IEEE awards Bezdek
The IEEE (Institute of Electronics and Electrical Engineers) has named James C. Bezdek as the recipient of its 2007 Frank Rosenblatt Award, recognizing his contributions to the development of the theory and applications of the fuzzy c-means and related pattern recognition methods. These applications have helped practitioners in medical image analysis for both diagnosis and pre-operative planning of brain tumor patients.
Sponsored by the IEEE Computational Intelligence Society, the award recognizes outstanding contributions to the advancement of design, practice, techniques or theory in biologically and linguistically motivated computational paradigms.
Bezdek is Nystul Professor and Eminent Scholar of Computer Science at the University of West Florida in Pensacola. In his academic positions over the past three decades, including 17 years in his current position, he has conducted research in the theory of numerical optimization, statistical mixture models, switching regression theory, convergence theory of clustering algorithms, image processing, edge detection, relational clustering, tendency assessment and cluster validity. Applications of his work include diagnostic medicine, economics, chemistry, image processing, meteorology, web mining, geology, target recognition, regression analysis, document retrieval, structural failure and irrigation models. His current interest is clustering in very large (non-loadable) datasets for data-mining applications. He also has made fundamental contributions in other areas of computational intelligence including neural networks.
Sponsored by the IEEE Computational Intelligence Society, the award recognizes outstanding contributions to the advancement of design, practice, techniques or theory in biologically and linguistically motivated computational paradigms.
Bezdek is Nystul Professor and Eminent Scholar of Computer Science at the University of West Florida in Pensacola. In his academic positions over the past three decades, including 17 years in his current position, he has conducted research in the theory of numerical optimization, statistical mixture models, switching regression theory, convergence theory of clustering algorithms, image processing, edge detection, relational clustering, tendency assessment and cluster validity. Applications of his work include diagnostic medicine, economics, chemistry, image processing, meteorology, web mining, geology, target recognition, regression analysis, document retrieval, structural failure and irrigation models. His current interest is clustering in very large (non-loadable) datasets for data-mining applications. He also has made fundamental contributions in other areas of computational intelligence including neural networks.