Information permeates every corner of our lives and shapes our universe. Understanding and harnessing information holds the potential for significant advances. The breadth and depth of underlying concepts of the science of information transcend traditional disciplinary boundaries of scientific and commercial endeavors. Information can be manifested in various forms: value of information in economics is measured in dollars; chemical information is contained in shapes of molecules; biological information stored and processed in our cells prolongs life. So what is information? In this talk we first attempt to identify the most important features of information and define it in the broadest possible sense. We subsequently turn to the notion and theory of information introduced by Claude Shannon in 1948 that served as the backbone for digital communication. We go on to bridge Shannon information with Boltzmann's entropy, Maxwell's demon, Landauer's principle and Bennett's irreversible computations. We point out, however, that a wide spread application of information theory to economics, biology, life science and complex networks seems to be still awaiting us. We shall discuss some examples that recently crop up in biology, chemistry, economics, and quantum physics. We conclude this part of the talk with a few pertinent challenges for future research. We hope to put forward some educated questions, rather than answers, to the issues and tools that lay before researchers interested in information. In the last part of the talk, we shall discuss two examples illustrating the interplay between information theory and computer science. We first describe a truly error resilient Lempel-Ziv'77 algorithm and present its precise analysis using suffix trees and tools of analytic algorithmics. Finally, we muse on the method of types, a powerful technique in information theory and analysis of algorithms. We point out that counting types can be accomplished efficiently by enumerating Eulerian paths (Markov types) and binary trees with a given path length (universal types).

Wojciech Szpankowski received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the Technical University of Gdansk in 1976 and 1980, respectively. Currently, he is Professor of Computer Science (and by courtesy Electrical and Computer Engineering) at Purdue University. In 1992 he was Professeur Invite at INRIA-Rocquencourt, France, in 1999 he was Visiting Professor at Stanford University, and in 2006 the Erskine Fellow at University of Canterbury, Christchurch, New Zealand. Szpankowski's research interests cover mainly analysis of algorithms and information theory, and also bioinformatics, analytic combinatorics, and stability problems of distributed systems. He published the book "Average Case Analysis of Algorithms on Sequences", John Wiley & Sons, 2001.

Dr. Szpankowski has been a guest editor and an editor of technical journals, including the IEEE Transactions on Information Theory, Foundation and Trends in Communications and Information Theory, Theoretical Computer Science, Combinatorics, Probability & Computing. the ACM Transaction on Algorithms, and Int. J. Bioinformatics Research and Applications. He co-chaired the Information Theory and Networking Workshop, Metsovo, Greece, the "NSF Workshop on Information Theory and Computer Science Interface", Chicago, and the workshop "Information Beyond Shannon", Orlando. In June 2004 he directed the MSRI Graduate Program on the "Analysis of Algorithms and Information Theory". He is a Fellow of the IEEE.