I am a Postdoctoral Fellow at the Department of Applied Mathematics and Statistics at Johns Hopkins University, mentored by Mauro Maggioni. Before that, I completed a Ph.D. in Mathematics at Technical University of Munich, advised by Felix Krahmer, in 2019. I also obtained M.Sc. and B.Sc. degrees in Mathematics from TU Munich in 2015 and 2013, respectively.
My research focuses on developing and improving the mathematical foundations of data science. I am interested in the theory and practice of addressing computational and statistical challenges arising from models involving sparsity, graph or low-rank structures with efficient optimization methods.
In my research I address these questions using high-dimensional probability, applied and computational harmonic analysis, non-convex optimization and numerical linear algebra.
My last name can also be written as Kuemmerle.