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Chandrika Kamath is a research staff member in CASC. Her interests are in the area of scientific data mining, especially in the analysis of science data from experiments, observations, and simulations. Her multi-disciplinary expertise in algorithms includes image and video processing, feature extraction, dimension reduction, pattern recognition, statistical techniques, and machine learning. Chandrika earned her Ph.D. in 1986 and her M.S. in 1984, both in Computer Science from the University of Illinois at Urbana-Champaign. She received her B.Tech degree in Electrical Engineering from the Indian Institute of Technology, Bombay, in 1981. Prior to joining LLNL in 1997, Chandrika was a Consulting Software Engineer at Digital Equipment Corporation, developing high-performance mathematical software. Her early career interests included the solution of sparse linear systems of equations and the optimization and parallelization of software on high-performance computers. From 1998 through 2007, Chandrika was both the project lead and an individual contributor for Sapphire, a project in scientific data mining. In her roles, she conducted research in analysis algorithms, implemented the algorithms in software, and applied the software to practical problems at LLNL and other DOE Laboratories. The Sapphire team was awarded the 2006 R&D 100 award for their work on the scientific data mining software. Since the successful completion of Sapphire in 2007, Chandrika has continued her work on the analysis of data from various application domains. Chandrika holds six patents in data mining. She was involved in organizing the series of workshops on Mining Scientific Data and the week-long short program at the Institute for Pure and Applied Mathematics on Mathematical Challenges in Scientific Data Mining. She is active in the organization of various data mining conferences, especially the SIAM Conference on Data Mining, where she serves as the Chair of the Steering Committee and is responsible for selecting and managing the team which organizes the conference each year. She was also a co-editor of the book Data Mining for Scientific and Engineering Applications. Her recent book, Scientific Data Mining:A Practical Perspective, was published by SIAM in 2009. Chandrika is one of the three Founding Editors-in-Chief of the Wiley journal, Statistical Analysis and Data Mining, where she focuses on the practical applications of data analysis techniques.