Developing Open Source Tools for Differential PrivacyOpenDP is a community effort to build trustworthy, open-source software tools for statistical analysis of sensitive private data. These tools, which we call OpenDP, offer the rigorous protections of
differential privacy for the individuals who may be represented in confidential data and statistically valid methods of analysis for researchers who study the data.
The OpenDP library for Python, R, and Rust is just one area of work under the umbrella of the OpenDP project discussed on this site. To learn more about the OpenDP library, visit its
documentation or
GitHub repo.
Join Us on Slack, Github, Mailing List! Learn more about usJob OpportunitiesSpeaker: Annie Wu, Harvard University
