REU Site: University of North Carolina at Greensboro - Complex Data Analysis using Statistical and Machine Learning Tools
- Institution
- University of North Carolina Greensboro, NC
- Principal investigator
- Jianping Sun
- Funding
- $405K
- Duration
- 2023–2027
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Abstract
Technological innovations now allow the collection of massive amounts of data at low cost. Appropriate handling and analysis of such data is vital training for the future generation of graduates. This award will support the University of North Carolina at Greensboro Complex Data Analysis using Statistical and Machine Learning Tools Research Experiences for Undergraduates site, which will provide 10 weeks of training and research opportunities in the analysis of complex data to ten undergraduates each summer, 2023-2025. The program will aim to recruit students from diverse backgrounds and educational institutions. This research experience is intended to motivate student participants to go on to graduate study in mathematical sciences and to become skilled data analytics professionals. The program will introduce students to a range of analysis techniques for complex data. The research projects will introduce them to a range of techniques appropriate to different types of data complexity. Potential projects include working with geospatial sources (such as Census, election, and epidemiological data) and human genome sequencing data. Students in the program will also receive professional skills training and give presentations on their work, submit papers for publication, and participate in conferences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Jianping SunPI
- Sat Gupta
- Xiaoli Gao
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