About our REU/RET site
The Emory Research Experience for Undergraduates and Teachers 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.
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 and four teachers for six weeks. The participants are mentored by faculty members from the Department of Mathematics and the Department of Computer Science.
We recruit students nationwide, with a strong focus on underrepresented groups and students enrolled in colleges with limited research opportunities in this area.
By involving in-service K-12 teachers in the research experience, our site will extend its impact to high-school students and help innovate curricula design and improve career counseling. We recruit teachers from the diverse Atlanta metro area and other districts nationwide.
How does it work?
Our REU/RET site introduces participants to the mathematical theory and computational tools used in applications. Our projects include a variety of topics that range from data assimilation to machine learning. Guided by faculty mentors, teams consisting of undergraduate students and teachers work toward creating new mathematical insight and designing practical solutions.
Our site’s activities will be centered around a common theme that differs each year:
- 2021: Learning from Images
- 2022: Combining Models and Data
- 2023: Data Science for Social Justice
Within each theme, faculty mentors will pose at least four research problems each tackled by one student-teacher 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 introduce 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.