The program for SIGIR 2009 includes two keynote speakers, each presented in plenary session.
Susan Dumais: Salton Award Winner
The Sunday evening reception honors the past and current recipients of this prestigious award.
The Gerard Salton Award honors those who have made "significant, sustained and continuing contributions to research in information retrieval." The past recipients are Gerard Salton, Karen Spärck Jones, Cyril Cleverdon, William Cooper, Tefko Saracevic, Stephen Robertson, W. Bruce Croft, and C.J. "Keith" van Rijsbergen. For more information about the past recipients, including abstracts of their keynote presentations, see SIGIR's award site.
An Interdisciplinary Perspective on Information Retrieval
My approach to information retrieval is more user-centric than system-centric, more empirical than theoretical, but I cross these boundaries as different stages of investigation. I do so because I believe that the success of information retrieval systems depends on both the ability of systems to efficiently and effectively represent, match and rank objects, and the ability to support individuals in articulating their information needs and analyzing the retrieved results to solve the problems that motivated their search in the first place.
Bio
Susan Dumais is a Principal Researcher and manager of the Context, Learning and User Experience for Search (CLUES) Group at Microsoft Research. She has been at Microsoft Research since 1997 and has published widely in the areas of human-computer interaction and information retrieval. Her current research focuses on personal information management, user modeling and personalization, novel interfaces for interactive retrieval, and implicit measures of user interest and activity. She has worked closely with several Microsoft groups (Windows Desktop Search, Live Search, SharePoint Portal Server, and Office Online Help) on search-related innovations. Prior to joining Microsoft Research, she was at Bellcore and Bell Labs for many years, where she worked on Latent Semantic Indexing (a statistical method for concept-based retrieval), combining search and navigation, individual differences, and organizational impacts of new technology.
Susan has published more than 170 articles in the fields of information science, human-computer interaction, and cognitive science, and holds several patents on novel retrieval algorithms and interfaces. She is Past-Chair of ACM's Special Interest Group in Information Retrieval (SIGIR), and served on the NRC Committee on Computing and Communications Research to Enable Better Use of Information Technology in Digital Government, and the NRC Board on Assessment of NIST Programs. She is on the editorial boards of ACM: Transactions on Information Systems, ACM: Transactions on Human Computer Interaction, Human Computer Interaction, Information Processing and Management, Information Retrieval, New Review of Hypermedia and Multimedia, and the Annual Review of Information Science and Technology. She is an associate editor for the first and second editions of the Handbook of Applied Cognition, and serves on program committees for several conferences. She was elected to the CHI Academy in 2005, and an ACM Fellow in 2006. Susan is an adjunct professor in the Information School at the University of Washington, and has been a visiting faculty member at Stevens Institute of Technology, New York University, and the University of Chicago.
Albert-László Barabási
From Networks to Human Behavior
Highly interconnected networks with amazingly complex topology describe systems as diverse as the World Wide Web, our cells, social systems or the economy. Recent studies indicate that these networks are the result of self-organizing processes governed by simple but generic laws, resulting in architectural features that makes them much more similar to each other than one would have expected by chance. I will discuss the amazing order characterizing our interconnected world and its implications to network robustness and spreading processes. Finally, most of these networks are driven by the temporal patterns characterizing human activity. I will use communication and web browsing data to show that there is deep order in the temporal domain of human dynamics, and discuss the different ways to understand and model the emerging patterns.
Bio
Albert-László Barabási is a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics, Computer Science and Biology, as well as in the Department of Medicine, Harvard Medical School and Brigham and Women Hospital, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute. A Hungarian born native of Transylvania, Romania, he received his Masters in Theoretical Physics at the Eötvös University in Budapest, Hungary and was awarded a Ph.D. three years later at Boston University. After a year at the IBM T.J. Watson Research Center, he joined Notre Dame as an Assistant Professor, and in 2001 was promoted to the Professor and the Emil T. Hofman Chair. Barabási is the author of Linked: The New Science of Networks, currently available in eleven languages. He is the co-author of Fractal Concepts in Surface Growth (Cambridge, 1995), and the co-editor of The Structure and Dynamics of Networks (Princeton, 2005). His work lead to the discovery of scale-free networks in 1999, and proposed the Barabasi-Albert model to explain their widespread emergence in natural, technological and social systems, from the cellular telephone to the WWW or online communities. His work on complex networks have been widely featured in the media, including the cover of Nature, Science News and many other journals, and written about in Science, Science News, New York Times, USA Today, Washington Post, American Scientist, Discover, Business Week, Die Zeit, El Pais, Le Monde, London’s Daily Telegraph, National Geographic, The Chronicle of Higher Education, New Scientist, and La Republica, among others. He has been interviewed by BBC Radio, National Public Radio, CBS and ABC News, CNN, NBC, and many other media outlets.
