The James L. Massey Research & Teaching Award for Young Scholars recognizes outstanding achievement in research and teaching by young scholars in the Information Theory community. The 2025 recipient, , has made foundational and pioneering contributions to differential privacy and federated learning including composition theorems, optimal mechanisms for differential privacy, and privacy-preserving distributed learning. Dr. Kairouz has stimulated research in the fields of privacy and learning by leading workshops; delivering tutorials, summer courses, invited talks; participating in panels and podcasts; and by mentoring graduate students at top universities. He is the lead author of a survey paper on federated learning that has come to be regarded as the authoritative reference on the topic.
Bio: Peter Kairouz is a Senior Staff Research Scientist at Google, where he leads key research and engineering initiatives. His work advances technologies like federated learning, privacy auditing, and differential privacy, driving forward responsible AI developments. Before joining Google, he completed a Postdoctoral Fellowship at Stanford University and earned his Ph.D. from the University of Illinois at Urbana-Champaign (UIUC). He is the recipient of several prestigious awards, including the 2012 Roberto Padovani Scholarship from Qualcomm's Research Center, the 2015 ACM SIGMETRICS Best Paper Award, the 2015 Qualcomm Innovation Fellowship Finalist Award, the 2016 Harold L. Olesen Award for Excellence in Undergraduate Teaching from UIUC, the 2021 ACM CCS Best Paper Award, and the 2024 Google Research Tech Impact Award. Dr. Kairouz has organized numerous workshops and delivered tutorials on private learning and analytics at top-tier conferences, and he continues to serve in key editorial and leadership roles within the machine learning and information theory communities.