The Research Experience for Undergraduates (REU) site on big data analytics at Oklahoma State University (OSU) is a ten-week summer program that seeks to recruit ten undergraduate students from colleges with limited research capabilities and high concentrations of underrepresented minority populations such as African Americans and Native Americans in Oklahoma and neighboring states. The participants will engage in research projects in big data analytics under faculty mentors' mentorship and guidance and allow students to participate in interdisciplinary research that crosses a variety of fields. The goals of the project include (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. The participants will also be exposed to research activities in the industry through field trips and external speakers. This exposure will inform students' future choices about potential career paths within academia as well as within industrial settings. By the end of the program, the students should acquire skills that will lead to rewarding professional careers in science and technology, specifically in data science, expected to continue to be one of the most important fields of the future.
This REU site aims to engage undergraduates in learning experiences that increase students` interest and ability to conduct primary research in computer science, especially big data analytics research. 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. They will be introduced to different aspects of big data analytics while working on real-world projects with different types of data, including network, health, and image data. They will develop efficient novel algorithms to analyze massive real-world social and information networks, to analyze the health data collected from electronic health records and to extract meaningful visual representations of unlabeled data for better visual understanding. Research topics range from using big data to characterize hate speech in social media to understand the COVID-19 spread. 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 primary focus is to recruit female and underrepresented minorities, make UG students ready to pursue professional careers in research-oriented positions and contribute to the broadening of diversity in computer science.
This project is jointly funded by Computer and Information Science and Engineering’s Information and Intelligent Systems division and the Established Program to Stimulate Competitive Research (EPSCoR).
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.
