I am an Assistant Professor in Computer Science at the University of North Carolina at Charlotte. Prior to joining UNC Charlotte, I was a Postdoctoral Fellow at the Department of Applied Mathematics and Statistics at Johns Hopkins University (mentored by Mauro Maggioni) after completing a Ph.D. in Mathematics at Technical University of Munich in 2019, advised by Felix Krahmer. I obtained M.Sc. and B.Sc. degrees in Mathematics from TU Munich in 2015 and 2013.

My research focuses on scalable, efficient and reliable algorithms and models for machine learning and 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. To this end, I leverage mathematics ranging from high-dimensional probability, applied and computational harmonic analysis, non-convex optimization to numerical linear algebra in my research.

I have openings for highly motivated Ph.D. students (see also here), as well as for undergraduate students interested in researching the Lightning network in Summer 2023! More information can be found at Open Positions. If you have similar research interests and are interested in pursing a Ph.D., please apply here, mention my name in your application and let me know.
I am also happy to work with undergraduate and master’s students already enrolled at UNC Charlotte. If and interested in a research project or thesis, pass by Woodward Hall 230C or send me an email.

In Fall 2023, I teach a graduate course on Optimization for Machine Learning and Data Science. The targeted audience for this course are master’s and Ph.D. students in computer science, mathematics, data science and electrical engineering. Feel free to reach out for me if you have any questions.

My last name can also be written as Kuemmerle.