research faculty member at the University of
California at Berkeley Computer Science Department, from which he
received a Ph.D. in 1986 and the distinguished alumni award in
2006. He has over fifty publications in Computer Science,
concentrating on Artificial Intelligence, Natural Language Processing
and Software Engineering, including the books Artificial Intelligence:
A Modern Approach (the leading textbook in the field), Paradigms of AI
Programming: Case Studies in Common Lisp, Verbmobil: A Translation
System for Face-to-Face Dialog, and Intelligent Help Systems for
UNIX. He is also the author of the Gettysburg Powerpoint Presentation
and the world's longest palindromic sentence.
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Technology Empowerment and the TeRK Project
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Illah Nourbakhsh
(Carnegie-Mellon University)
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Abstract
The CREATE lab has embarked on a series of public projects to try and
understand how significant scaling may be feasible using robotics for
technology empowerment and community-building. Our work is now
hybridizing the Global Connection efforts together with our more
traditional Telepresence Robot Kit and CMUcam educational tools, and
we are carrying out experiments locally in Pittsburgh and
internationally in collaboration with UNESCO. I will describe the
current status of our community products, describing both our target
communities spanning the cognitive pipeline, and the new technologies
we have been releasing.
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Bio
Illah R. Nourbakhsh is an Associate Professor of Robotics and head of
the Robotics Masters
Program in The
Robotics Institute at Carnegie Mellon University. He is co-founder of
the Toy Robots
Initiative at The Robotics Institute, director of the
Center for Innovative Robotics
and director of the Community Robotics, Education and Technology
Empowerment (CREATE) lab. He
is also co-PI of the Global Connection Project,
home of the Gigapan project. He
is also co-PI of the Robot 250
city-wide art+robotics fusion program in Pittsburgh. His current
research projects include educational and social robotics and
community robotics. Illah recently co-authored the MIT Press textbook,
Introduction to Autonomous Mobile Robots.
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