Data Science has the power to provide evidence for and numerical confirmation of social justice issues. Conscientious application of data science techniques and a mindful analysis can reveal meaningful patterns and structures in data, particularly in the context of health care and environmental issues. Understanding and developing new mathematical techniques that allow the unbiased and privacy-preserving analysis of such data sets can be a crucial step toward solving structural problems.

The projects in this theme analyze and improve the robustness and fairness of data science techniques and demonstrate their applicability to health care and environmental data sets. Our goal is to advance the mathematical underpinnings of data science and provide proof-of-concept results on real-world challenges. Our outreach activities aim at communicating our results to the general public. The participants will investigate how to address the shortcomings of current algorithms and the existing data and learn about their results' sociopolitical implications.

** Prerequisites and Expectations **

The research projects are accessible to teachers and undergraduate students with a strong background in Linear Algebra, Vector Calculus, Differential Equations, and elementary programming experience. Our site includes a comprehensive research training plan to help participants learn other project-specific materials. Our activities include professional development, a weekly lunch seminar, and social excursions in the Atlanta area.