Alexander Effland
Prof. Dr. Alexander Effland
  • Institute for Applied Mathematics
Research topics
  • Machine Learning/Deep Learning
  • Cardiac Modeling
  • Calculus of Variations
  • Mathematical Image Processing
  • Computer Vision with Applications in Life Science
Alexander Effland (*1987) studied mathematics and economics at the University of Bonn, where he also obtained his PhD in Numerical Analysis/Mathematical Image Processing at the Institute for Numerical Simulation in 2017. Then, he joined the Institute of Computer Graphics and Vision at Graz University of Technology as a (senior) postdoctoral researcher. Starting in April 2021, he is professor for Mathematics & Life Sciences at the Institute for Applied Mathematics (University of Bonn). Alexander Effland's research interests include mathematical image processing/computer vision (variational methods, PDE-based approaches, machine learning, deep learning), mathematics of deep learning, shape analysis, and discrete Riemannian geometry. These methods are frequently applied to problems in immunology, radiology or cardiology.
Selected publications

Pinetz T, Kobler E, Pock T, Effland A (2021) Shared Prior Learning of Energy-Based Models for Image Reconstruction. SIAM J. Imaging Sci. 14(4):1706-1748.

Effland A, Kobler E, Kunisch K, Pock T (2020) Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration. J. Math. Imaging Vis. 62:396-416

Effland A, Neumayer S, Rumpf M (2020) Convergence of the Time Discrete Metamorphosis Model on Hadamard Manifolds. SIAM J. Imaging Sci. 13(2):557-588

Kobler E*, Effland A*, Kunisch K, Pock T (2020) Total Deep Variation for Linear Inverse Problems. CVPR:7549-7558

Alexander Effland
Prof. Dr. Alexander Effland


Endenicher Allee 60

53115 Bonn

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