Fully Homomorphic Encryption (FHE) allows researchers to analyze encrypted data accurately without decrypting those data. It is an intriguing method for providing access to sensitive datasets while respecting both privacy concerns and licensing agreements and may eventually have significant use in privacy-protecting research protocols. This grant funds a project to demonstrate the usefulness of FHE algorithms in academic research. Computer scientists Kurt Rohloff from New Jersey Institute of Technology (NJIT) and Shafi Goldwasser from MIT are partnering with the University of Michigan’s Institute for Research on Innovation and Science (IRIS). IRIS collects sensitive data from universities on grant spending and staffing. Rohloff and Goldwater will develop an FHE computing environment and associated algorithms designed to analyze this sensitive data while observing necessary privacy-protecting protocols. Grant funds will support graduate students, postdoctoral fellows, and programmers working on the project, a social scientist to consult closely with the team about the needs and practices of empirical researchers, and outreach to potential users through workshops, publications, and presentations at professional conferences.