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Department of Computer Science

About REU

May 22, 2023 through July 28, 2023

The program will be held on-site at the Oklahoma State University during the Summer 2023


Research Experience for Undergraduates (REU) site on big data analytics at Oklahoma State University (OSU) is a ten-week summer program. The participants will engage in research projects in big data analytics under faculty mentors' mentorship and guidance.

 

The goals of the project

  1. Providing a quality research experience for undergraduates,
  2. Increasing participation of female and under-represented minorities in computing fields (especially big data analytics), which will contribute to the broadening of diversity in computer science,
  3. Preparing students to pursue graduate studies in computing and data science fields, and building a community of big data analytic researchers.

Each participant will receive

  • A $6000 stipend for the ten-week duration
  • Paid housing at the OSU campus (arranged by the program)
  • Meals, materials costs and a travel allowance.

Program Requirements

  • REU fellows must live in campus housing - arranged by the REU site program coordinator
  • REU fellows must attend weekly seminars and professional development events
  • REU fellows must prepare and submit a written report of the work done
  • REU fellows must give an oral presentation of work performed at the REU Site
  • REU fellows will work at least 35 hours per week on projects and up to 5 hours per week on professional development, attending program-wide activities and other engagements

Benefits to participants

  • Students will learn how to develop and use different machine learning (e.g., neural networks), data mining (e.g., clustering), and statistical methods (e.g., regression), with applications to graph theory, text mining, image processing, and bioinformatics.
  • Students will contribute to cutting-edge research and often publish and present in top venues.
  • The REU experience will expand the students' understanding of research by placing students in teams that include other undergraduate students and graduate students under the mentorship of the PIs and other faculty mentors. They will also learn about the ethical challenges inherent in big data analytics, from issues of privacy to problems emerging from machine learning applied to biased datasets.
  • With weekly meetings and seminars, they will also learn about other projects, share their experience in their project with other students to form a cohort.
  • The participants will also be exposed to research activities in the industry through field trips and external speakers.

To learn more, see the Projects page.

 

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