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
Vince Conitzer (Duke University)

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.

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.


Sensor Nodes
Phil Levis (Stanford University)

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.

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.


How to revolutionize education for AI, CS, and everything
Peter Norvig (Google)


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.


Technology Empowerment and the TeRK Project
Illah Nourbakhsh (Carnegie-Mellon University)

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.

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.