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Institute for Industrial Mathematics
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Simon Hubmer

Research interest

  • Inverse and Ill-Posed Problems
  • Regularization Techniques
  • Tomographic and Medical Imaging
  • Parameter Estimation Problems
  • Phase Retrieval and Applications

Curriculum Vitae

born in Wels, Austria

Bachelor Studies Technical Mathematics, JKU Linz, Austria

Master Studies Industrial Mathematics, JKU Linz, Austria

PhD Studies Technical Sciences, JKU Linz,
 Austria

PhD student at the Doctoral Program "Computational Mathematics", JKU Linz.

Research Scientist at RICAM

Recipient of the EAIP Young Scientist Award.

Mandatory civilian service to the Austrian government, Linz, Austria.

Mathematics consultant, MathConsult GmbH, Linz, Austria.

University Assistant, Industrial Mathematics Institute, JKU Linz, Austria.

Peer reviewed journal publications

  • X. Li, S. Hubmer, S. Lu, R. Ramlau. Regularization of linear inverse problems with irregular noise using embedding operators. SIAM Journal on Imaging Sciences, Volume 17, Number 4, pp. 2053–2075, 2024, doi: 10.1137/24M1636307, Green O
  • W. Rannetbauer, S. Hubmer, C. Hambrock, R. Ramlau. Predictive modelling of critical variables for improving HVOF coating using gamma regression models. Journal of Mathematics in Industry, Volume 14, Number 7, 2024, doi: 10.1186/s13362-024-00146-9, Gold OA.
  • W. Rannetbauer, C. Hambrock, S. Hubmer, R. Ramlau. Enhancing Predictive Quality in HVOF Coating Technology: A Comparative Analysis of Machine Learning Techniques. Proceedia Computer Science, Volume 232, pp. 1377–1387, 2024, doi: 10.1016/j.procs.2024.01.136, Gold OA..
  • S. Hubmer, E. Sherina, R. Ramlau, M. Pircher, R. Leitgeb. Subaperturebased Digital Aberration Correction for OCT: A Novel Mathematical Approach. SIAM Journal on Imaging Sciences, Volume 16, Number 4, pp.1857–1885, 2023, doi: 10.1137/22M1543240, Green OA.
  • S. Hubmer, E. Sherina, R. Ramlau. Characterizations of Adjoint Sobolev Embedding Operators with Applications in Inverse Problems. Electronic Transactions on Numerical Analysis, Volume 59, pp. 116–144, 2023, doi: 10.1553/etna_vol59s116, Gold OA.
  • F. Hinterer, M. C. Schneider, S. Hubmer, M. Lopez-Martinez, R. Ramlau, G. J. Schütz. Localization of fixed dipoles at high precision by accounting for sample drift during illumination. Applied Physics Letters, Volume 123, Number 2, pp. 023703, 2023, doi: 10.1063/5.0137834, Green OA.
  • M. Quellmalz, L. Weissinger, S. Hubmer, P. D. Erchinger. A Frame Decomposition of the Funk-Radon Transform. In: Scale Space and Variational Methods in Computer Vision, Springer International Publishing, Cham, pp. 42–54, 2023, doi: 10.1007/978-3-031-31975-4_4, Green OA.
  • F. Hinterer, S. Hubmer, P. Jeethwa, K. M. Soodhalter, G. van de Ven, R. Ramlau. A Projected Nesterov–Kaczmarz Approach to Stellar PopulationKinematic Distribution Reconstruction in Extragalactic Archaeology. SIAM Journal on Imaging Sciences, Volume 16, Number 1, pp. 192–222, 2023, doi: 10.1137/22M1503002, Green OA.
  • L. Krainz, E. Sherina, S. Hubmer, M. Liu, W. Drexler, O. Scherzer. Quantitative Optical Coherence Elastography: A novel Intensity-based Inversion Method versus Strain-based Reconstructions. IEEE Journal of Selected Topics in Quantum Electronics, Volume 29, Number 4, pp. 1–16, 2022, doi: 10.1109/JSTQE.2022.3225108, Gold OA.
  • S. Hubmer, E. Sherina, S. Kindermann, K. Raik. A numerical comparison of some heuristic stopping rules for nonlinear Landweber iteration. Electronic Transactions on Numerical Analysis, Volume 57, pp. 216–241, 2022, doi: 10.1553/etna_vol57s216, Gold OA.
  • R. Wagner, D. Saxenhuber, R. Ramlau, S. Hubmer. Direction dependent Point Spread Functgion Reconstruction for Multi-Conjugate Adaptive Optics on Giant Segmented Mirror Telescopes. Astronomy and Computing, Volume 40, pp. 100590, 2022, doi: 10.1016/j.ascom.2022.100590, Green OA.
