Daniel Tenbrinck

Daniel Tenbrinck is an Academic Councilor and Acting Professor (W3) at the Department of Data Science, Faculty of Natural Sciences, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU Erlangen-Nürnberg). His career spans roles at the University of Münster, ENSICAEN (France), and FAU Erlangen-Nürnberg. He holds a PhD in Computer Science (2013) from WWU Münster.

• Research Focus: Data Science, Machine Learning, Biomedical Imaging, Variational Methods, Graph Theory, and Numerical Analysis.
• Recent Publications: Explore hypergraph p-Laplacians, Fourier neural operators for image classification, and Bregman learning frameworks for sparse networks.

Awards: Received the 2022 Teaching Award from FAU's Faculty of Natural Sciences and a 2021 performance bonus for outstanding contributions. Secured significant third-party funding, including a €1.98M BMBF grant for "COMFORT" (2024) and a €915k Bavarian Digitalization grant (2023).

Teaching: Offers courses in Numerics, Mathematical Image Processing, Inverse Problems, and Data Science seminars. Actively involved in academic program development through grants like the 2023 Innovation Fund for Teaching.