Panel Participants' Bios
Jacek Gwizdka (Panel Organizer & Contact Person) Assistant Professor, SCILS, Rutgers University, 4 Huntington St., New Brunswick, NJ 08901, USA Voice: 732-932-7500 ex.8236, E-mail: firstname.lastname@example.org
Dr. Jacek Gwizdka is an Assistant Professor in the Department of Library and Information Science, within the School of Communication, Information and Library Studies, at Rutgers University. Dr. Gwizdka studies affects of cognitive differences among people on their interaction with information systems. He is interested in using rich interaction logging for unobtrusive identification of user states and characteristics. He currently works on the Personalization of the Digital Library Experience project (PooDLE: http://www.scils.rutgers.edu/imls/poodle/). His research includes the study of email use and email message management, as well as work on interaction mechanisms for adding metadata to electronic notebooks and to collections of digital photos. He is a contributing author to the edited PIM volume. Dr. Gwizdka conducted research at Xerox PARC, Hewlett Packard Research Labs, and Fuji Xerox Palo Alto Labs. Dr. Gwizdka holds one patent relating to PIM. He holds a PhD in Human Computer Interaction from the Department of Mechanical and Industrial Engineering at the University of Toronto. For more information please visit: http://www.gwizdka.com and http://www.scils.rutgers.edu/∼jacekg/
Nicholas Belkin (Co-organizer & Moderator) Professor II, SCILS, Rutgers University, 4 Huntington St., New Brunswick, NJ, USA
Nicholas Belkin has been Professor of Information Science in the School of Communication, Information and Library Studies at Rutgers University since 1985. Prior to this appointment, he was Lecturer, and then Senior Lecturer in the Department of Information Science at The City University, London, from 1975. He is the recipient of the ASIST Outstanding Teacher and the ASIST Research Awards, and of the ASIST Award of Merit, as well as having served as Chair of the ACM SIGIR. His current research interests focus on the personalization of IR systems, on IR systems which support multiple information seeking strategies, and on the development of a theory of information retrieval as interaction with text. Current or recent projects include classification of interactions with information, design for IR systems which support multiple interactive information seeking strategies, studies in how users understand relevance feedback and ranking in IR, experiments in the combination of evidence for IR, interface design for IR systems, the use of language modeling techniques for developing user models for IR systems, and the personalization of the digital library experience (http://scils.rutgers.edu/imls/poodle).
Susan Dumais (Panel Participant), Principal Researcher, Context Learning and User Experience for Search (CLUES), Microsoft Research
Susan Dumais is interested in algorithms and interfaces for improved information retrieval, as well as general issues in and human-computer interaction. She joined Microsoft Research in July 1997, and works on a wide variety of information access and management issues, including: personal information management, web search, question answering, information retrieval, text categorization, collaborative filtering, interfaces for improved search and navigation, and user/task modeling. Prior to coming to Microsoft, she worked on a statistical method for concept-based retrieval known as Latent Semantic Indexing. Pointers to this work are on the Bellcore (now Telcordia) LSI page (http://lsi.research.telcordia.com/). Dr. Dumais is, among other honors, a Fellow of the ACM, and the recipient of the NJASIST Distinguished Lectureship Award.
Luanne Freund (Panel Participant), Assistant Professor, School of Library, Archival and Information Studies, University of British Columbia, Vancouver, BC, Canada
Dr. Luanne Freund is an Assistant Professor in the School of Library, Archival and Information Studies at UBC. Her areas of research are human information interaction in digital environments; pragmatic and task-based approaches to information searching; digital document genres; and evaluation of interactive information retrieval. Her dissertation research, funded by the IBM Centre for Advanced Studies, focused on the relationship between tasks and document genres in workplace information retrieval. Current work focuses on access and use of digital government information and electronic reading in academic contexts. Further information is available at: http://faculty.arts.ubc.ca/lfreund
Susan Gauch (Panel Participant), Rodger S. Kline Leadership Chair, Professor and Head of the Department of Computer Science and Computer Engineering, University of Arkansas, USA
Dr. Gauch's primary research field is Intelligent Information Agents. She received her Ph.D. from University of North Carolina – Chapel Hill in 1990 where she developed an expert search assistant for an online full-text database. While a Senior Research Scientist with the Biological Knowledge Laboratory at Northeastern University, she explored the storage, retrieval, and user interface technologies necessary to present and navigate databases of technical literature. While at the University of Kansas, from 1993–2007, her research encompassed intelligent agents for information discovery and fusion from the World Wide Web (ProFusion), content-based searching of digital video libraries, a National Science Foundation-sponsored project on the application of corpus linguistics to the field of information retrieval, and another National Science Foundation project focusing on the use of ontologies of coordinating distributed information agents. In 2007, Dr. Gauch joined the University of Arkansas to become the Head of Computer Science and Computer Engineering. One currently funded project is investigating conceptual and personalized information retrieval within the context of the Citeseer archive of computer science literature. Another NSF project is exploring the use of statistical techniques to semi-automatically create an ontology for amphibian morphology.