Google Keynote: Federated Learning & Federated Analytics-Research, Applications, & System Challenges

A Google TechTalk, presented by Hubert Eichner, Francoise Beaufay, Ravi Kumar & Peter Kairouz, 2021/11/9 ABSTRACT: An overview of federated analytics applications and algorithms, federated learning applications and algorithms, and how we build an infrastructure and scale it. About the Speakers: Peter Kairouz, Google (moderator) Peter Kairouz is a research scientist at Google, where he focuses on federated learning research and privacy-preserving technologies. Before joining Google, he was a Postdoctoral Research Fellow at Stanford University. He received his Ph.D. in electrical and computer engineering from the University of Illinois at Urbana-Champaign (UIUC). Francoise Beaufay, Google Françoise Beaufay is a Distinguished Scientist at Google, where she leads a team of engineers and researchers working on speech recognition and mobile keyboard input. Her area of expertise covers deep learning, language modeling and other technologies related to natural language processing, with a recent focus on privacy-preserving on-device learning. Françoise studied Mechanical and Electrical Engineering in Brussels, Belgium. She holds a PhD in Electrical Engineering and a PhD minor in Italian Literature, both from Stanford University. Hubert Eichner, Google Hubert Eichner received his PhD from Max-Planck Institute of Neurobiology in Theoretical Neuroscience then joined Microsoft to work on embedded speech recognition. He is currently serving as overall tech lead for Google's production Federated Learning platform. Ravi Kumar, Google Ravi Kumar has been a research scientist at Google since 2012. Prior to this, he was at the IBM Almaden Research Center and at Yahoo! Research. His interests include algorithms for massive data, privacy, and the theory of computation. For more information about the workshop: https://events.withgoogle.com/2021-workshop-on-federated-learning-and-analytics/#content