About our REU site

The Emory Research Experience for Undergraduates site focuses on computational mathematics and its applications in data science, which impacts nearly every field of science, industry, and society. Despite its growing importance, the number of academic training opportunities in data science has not kept pace with the rapid growth in demand from private and public entities.

We have been running this program since the summer of 2021. Between 2021 and 2023, the site was held in conjunction with the Emory Research Experience for Teacher site and we hosted about a dozen in-service high school teachers.

Our site emphasizes developing research and professional skills that enable participants to understand, conduct, and effectively communicate research in this booming area. Each summer, our site trains at least twelve undergraduates for eight weeks. The participants are mentored by faculty members from the Department of Mathematics and the Department of Computer Science.

We recruit students nationwide, focusing strongly on underrepresented groups and students enrolled in colleges with limited research opportunities in this area.

How does it work?

Our REU site introduces participants to the mathematical theory and computational tools used in applications. Our projects include various topics ranging from data assimilation to machine learning. Guided by faculty mentors, undergraduate students work toward creating new mathematical insights and designing practical solutions.

Our site’s activities will be centered around a common theme that differs each year:

  • 2024: Learning from Images
  • 2025: Combining Models and Data
  • 2026: Discovering new Mathematics with Computational and Machine Learning Methods

Within each theme, faculty mentors will pose at least four research problems tackled by one student team.

New insights of relevance to the broader scientific community will be created and disseminated in several ways, for example,

  • oral presentations
  • poster presentations
  • student/teacher-authored publications
  • open source software
  • blog posts / project websites
  • course materials for classroom-use

What pre-requisites are needed?

By definition, the research projects will take participants beyond standard coursework. To fill the gap, our site’s educational component introduces the participants to a range of mathematical techniques, including machine learning, deep neural networks, numerical linear algebra, optimization, partial differential equations, and statistics. The faculty mentors also provide their mentees with professional and computational skills, including scientific writing, oral and poster presentations, and cloud computing. The weekly seminar will feature group activities and faculty-led presentations on data and ethics, algorithmic bias, public scholarship.

Information for Applicants

Interested in joining? Learn more about about requirements, deadlines, and application materials on the information for applicants page.