Differential privacy technology has passed a preliminary transition from being the subject of academic work to initial implementations by large organizations and high-tech companies that have the expertise to develop and implement customized differentially private methods. With a growing collection of software packages for generating differentially private releases from summary statistics to machine learning models, differential privacy is now transitioning to being usable more widely and by smaller organizations. This webinar explains how administrative data containing personal...
Congratulations to Kobbi Nissm, longtime part of the Privacy Tools Project leadership and McDewitt Chair in Computer Science at Georgetown University, for receiving Georgetown's 2020 Distinguished Achievement in Research Award!
The Harvard University Privacy Tools Project has an immediate need for a frontend developer to implement a Vue.js application based on defined workflows as well as wireframes.The project is iterative including regular interactions with the development team and UX lead.
Project elements include the creation of Vue.js components, state management with Vuex, the consumption and utilization of REST APIs, and the use of Material Design (...
The Privacy Tools Project is excited to be a partner on the new Cooperative Agreement from the US Census Bureau awarded to Boston University, aimed at developing methods for providing formal privacy guarantees for data collected through complex sample surveys:
At the Conference on Learning Theory (COLT 2020), Salil Vadhan will present "The Theory and Practice of Differential Privacy". He will survey some of the recent theoretical advances and challenges in differential privacy, highlighting connections to learning theory. Salil will also discuss efforts toward wider practical adoption, such as OpenDP, a new community effort to build a suite of trusted, open-source tools for deploying differential privacy.
"Bridging the Gap between Computer Science and Legal Approaches to Privacy" has been selected by the 2019 PET Award committee as a co-winner of the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies.
About the prize: Poster Prize of the 3rd Annual FAS Postdoc Research Symposium held June 21, 2019 at Northwest Building 52 Oxford Street. Organized by Harvard University Faculty of Arts and Sciences Office of Postdoctoral Affairs, and the FAS Postdoctoral Association. Donors include: QIAGEN, GENEWITZ,ThermoFisher Scientic, and Milipore Sigma.