Nati (Nathan) Srebro is a professor at the Toyota Technological Institute at Chicago, with cross-appointments at the University of Chicago Dept. of Computer Science and Committee on Computational and Applied Mathematics. He obtained his PhD at the Massachusetts Institute of Technology (MIT) in 2004, and previously was a post-doctoral fellow at the University of Toronto, a Visiting Scientist at IBM, and an Associate Professor of the Technion. Srebro’s research encompasses methodological, statistical and computational aspects of Machine Learning, as well as related problems in Optimization. Some of Srebro’s significant contributions include work on learning “wider” Markov networks; introducing the use of the nuclear norm for machine learning and matrix reconstruction; work on fast optimization techniques for machine learning, and on the relationship between learning and optimization. His current interests include understanding deep learning through a detailed understanding of optimization; distributed and federated learning; algorithmic fairness and practical adaptive data analysis.