This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program, CFDA #47.070, provides $265,054 to Weill Medical College of Cornell University to develop a consolidated framework for computational privacy and machine learning from October 1, 2022 to September 30, 2026. The framework aims to comprehensively consider optimal tradeoffs between privacy protections and critical machine learning properties like predictive utility, fairness, and distributed learning. It will provide tools to protect data privacy for real-world machine learning applications under different circumstances, allowing for the advantages of machine learning techniques on big data while protecting privacy under relevant regulations. Outcomes will be incorporated into courses and disseminated through open-source software, workshops, and involvement of undergraduate researchers and K-12 education outreach.