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-
 Student Participants
- Katelyn Gao (MIT)
- Heather Hardeman (University of Montevallo)
- Edward Lim (Johns Hopkins University)
- Cristian Potter (East Carolina University)
- Advisors
- Carl D. Meyer (Faculty Advisor, NC State)
- Ralph Abbey (Graduate Student Advisor, NC State)
- Project Description
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Given unorganized data that may be derived from text, images,
or simply raw numerics, the objective is to develop new and innovative
techniques for detecting, revealing, and analyzing hidden patterns and
clusters of information that exhibit some sort of similarity
or commonality. The size and diverse nature of the data sets of interest
make this a formidable but extremely important problem in areas that include national security, military
intelligence, bioinformatics, knowledge discovery, corporate sales strategy, and industrial and government forecasting, decision making,
and planning.
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The first part of
the project will be to learn and understand how to use some of the
state-of-the art techniques by analyzing some selected practical
applications.
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The second part of the research will involve
exploring the possibilities of
developing some new methodologies and algorithms.
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The mathematics employed involves linear algebra, probability and
statistics, networks and graphs, numerical analysis, and
scientific computing principles.
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Presentations
- Final Report
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