X-CGP-ClamAV-Result: CLEAN X-VirusScanner: Niversoft's CGPClamav Helper v1.23.2 (ClamAV engine v0.103.2) Return-Path: Sender: To: CNI-ANNOUNCE Date: Thu, 10 Nov 2022 19:00:01 -0500 Message-ID: X-Original-Return-Path: Received: from [73.160.73.173] (account clifford@cni.org HELO [192.168.1.15]) by cni.org (CommuniGate Pro SMTP 6.2.15) with ESMTPSA id 39974284 for cni-announce@cni.org; Thu, 10 Nov 2022 12:30:02 -0500 X-Original-Date: Thu, 10 Nov 2022 12:30:02 -0500 From: Cliff Lynch X-Original-To: cni-announce@cni.org X-Original-Message-ID: <20221110123002278020.b4b0705f@cni.org> Subject: First Round Awards in US-UK Privacy Enhancing Technologies Challenge MIME-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit X-Mailer: GyazMail version 1.6.5 There's a very interesting (and complex) US-UK challenge program to apply innovative privacy enhancing technologies either to reduce financial fraud or the improve predictions of individual risk during pandemics. One really interesting aspect of the program is the extensive use of synthetic data. The program has just announced its first awards. It's worth at least reading the short announcement from NSF summarizing the program and the awards at https://beta.nsf.gov/news/winners-announced-first-phase-us-uk-privacy More information on the overall program here https://petsprizechallenges.com Details on the winning US teams can be found here https://drivendata.co/blog/federated-learning-pets-prize-winners-phase1 My thanks to the always-amazing Gary Price for noting this program. Clifford Lynch Director, CNI