Article Source

• Challenges and Opportunities in Differentially Private Federated Learning

Challenges and Opportunities in Differentially Private Federated Learning

• Researcher Peter Kairouz’s invited talk at the 1st Secure and Private Computing in AI and Finance workshop (sites.google.com/view/spcaif22), affiliated to the 3rd ACM International Conference on AI in Finance (ai-finance.org)

Speaker : Peter Kairouz

Peter Kairouz is a research scientist at Google, where he leads research efforts on distributed, privacy-preserving, and robust machine learning. Prior to joining Google, he was a postdoctoral research fellow at Stanford University, and before that, he was a PhD student at the University of Illinois Urbana-Champaign (UIUC). He is the recipient of the 2012 Roberto Padovani Scholarship from Qualcomm’s Research Center, the 2015 ACM SIGMETRICS Best Paper Award, the 2015 Qualcomm Innovation Fellowship Finalist Award, and the 2016 Harold L. Olesen Award for Excellence in Undergraduate Teaching from UIUC.Peter Kairouz is a research scientist at Google, where he leads research efforts on distributed, privacy-preserving, and robust machine learning. Prior to joining Google, he was a postdoctoral research fellow at Stanford University, and before that, he was a PhD student at the University of Illinois Urbana-Champaign (UIUC). He is the recipient of the 2012 Roberto Padovani Scholarship from Qualcomm’s Research Center, the 2015 ACM SIGMETRICS Best Paper Award, the 2015 Qualcomm Innovation Fellowship Finalist Award, and the 2016 Harold L. Olesen Award for Excellence in Undergraduate Teaching from UIUC.