REU Site: The future of discovery: training students to build and apply open-source machine learning models and tools

Machine learning and deep learning are advanced technologies employed to address complex problems that were previously deemed too difficult for computer solutions. Students enrolled in this Research Experiences for Undergraduates (REU) program acquire practical experience across various machine learning domains, from developing open-source models to applying them in real-world scenarios.

They contribute to research advancements spearheaded by researchers at the University of Illinois, with their developed models and tools being made open source to facilitate further innovations in other fields. This project aims to cultivate a proficient workforce in advanced machine learning techniques and open-source contributions. The training provided equips students from diverse backgrounds and quantitative disciplines with the skills necessary to apply machine learning in research, preparing them to utilize these methods across multiple domains and encouraging them to pursue higher education.

The objectives of this project are to train undergraduate students, particularly those from communities with limited access to relevant resources, in the fields of machine learning and open-source software. These students subsequently apply their acquired skills to mentor-guided research projects. This on-site summer program at the University of Illinois Urbana-Champaign hosts 10 students per year, matching their preferences and interests with those of a group of mentors.

Each student is paired with two mentors—one specializing in the project's research area and the other an expert in machine learning. The program aims to enhance the students' understanding of research and graduate school, often inspiring them to pursue further education. Additionally, it equips students with valuable skills for data science and data analysis careers in industry, thereby increasing diversity in both graduate programs and professional settings.

By participating in the program, students foster connections between the University of Illinois and their home institutions, encouraging future involvement in the program and laying the groundwork for future collaborative research initiatives.

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.