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NOBEL PRIZE 2026

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NSFDirectorate for Computer and Information Science and Engineering

REU Site: Data Science Across Disciplines

Active
Institution
Marquette University, WI
Principal investigator
Praveen Madiraju
Funding
$462K
Duration
2026–2029
Open portfolio

Moonbase score

Still being scored

Abstract

The Data Science Across Disciplines Research Experiences for Undergraduates Site addresses the national scarcity of a skilled workforce capable of applying computational and data science techniques to complex, real-world problems. By immersing undergraduate students in an intensive research and mentoring environment, the program bridges the gap between classroom theory and interdisciplinary practice. The project’s novelties are its diverse range of research applications, stretching from healthcare to the societal impacts of artificial intelligence, and the Site’s long-standing recruitment network that connects students from small colleges with limited research resources to high-impact projects. The project's broader significance and importance are found in its commitment to strengthening the scientific workforce and its ability to empower students to solve problems in fields as varied as medicine, computer science education, and social science. Participants return to their home institutions as peer mentors, amplifying the program’s reach and inspiring a new generation of data-literate professionals across academia, industry, and government. The technical approach centers on a research-intensive immersion beginning with an accelerated data science boot camp to establish a foundational competency in analytics and methodology. Students utilize advanced data science and psychometric methods to investigate specific domain-driven questions. The site leverages cutting-edge research laboratories to facilitate student engagement with data cleaning, predictive modeling, statistical validation, and large language models. Expected advances include the development of novel computational solutions for domains such as healthcare and social science, alongside measurable gains in student proficiency in verbal and written communication of technical findings. The program concludes by producing researchers who demonstrate high technical competence and the ability to translate complex data into actionable insights for the benefit of public health and societal well-being. 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

  • Praveen MadirajuPI
  • Dennis BrylowCo-PI

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Directorate for Computer and Information Science and Engineering01002627DB NSF RESEARCH & RELATED ACTIVITRSCH EXPER FOR UNDERGRAD SITESreturnstudentsprogramfieldstechnicalcomputationalpsychometricaddressesutilizeconcludes

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