Stephen Fienberg received this award for his 2006 paper "Privacy and Confidentiality in an e-Commerce World: Data Mining, Data Warehousing, Matching and Disclosure Limitation" published in the journal Statistical Science Vol. 21 No. 2, pp 143-154. This paper deals with the growing concerns regarding loss of privacy associated with the rapidly growing availability of online databases containing personal information. This issue poses many challenges for statistical methodology. Stephen Fienberg's work explores how such activities can take place without compromising pledges of confidentiality for individual databases. As such, it is likely to have a major impact into how large online databases are maintained and analyzed in the future.

 Stephen Fienberg is originally from Toronto and did his undergraduate training at the University of Toronto before going to Harvard University where he received his Ph.D. in 1968. He is currently the Maurice Faulk University Professor of Statistics and Social Science at Carnegie Mellon University, with appointments in the Department of Statistics, the Machine Learning Department, and Cylab. He has served as Dean of the College of Humanities and Social Sciences at Carnegie Mellon and as Vice President for Academic Affairs at York University, as well as on the faculties of the University of Chicago and the University of Minnesota. He is a member of the U. S. National Academy of Sciences, a fellow of the Royal Society of Canada, and a fellow of the American Academy of Political and Social Science. He is also a fellow of the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics. He was the 1982 recipient of the Committee of Presidents of Statistical Societies Presidents' award as the Outstanding Statistician under the age of 40, and the 2002 recipient of the Samuel S. Wilks Award of the American Statistical Association recognizing his distinguished career in statistics.