PhD candidate in the SIVERT project
Chair for Scientific Computing
University of Kaiserslautern-Landau (RPTU)
Bldg/Geb 36, Paul-Ehrlich-Strasse
67663 Kaiserslautern, Germany
Office: 36-409
Phone: +49 (0)631 205 5636
Email: tobias.kortus@rptu.de
Research Interests
- Machine Learning
- Reinforcement Learning
- Medical Physics (Proton computed tomography)
- Charged particle tracking
Talks
- Tracking of Proton Traces in a Digital Tracking Calorimeter using Reinforcement Learning, 13.05.2022 CERN, Geneva, Swizerland, website
- Towards Neural Charged Particle Tracking in Proton Computed Tomography with Reinforcement
Learning, 13.09.2022, Colymbari, Greece, website - Reinforcement Learning Algorithms for Charged Particle Tracking with Applications in Proton Computed Tomography, 30.01.2024 CERN, Geneva, Swizerland, website
- Exploring End-to-end Differentiable Neural Charged Particle Tracking – A Loss Landscape Perspective, 10.9.2024, Darmstadt, Germany, website
- Exploring End-to-end Differentiable Neural Charged Particle Tracking – A Loss Landscape Perspective, 23.09.2024, Valencia, Spain, website
Publications
2024
Exploring End-to-end Differentiable Neural Charged Particle Tracking – A Loss Landscape Perspective Miscellaneous
arXiv:2407.13420 [physics.comp-ph], 2024.
2023
Towards Neural Charged Particle Tracking in Digital Tracking Calorimeters With Reinforcement Learning Journal Article
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 12, pp. 15820-15833, 2023.
Exploration of Differentiability in a Proton Computed Tomography Simulation Framework Journal Article
In: Physics in Medicine and Biology, vol. 68, no. 24, pp. 244002, 2023.
Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter Journal Article
In: Phys. Med. Biol., vol. 68, no. 194001, 2023.
The Bergen proton CT system Journal Article
In: Journal of Instrumentation, vol. 18, no. 2, 2023.
2021
Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks Journal Article
In: Acta Oncologica, 1-6, 2021.