University of California, San Diego professor Tara Javidi considers how people acquire and use information in various engineering applications to be as important as the use of information for a context-specific purpose. Javidi shares a $1-million U.S. National Science Foundation (NSF) collaborative research grant to co-develop a new theoretical architecture for understanding how to best direct information flow in large cyber-physical systems.
This marks the fourth NSF grant Javidi has received in the past 18 months to address issues of information acquisition in the contexts of cognitive networking, enhanced spectrum access, computer vision, and social networking. All four projects aim to integrate tools from control theory, information theory, and statistics to jointly optimize data collection, analysis, and processing. "The problem of information collection cannot be ignored or taken for granted without introducing inherent loss of performance," Javidi contends.
Javidi and her collaborators in the new NSF project are attempting to anticipate which sensing and data collection resources are best employed, where, and when. Javidi says the proposed project's primary problem sets include that of network scale and decentralized control, and the tradeoff between cost, accuracy, and dimension of data when acquiring information.
From UCSD News
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Abstracts Copyright © 2013 Information Inc., Bethesda, Maryland, USA
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