REU/RET Site: Computational Mathematics for Data Science

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The Emory Research Experience for Undergraduates and Teachers site focuses on computational mathematics and its applications in data science. Data science is of fundamental and strategic importance to the US and impacts nearly every field of science. However, the number of academic training opportunities and skilled workers has not kept pace with the rapid growth in demand from private and public entities. The site emphasizes developing research and professional skills that will increase the participants' ability to understand, conduct, and effectively communicate research in data science and computational mathematics. The three-year program will train twelve undergraduates and four teachers annually for six weeks. Faculty members from Emory's Departments of Mathematics and Computer Science will supervise and mentor the participants. The site's activities will equip undergraduate students with the mathematical and computational skills required to launch careers in this area and will motivate them to pursue a graduate degree. Student recruitment will be 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, the site will extend its impact to high-school students and help innovate curricula design and improve career counseling. The teachers will be recruited from the diverse Atlanta metro area and other districts nationwide.The REU/RET site will introduce undergraduate students and teachers to the mathematical theory and computational tools used in applications ranging from data assimilation to machine learning and enable them to advance these fields by solving research problems in teams. The site's activities will be centered around a common theme that differs each year. The site's annual research themes will be Learning from Images, Combining Models with Data, and Data Science for Social Justice, respectively. Within each theme, faculty mentors will pose at least four research problems and advise student-teacher teams to work on innovative solutions. New insights of relevance to the broader scientific community will be created and disseminated in student/teacher-authored publications, open-source software, and online blogs. The teachers will also create and make freely available materials for classroom-use. The research projects will take participants beyond standard coursework. The site's educational component will 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 will 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.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.