Technical Program

Presenter Instructions

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Preliminary Program

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Plenary Speakers

Monday 5 Sept. 0830 - 0930
Quantum and Information
Professor Benjamin Schumacher
Kenyon College, Ohio, U.S.A.

Abstract In recent years, the young science of quantum information theory has explored the implications of quantum physics for the storage, transmission and processing of information. This exploration has proceeded in three closely linked stages. (1) We have analyzed how quantum systems can be used as resources for performing familiar "classical" information tasks, such as the transmission of a message. (2) We have defined entirely new "quantum" information tasks, such as the transfer of an unknown quantum state, and we have studied the physical resources necessary to accomplish them. (3) We have started to think about information in a more general way that incorporates physics from the very outset. As quantum physics and information theory interact, each changes how we understand the fundamental concepts of the other.

Benjamin Schumacher is Professor of Physics at Kenyon College, Gambier, Ohio. His research interests are in the growing field of quantum information theory, and also in black hole thermodynamics, the relation of computation to physics, and complex systems.

Tuesday 6 Sept. 0830 - 0930
Hands-Free Writing
Professor David MacKay
Cambridge University, U.K.

Abstract Keyboards are inefficient for two reasons: they do not exploit the predictability of normal language; and they waste the fine analogue capabilities of the user's muscles. I describe Dasher, a new communication system designed using information theory. A person's gestures are a source of bits, and the sentences they wish to communicate are the sink. We aim to maximize the number of bits per second conveyed from user into text. Dasher is back-to-front arithmetic coding. (Arithmetic coding is the compression algorithm devised by Peter Elias in the 1960s, now widely used in state-of-the-art compressors.) In Dasher, the user's continuous gestures define the bits of the compressed file, and a probabilistic language model uncompresses those bits into text. Dasher works. Single-finger writing speeds exceeding 35 words per minute can be achieved. Hands-free writing is also possible, at speeds up to 25 words per minute. Dasher is free software, and it works in over one hundred languages.

David MacKay is a Professor in the Department of Physics at Cambridge University. He obtained his PhD in Computation and Neural Systems at the California Institute of Technology. His interests include machine learning, reliable computation with unreliable hardware, the design and decoding of error correcting codes, and the creation of information-efficient human-computer interfaces.

Wednesday 7 Sept. 0830 - 0930
Towards a Theoretical Foundation for Wireless and Sensor Networks
Professor P. R. Kumar
University of Illinois at Urbana-Champaign, U.S.A.

Abstract What guidance can information theory provide to the emerging technologies of wireless and sensor networks that may be at the cusp of a possible takeoff? This talk explores the themes of how much information wireless networks can transport, what should be their architecture, what protocols are appropriate for their operation, and a possible Maxwellian model of computation for sensor networks.

P. R. Kumar is Franklin Woeltge Professor of Electrical and Computer Engineering, and a Research Professor in the Coordinated Science Laboratory, at the University of Illinois, Urbana-Champaign. He obtained his B. Tech. degree from IIT Madras, and the D.Sc. degree from Washington University, St. Louis. He was the recipient of the Donald P. Eckman Award of the American Automatic Control Council. His current research interests are in wireless networks, the convergence of control with communication and computing, wafer fabrication plants, manufacturing systems, and machine learning. He is a Fellow of IEEE.

Thursday 8 Sept. 0830 - 0930
Shannon Lecture
Pyramids, Infomids, and Beyond
Professor Richard Blahut
University of Illinois at Urbana-Champaign, U.S.A.

Friday 9 Sept. 0830 - 0930
What has Information Theory Ever Done for Bioinformatics?
Professor Terry Speed
University of California, Berkeley and Walter & Eliza Hall Institute of Medical Research, Melbourne Australia.

Abstract Bioinformatics is not easy to define, and information theory is no easier, so I'll begin with a brief outline of what they mean to me. However one defines them, it is an inescapable fact that terms such as information, language, alphabet, word, communication, and code are frequently used in modern biology, and so it might be thought that they provide a link between the two topics of my talk. Perhaps sadly, I don't think this is the case, although this is not for want of effort on the part of many people. It seems to me more reasonable to regard these terms as aspects of the use of metaphor in biology, and that may even be true in engineering as well. I have always liked the statement of J Wolfowitz, speaking of the entropy function H, which he felt "for convenience and brevity" should have a name. "However", he wrote, "....we shall use only such properties of H as we shall explicitly prove. In particular, we shall not erect any philosophical systems on H as a foundation. One reason for this is that we shall not erect any philosophical systems at all, and shall confine ourselves to the proof of mathematical theorems". I'll try to take a similarly hard-nosed approach to my topic, though theorems will be rather thin on the ground. I will describe certain statistical models and model selection procedures, and along the way I will show you some of the places where codes and entropy have indeed cropped up in bioinformatics.

Terry Speed splits his time equally between the University of California at Berkeley, where he is a professor of Statistics, and the Walter & Eliza Hall Institute of Medical Research, in Melbourne, Australia, where he is joint head of the Division of Genetics & Bioinformatics. His research interests are in the application of statistics to problems in genetics and molecular biology, much of which is now called bioinformatics.