Keynote Announcement

Keynote: Training Dynamics and Trust in Machine Learning by Nicolas Papernot

Bio: Nicolas Papernot is an Assistant Professor of Computer Engineering and Computer Science at the University of Toronto. He also holds a Canada CIFAR AI Chair at the Vector Institute and is a faculty affiliate at the Schwartz Reisman Institute. His research interests span the security and privacy of machine learning. Some of his group’s recent projects include proof-of-learning, collaborative learning beyond federation, dataset inference, and machine unlearning. Nicolas is an Alfred P. Sloan Research Fellow in Computer Science. His work on differentially private machine learning was awarded an outstanding paper at ICLR 2022 and a best paper at ICLR 2017. He serves as an associate chair of the IEEE Symposium on Security and Privacy (Oakland), and an area chair of NeurIPS. He co-created and co-chaired the first IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) in 2023. Nicolas earned his Ph.D. at the Pennsylvania State University, working with Prof. Patrick McDaniel and supported by a Google PhD Fellowship. Upon graduating, he spent a year at Google Brain where he still spends some of his time.