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National Academy of Engineering Member

February 2009

Computer Science and Electrical Engineering Professor Deborah Estrin has been elected to the National Academy of Engineering. Election to the academy is among the highest professional distinctions accorded to an engineer. Academy membership honors those who have made outstanding contributions to engineering research, practice or education, including, where appropriate, significant contributions to the engineering literature. Professor Estrin is Director of the NSF Center for Embedded Networked Sensing, and she is being honored for the pioneering design and application of heterogeneous wireless sensing systems for environmental monitoring.

Professor Estrin holds the Jon Postel Chair in Computer Networks, and is Founding Director of the NSF-funded Center for Embedded Networked Sensing (CENS). Estrin received her Ph.D. (1985) in Computer Science from the Massachusetts Institute of Technology, and her B.S. (1980) from U.C. Berkeley. She has been co-PI on many NSF and DARPA funded projects. In 2007 Professor Estrin was elected as a Fellow of the American Academy of Arts and Sciences. She is also a fellow of the ACM, AAAS and the IEEE. She has served on numerous panels for the NSF, National Academy of Sciences/NRC, and DARPA. She has also served as an editor for the ACM/IEEE Transactions on Networks, and as a program committee member for many networking related conferences.

Professor Estrin was selected as the first ACM-W Athena Lecturer in 2006. The Athena Lectures celebrate women researchers who have made fundamental contributions to Computer Science. She was awarded the Anita Borg Institute's Women of Vision Award for Innovation in 2007.

Since the late 90's Professor Estrin's research has focused on embedded networked sensing systems, with a particular focus on applications to environmental monitoring. Most recently this work includes participatory-sensing systems, based on automated, programmable, and adaptive collection of environmental, physiological, and social parameters at the personal and community level. These systems will leverage the installed base of image and acoustic sensors that we all carry around in our pockets or on our belts-cell phones.

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