  • S. Hubmer, R. Ramlau, L. Weissinger. On Regularization via Frame Decompositions with Applications in Tomography, Inverse Problems, Volume 38, Number 5, pp. 055003, 2022, doi: 10.1088/1361-6420/ac5b86, Green OA.
  • F. Hinterer, M. C. Schneider, S. Hubmer, M. Lopez-Martinez, P. Zegler, A. Jesacher, R. Ramlau, G. Schütz. Robust and bias-free localization of individual fixed dipole emitters achieving the Cramér Rao bound. PLOS ONE, Volume 17, Number 2, pp. 1–15, 2022, doi: 10.1371/journal.pone.0263500, Green OA.
  • S. Hubmer, A. Ploier, R. Ramlau, P. Fosodeder, S. van Frank. A mathematical approach towards THz tomography for non-destructive imaging. Inverse Problems and Imaging, Volume 16, Number 1, pp. 68–88, 2022, doi: 10.3934/ipi.2021041, Green OA.
  • E. Sherina, L. Krainz, S. Hubmer, W. Drexler, O. Scherzer. Challenges for Optical Flow Estimates in Elastography. In: Eighth International Conference on Scale Space and Variational Methods in Computer Vision, Springer International Publishing, pp. 128–139, 2021, doi: 10.1007/978-3-030-75549-2_11, Green OA.
  • P. Fosodeder, S. Hubmer, A. Ploier, R. Ramlau, S. VanFrank, C. Rankl. Phase-contrast THz-CT for non-destructive testing. Optics Express, Volume X29, Number 10, pp. 15711–15723, 2021, doi: 10.1364/OE.422961, Hybrid OA.
  • S. Hubmer, and R. Ramlau. Frame Decompositions of Bounded Linear Operators in Hilbert Spaces with Applications in Tomography. Inverse Problems, Volume 37, Number 5, pp. 055001, 2021, doi: 10.1088/1361-6420/abe5b8, Hybrid OA.
  • E. Sherina, L. Krainz, S. Hubmer, W. Drexler, and O. Scherzer. Displacement field estimation from OCT images utilizing speckle information with applications in quantitative elastography. Inverse Problems, Volume 36, Number 12, pp. 124003, 2020, doi: 10.1088/1361-6420/abaf65, Hybrid OA.
  • S. Hubmer, and R. Ramlau. A Frame Decomposition of the Atmospheric Tomography Operator. Inverse Problems, Volume 36, Number 9, pp. 094001, 2020, doi 10.1088/1361-6420/aba4fe, Hybrid OA.
  • F. Hinterer, S. Hubmer, and R. Ramlau. A note on the minimization of a Tikhonov functional with ℓ1-penalty. Inverse Problems, Volume 36, Number 7, pp. 074001, 2020, doi: 10.1088/1361-6420/ab89c2, Hybrid OA.
  • S. Hubmer, A. Neubauer, R. Ramlau, and H. U. Voss. A conjugate-gradient approach to the parameter estimation problem of magnetic resonance advection imaging. Inverse Problems in Science & Engineering, Volume 28, Number 8, pp. 1154–1165, 2020, doi: 10.1080/17415977.2019.1708911, Green OA.
  • S. Hubmer, K. Knudsen, C. Li, and E. Sherina. Limited-angle acoustoelectrical tomography. Inverse Problems in Science & Engineering, Volume 27, Number 9, pp. 1298–1317, 2019, doi: 10.1080/17415977.2018.1512983, Hybrid OA.
  • S. Hubmer and R. Ramlau. Nesterov’s accelerated gradient method for nonlinear ill-posed problems with a locally convex residual functional. Inverse Problems, Volume 34, Number 9, 2018, doi: 10.1088/1361-6420/aacebe, Hybrid OA.
  • S. Hubmer, E. Sherina, A. Neubauer, and O. Scherzer. Lamé parameter estimation from static displacement field measurements in the framework of nonlinear inverse problems. SIAM Journal on Imaging Sciences, Volume 11, Number 2, pp. 1268–1293, 2018, doi: 10.1137/17M1154461, Green OA.
  • S. Hubmer, A. Neubauer, R. Ramlau, and H. U. Voss. On the parameter estimation problem of magnetic resonance advection imaging. Inverse Problems and Imaging, Volume 12, Number 1, pp. 175–204, 2018, doi: 10.3934/ipi.2018007, Green OA.
  • S. Hubmer and R. Ramlau, Convergence analysis of a two-point gradient method for nonlinear ill-posed problems. Inverse Problems, Volume 33, Number 9, 2017, doi: 10.1088/1361-6420/aa7ac7, Green OA. (Named as one of the highlights of 2017 of the journal).


