A Machine Learning Framework for High-Dimensional Mean Field Games and Optimal Control
Lars Ruthotto is an applied mathematician developing computational methods for machine learning and inverse problems. He is an Associate Professor in the Department of Mathematics and the Department of Computer Science at Emory University and a member of the Scientific Computing Group. Prior to joining Emory, he was a postdoc at the University of British Columbia and he held PhD positions at the University of Lübeck and the University of Münster.
Lars received an NSF CAREER award and is also supported by grants from the US Israeli Binational Science Foundation, the US Department of Energy’s Advanced Scientific Computing Research program, and the Air Force Office of Scientific Research.