Jan Lellmann

Jan Lellmann is a Professor at the Institute of Mathematics and Image Computing of the University of Lübeck, with affiliations to Fraunhofer MEVIS. His research focuses on variational image processing, emphasizing the systematic formulation of prior knowledge into energy functions for improved accuracy and data efficiency.

• Applications span medical imaging, earth sciences, and biological data analysis.
• He develops non-smooth optimization methods for problems with combinatorial aspects like image segmentation.

His recent work includes manifold-constrained optimization and quantum algorithms for imaging tasks. He has contributed software libraries like MFOPT (for manifold optimization) and COAL (for convex energy minimization).

Scientific Awards:

• Best Student Paper Award at SSVM 2021
• Honorable Mention at CVPR 2016

• Integration of quantum computing with classical image registration.
• Advancements in Riemannian geometry for protein dynamics and cryo-EM.
• Development of meta-learning frameworks for adaptive image alignment.
• Focus on non-smooth and higher-order regularization for sparse data reconstruction.