Preprints and Technical Reports

  • H. Gfrerer, S. Hubmer, R. Ramlau. On SCD Semismooth* Newton methods for the efficient minimization of Tikhonov functionals with non-smooth and non-convex penalties, submitted, 2024, available from: https://arxiv.org/abs/2410.13730, opens an external URL in a new window
  • L. Weissinger, S. Hubmer, B. Stadler, R. Ramlau. Singular Value and Frame Decomposition-based Reconstruction for Atmospheric Tomography, submitted, 2024, available from: https://arxiv.org/abs/2405.01079, opens an external URL in a new window
  • W. Rannetbauer, C. Hambrock, S. Hubmer, R. Ramlau. Predicting interaction phenomena in HVOF thermal spraying of WC-CoCr: a hybrid experimentalstatistical approach, submitted, 2024
  • E. Sherina, L. Krainz, S. Hubmer, O. Scherzer, W. Drexler. Inversion Methods For Strain And Stiffness Reconstruction In Quantitative Optical Coherence Elastography, In: Tomographic Inverse Problems: Mathematical Challenges and Novel Applications, 2023, Eds.: S. Arridge, M. Burger, B. Hahn, E. T. Quinto, 2023, Mathematisches Forschungsinstitut Oberwolfach, doi: 10.4171/OWR/2023/21
  • F. Kagerer, M. Beinhofer, S. Hubmer, R. Ramlau. Myopic Approaches for a Real World Palletizing Problem, In: Proceedings of the Austrian Robotics Workshop 2021, Eds.: W. Kubinger, M. Brandstötter, C. Schöffmann, M. Vincze, June 2021, Vienna, ISBN 978-3-200-07799-7

  • Applied Numerical Mathematics.
  • Electronic Transactions on Numerical Analysis.
  • Inverse Problems (IOP trusted reviewer).
  • Journal of Complexity.
  • Journal of Computational and Applied Mathematics.
  • Journal of Inverse and Ill-Posed Problems.
  • Journal of Inverse Problems and Imaging.
  • Journal of Mathematical Imaging and Vision.
  • Mathematics.
  • Numerical Functional Analysis and Optimization.
  • Numerische Mathematik.
  • Radon Series on Computational and Applied Mathematics.

  • 03/2018 - 02/2026: SFB Tomography Across the Scales. Subproject: Tomography in Astronomy, funded by the FWF and headed by Prof. Otmar Scherzer and Prof. Ronny Ramlau. Project work and proposal/report writing.
  • 01/2022 - 12/2028: CD laboratory for mathematical modelling and simulation of nextgeneration medical ultrasound devices. External Module Aberration Corrections, funded by the Christian Doppler Forschungsgesellschaft in cooperation with GE Healthcare Austria GmbH & Co OG, and headed by Prof. Otmar Scherzer and Prof. Ronny Ramlau. Project work and support of proposal/report writing.
  • 2019 - 2020: Terahertz computer tomography for plastics extrusion (TACTICS). Mathematical project partner in cooperation with RECENDT GmbH, funded by ATTRACT (Horizon 2020) and headed by Prof. Ronny Ramlau. Project work.
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