Biography

Nati (Nathan) Srebro is the Lenore Blum Professor of Computer Science at the Toyota Technological Institute at Chicago and a professor of Statistics and of Computer Science at the University of Chicago. 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 at the Technion. He has also held visiting positions in UC Berkeley, EPFL and the Weizmann Institute of Science, and was consulting faculty with Google and Microsoft. Some of Prof. 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 the optimality of stochastic methods, and on the relationship between learning and optimization more broadly; study of fairness measures for non-discrimination and introduction of equalized odds; and highlighting the importance of implicit optimization bias as a central driving force in deep learning. His work has been recognized by multiple Best Paper awards at COLT (Conference on Learning Theory), ICML (International Conference on Machine Learning), and UAI (Uncertainty in Artificial Intelligence), as well a ten-year Test of Time award at ICML.