We are looking forward to the 2021 OpenDP Community Meeting. Mark your calendars, this year's community meeting will be held September 22-24 from 11 AM - 3 PM EST. Details of the event will be posted when they are finalized.
Alexandra Wood gave a presentation and participated as a discussant as part of the Brussels Privacy Hub Tech Talk series, in conversation with Prof. Gianclaudio Malgieri (EDHEC Augmented Law Institute, VUB) and Nirdhar Khazanie (Google Product Manager) on the topic of "Secure Multi-party Computing."
Details are available on the Brussels Privacy Hub web site: https://brusselsprivacyhub.eu/events/tech-talks.html
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: