Statistical Analysis of Massive Data Streams: Proceedings of a Workshop (2004)
Chapter: Daryl Pregibon Keynote Address: Graph Mining - Discovery in Large Networks
Daryl Pregibon
Keynote Address: Graph Mining—Discovery in Large Networks
Abstract of Presentation
Transcript of Presentation and PowerPoint Slides
BIOSKETCH: Daryl Pregibon is head of the Statistics Research Department at AT&T Shannon Research Labs. His department is responsible for developing a theoretical and computational foundation of statistics for very large data sets. He has been with the Labs for over 20 years. He has interest in and has made contributions to the three main areas of statistics: modeling, data analysis, and computing. His specific contributions include data analytic methods for generalized linear and tree-based models, incorporating statistical expertise in data analysis software, and designing and building application-specific data structures in statistical computing. He is very active in data mining, which he defines as an interdisciplinary field combining statistics, artificial intelligence, and database research.
Dr. Pregibon received a PhD in statistics from the University of Toronto in 1979 and an MS in statistics from the University of Waterloo in 1976. He is a fellow of the American Statistical Association and has published over 50 articles in his field. He was coauthor of the best applications paper, “Empirical Bayes Screening for Multi-item Association in Large Databases,” at Knowledge Discovery and Data Mining 2001 (KDD2001) and the best research paper, “Hancock: A Language for Extracting Signatures from Data Streams,” at KDD2000. He is the past chair of CATS (Committee on Applied and Theoretical Statistics, National Academy of Sciences). He was co-chair of KDD97 and has been either a special advisor or member of the KDD program committees for the past 3 years. His is co-founder of SAIAS (Society for Artificial Intelligence and Statistics). Currently he is a member of CNSTAT (Committee on National Statistics, National Academy of Sciences), a member of the SIGKDD Executive Committee, a member of the Steering Committee of IDA (Intelligent Data Analysis), and a member of the Editorial Board of Data Mining and Knowledge Discovery.
