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Public Relations Office, School of Computer Science, Carnegie Mellon University
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17 August 1999

Carnegie Mellon's Center for Automated Learning and Discovery Receives $100,000 from Microsoft for Graduate Fellowships

Carnegie Mellon University's Center for Automated Learning and Discovery (CALD) in the School of Computer Science has received a $100,000 grant from Microsoft Corporation to create two graduate fellowships for its new master's program in Knowledge Discovery and Data Mining (KDD).

The program is designed to train students to become tomorrow's leaders in this rapidly growing field. KDD offers a rich, interdisciplinary education combining topics such as advanced machine learning algorithms and the statistical principles behind them, database and data warehousing methods, complexity analysis, approaches to data visualization, privacy and security issues and specific application areas such as business, marketing and public policy.

"Today's demand for data mining expertise far exceeds the supply, and this imbalance will become more severe over the coming decade," said CALD Director, Carnegie Mellon computer science professor Tom M. Mitchell. "In the meantime, the adoption rate of data mining methods throughout the nation will be impeded by the lack of trained experts."

"By exposing students to a combination of interdisciplinary course work, hands-on applications, and cutting-edge research, we expect that our graduates will be uniquely positioned to pioneer new data mining efforts, and to pursue research on the next generation of data mining tools, algorithms and systems," added Sebastian Thrun, CALD assistant professor and co-director of the new program.

"We are pleased to support Carnegie Mellon in establishing a new academic program in this area of computing," said Usama Fayyad, senior researcher in Microsoft's Research Data Mining and Exploration (DMX) Group. "The potential for data mining to positively impact education, business, and even scientific data analysis is enormous. The future depends on laying academic foundations and scientific principles to develop the needed innovative algorithms and solutions."

The Center for Automated Learning and Discovery was established in 1997 to pursue basic science in automated learning methods, including data mining, statistical methodology, and knowledge discovery, driven by applications to problems of societal importance. The center has an active faculty of 12, and is currently sponsored by 12 industrial affiliates ranging from banks to oil producers to manufacturing firms.

Contact:

Anne Watzman, Office of Public Relations,
School of Computer Science, Carnegie Mellon University,
412.268.3830


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