Dr. Sara Krause-Solberg

Scientific Coordinator

As scientific coordinator of Helmholtz Imaging, Sara leads the management unit at DESY. Together with her team, she coordinates the implementation and operation of the platform and is responsible for reporting to the Helmholtz Association. Sara is the contact person for all scientific questions. She implements the Helmholtz Imaging Projects Framework and ensures efficient project support throughout the project lifecycle. In addition, Sara acts as a broker for knowledge transfer.

In constant exchange with the heads of the Support and Science Units, Sara continues to shape and expand the platform according to the community’s needs.

Sara has her background in applied mathematics, where she specialized in the field of signal and image processing.

Before joining Helmholtz Imaging Sara was enrolled for eight years at three different universities as a mathematician. Throughout this time, she gained a deep insight in research as well as in the structural and administrative functionality of science. Her research considers data (e.g., audio or visual signals) to be samples from an appropriate manifold. It comprises techniques like dimensionality reduction, manifold learning, compressed sensing and neural networks.


Academic career

Since 2020 Scientific Coordinator of Helmholtz Imaging at DESY
2019-2020 Postdoc at the Institute of Mathematics at the Hamburg University of Technology
2016-2019 Postdoc at the Applied and Numerical Analysis and Optimization and Data Analysis Group at the Technical University of Munich (TUM)
2011-2015 Doctoral student at the Center for Optimization and Approximation at the Universität Hamburg, PhD completed in April 2016
2005-2011 Study of Mathematics at the Universität Hamburg and Université de Provence, Aix-Marseille I



Graf, O., Krahmer, F., & Krause-Solberg, S. (2023). One-bit Sigma-Delta modulation on the circle. Advances in Computational Mathematics, 49(3), 32. https://doi.org/10.1007/s10444-023-10032-4
Boßmann, F., Krause-Solberg, S., Maly, J., & Sissouno, N. (2022). Structural Sparsity in Multiple Measurements. IEEE Transactions on Signal Processing, 70, 280–291. https://doi.org/10.1109/TSP.2021.3137599
Iwen, M. A., Krahmer, F., Krause-Solberg, S., & Maly, J. (2021). On Recovery Guarantees for One-Bit Compressed Sensing on Manifolds. Discrete & Computational Geometry, 65(4), 953–998. https://doi.org/10.1007/s00454-020-00267-z