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Hanan Samet wins the 2011 Paris Kanellakis Theory and Practice Award

For fundamental contributions to the development of multidimensional spatial data structures and indexing.

Hanan Samet, recipient of the Paris Kanellakis Theory and Practice Award for pioneering research on quadtrees and other multidimensional spatial data structures for sorting spatial information, as well as his well-received books, which have profoundly influenced the theory and application of these structures. These spatial data structures are commonly used in biomedical imaging, games, map (GIS) and image processing, computer graphics, visualization, and other applications. Samet's contributions to, and application of, incremental nearest-neighbor search, spatial indexing, and spatial data mining exemplify the breadth of his work. Its impact can be seen in a wide array of practical applications including Google Earth, the world’s most widely used graphics application. His recent book, Foundations of Multidimensional and Metric Data Structures, was an award winner in the Best Book Competition of the American Publishers Association's Professional and Scholarly Publishers Group. His Ph.D. thesis on formal proofs of correctness of compilers and the symbolic execution of compiled execution sequences was among the earliest contributions to the field that later became known as translation validation for compilers. He is the Founding Chair of the ACM Special Interest Group on Spatial Information (SIGSPATIAL). A professor at the University of Maryland, Samet is a Fellow of ACM, IEEE, AAAS and IAPR (International Association of Pattern Recognition), and winner of the 2009 UCGIS (University Consortium for Geographic Information Science) Award. The Kanellakis Award honors specific theoretical accomplishments that significantly affect the practice of computing.

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