Otmar Scherzer

Prof. Otmar Scherzer is a distinguished academic at the Faculty of Mathematics, Department of Mathematics, University of Vienna. His work spans Inverse Problems, Mathematical Imaging, Computational Mathematics, and Applied Mathematics, with a focus on tomography, neural networks, and medical imaging. Over nearly two decades, he has published extensively in journals like Inverse Problems, SIAM Review, and IEEE Transactions.

• 2025: Advanced data-driven regularization and neural network applications in inverse problems.
• 2024: Explored diffraction tomography, Hilbert space approaches to scattering, and motion detection algorithms.
• 2023: Addressed uncertainty quantification, visco-acoustic imaging, and Doppler ultrasound interpolation.

His recent research emphasizes uncertainty-aware blob detection, strain reconstruction in elastography, and Fourier-based tomography. Publications frequently integrate numerical experiments and computational inverse methods, reflecting a blend of theoretical and applied mathematics.

Prof. Scherzer collaborates with institutions like RICAM (Johann Radon Institute) and contributes to hybrid imaging modalities such as quantitative optical coherence elastography and photoacoustic tomography. He has supervised projects in 3D shape reconstruction and non-convex regularization, though specific student names are not listed in the provided data.