Emerging Frontiers of Science of Information

The next lecture in the Helsinki Distinguished Lecture Series on Future Information Technology will be given by Prof. Wojciech Szpankowski from Purdue University. The lecture will be followed by cocktails.

The event is free of charge and open to all interested in the leading research in information technology.

Please register at https://elomake.helsinki.fi/lomakkeet/52655/lomake.html by Friday, September 5 (for logistic purposes).

Video: http://video.helsinki.fi/Arkisto/flash.php?id=20294

Info page: http://video.helsinki.fi/Arkisto/tallenne.php?ID=20294

Emerging Frontiers of Science of Information

Abstract

Information is one of the defining aspects of our era, permeating every facet of our lives. Our ability to extract and effectively utilize information from various processes has the potential for significant advances in our day-to-day lives. Our current understanding of information dates back to Claude Shannon's revolutionary work in 1948, resulting in a general mathematical theory of reliable communication, which formalized modern digital communication and storage principles, paved the way for the Internet, DVDs and iPods of today. Shannon's focus on what is fundamental, and his precise quantitative analyses, continue to motivate and inspire. However, in the current world, information is not merely communicated; it is also acquired, curated, suitably abstracted and represented, aggregated, analyzed, retrieved, inferred, secured, and used in various scientific, engineering, and socio-economic processes. A comprehensive Science of Information that fundamentally builds on Shannon's basic principles, to address key challenges in transforming data to information to knowledge is critically needed.

The National Science Foundation has established a flagship Science & Technology Center on the Science of Information (CSoI) to meet the new challenges posed by the rapid advances in basic and social sciences, economics and commerce, and engineering, coupled with the ability to collect, communicate, and analyze large amounts of data. Its mission is to advance science and technology through a new quantitative understanding of the representation, communication, and processing of information.  Led by Purdue, Center member institutions include Berkeley, Bryn Mawr, Howard, MIT, Princeton, Stanford, Texas A&M, UCSD, UIUC, U. Hawaii. Other institutions (e.g., Rutgers, ETH, and LINCS, Paris) are affiliated with the Center in various roles.

In this talk, after briefly reviewing some of Shannon accomplishments, we proceed to explain novel challenges in analyzing multi-modal data, present representative results from our approach in provable security in networks, algorithms for classifying tweets through joint string complexity, and offer some interesting information-theoretic models for biological systems.

Biography

Wojciech Szpankowski is Saul Rosen Professor of Computer Science and Electrical and Computer Engineering at Purdue University. He received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Gdansk University of Technology. He held several Visiting Professor/Scholar positions, including Stanford, Hewlett-Packard Labs, INRIA, Ecole Polytechnique, the Newton Institute, Cambridge, UK, and ETH, Zurich. He is a Fellow of IEEE, the Erskine Fellow, and 2010 recipient of the Humboldt Research Award.  His research interests cover analysis of algorithms, information theory, bioinformatics, analytic combinatorics, and stability problems of distributed systems. He published the book "Average Case Analysis of Algorithms on Sequences", John Wiley & Sons, 2001. Szpankowski has been a guest editor and an editor of several technical journals, including ACM Transaction on Algorithms, Algorithmica, IEEE Transactions on Information Theory, and Combinatorics, Probability, and Computing. In 2008 he launched the interdisciplinary Institute for Science of Information whose mission is to extend classical information theory to modern settings, including knowledge discovery and information extraction from massive datasets. He is the Director of the NSF Science and Technology Center for Science of Information.