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.

**Eligibility:**

- Students must be enrolled in an undergraduate program at a US institution

US citizenship or permanent residency is preferred but not required (i.e., we have limited funds to support international students that are currently enrolled at a US institution)

- Students must be able to commit some time during the pre-REU/RET phase between May 22 and June 11 (no more than one-hour synchronous activity per week) and must be available full-time between June 12 and July 22.