People
Members of the NEITALG research team.
Principal Investigator
TUM School of Computation, Information and Technology
Technical University of Munich
Massimo Fornasier
The research of Massimo Fornasier embraces a broad spectrum of problems in mathematical modeling, analysis and numerical analysis. Fornasier is particularly interested in the concept of compression as appearing in different forms in data analysis, image and signal processing, and in the adaptive numerical solutions of partial differential equations or high-dimensional optimization problems.
Fornasier received his doctoral degree in computational mathematics in 2003 from the University of Padua, Italy. After spending from 2003 to 2006 as a postdoctoral research fellow at the University of Vienna and University of Rome La Sapienza, he joined the Johann Radon Institute for Computational and Applied Mathematics (RICAM) of the Austrian Academy of Sciences where he served as a senior research scientist until March 2011. He was an associate researcher from 2006 to 2007 for the Program in Applied and Computational Mathematics of Princeton University, USA. In 2011 Fornasier was appointed Chair of Applied Numerical Analysis at TUM. He is a member of VQR, a panel responsible for the evaluation of the quality of research in Italy. He is also a member of the editorial boards of Networks and Heterogeneous Media, Journal of Fourier Analysis and Applications and Calcolo.
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Alessandro Scagliotti
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Francesco Mattesini
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Francesco Colasanto
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Viktor Stein
Viktor Stein is a postdoctoral researcher in Applied Numerical Analysis at the Technical University of Munich (TUM) and a junior member of the Munich Center for Machine Learning (MCML). His research interests include metric gradient flows in the Wasserstein geometry and kernelized variants, kinetic extensions thereof, like accelerated gradient flows, particle methods for generative modeling, designing and investigating the properties of suitable loss functionals, which combine, e.g., optimal transport, $f$-divergences, and kernel distances, and the infinite-dimensional geometry of probability measures. He wrote my PhD thesis under the supervision of Gabriele Steidl at TU Berlin in the Applied Mathematics Group at TU Berlin and the Berlin Mathematical School, and will defend his thesis in late June 2025.
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Lukang Sun
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Christian Fiedler
Postdoctoral Researcher
TUM School of Computation, Information and Technology
Technical University of Munich
Tim Roith
PhD Student
TUM School of Computation, Information and Technology
Technical University of Munich
Jona Klemenc