Axel Ringh

  • Assistant Professor, Applied Mathematics and Statistics, Mathematical Sciences

My research interests are in the intersection of applied mathematics and areas such as control theory, signal processing, inverse problems, and machine learning. In particular, I am interested in computational optimal transport, especially the Sinkhorn iterations and its connections to other areas, and applications of optimal transport. The latter includes problems in formation control, state estimation for ensembles, dynamic flow problems, and various applications in machine learning.