Nati Srebro obtained his PhD from the Massachusetts Institute of Technology (MIT) in 2004, held a postdoctoral fellowship with the Machine Learning Group at the University of Toronto, and was a Visiting Scientist at IBM Haifa Research Labs. Since January 2006, he has been on the faculty of the Toyota Technological Institute at Chicago (TTIC) and the University of Chicago, and has also served as the first Director of Graduate Studies at TTIC. From 2013 to 2014, he was associate professor at the Technion-Israel Institute of Technology. Prof. Srebro's research encompasses methodological, statistical and computational aspects of Machine Learning, as well as related problems in Optimization. Some of Prof. Srebro's significant contributions include work on learning "wider" Markov networks; pioneering work on matrix factorization and collaborative prediction, including introducing the use of the nuclear norm for machine learning and matrix reconstruction; and work on fast optimization techniques for machine learning, and on the relationship between learning and optimization.
- Foundations of Machine Learning, Spring 2017. Visiting Scientist.