Max Aehle


Chair for Scientific Computing
University of Kaiserslautern-Landau (RPTU)
Paul-Ehrlich-Straße 36, Room 415
67663 Kaiserslautern, Germany

Office:  36-415
Phone: +49 (0)631 205 5581
Email:   max.aehle@scicomp.uni-kl.de

Max Aehle

Research Interests


My current main focus is the machine code based automatic differentiation tool Derivgrind, which I have implemented using the dynamic binary instrumentation framework Valgrind. This novel approach allows to differentiate cross-language and partially closed-source computer programs with little development efforts. Specifically, I am motivated by the goal to provide derivatives of realistic Monte-Carlo particle simulators like Geant4 for the detector optimization undertaking of the MODE collaboration.

Besides, I develop proton computed tomography software for the Bergen pCT/SIVERT project and assist in teaching the scientific computing lecture. Previously, I have worked on the modelling of porous materials in the computational fluid dynamics suite SU2.

Talks


  • Quantification and Visualization of Uncertainties in CT Reconstruction (with Viktor Leonhardt), 7th Annual Loma Linda Workshop, 03.08.2021, virtual, website
  • How to use the Python/C API, SIVERT “Nice Tools” Colloquium, 20.09.2021, virtual
  • Debugging C++ Code with GDB and Valgrind, SIVERT “Nice Tools” Colloquium, 25.04.2022, virtual
  • Introduction to Tomographic RSP Reconstruction and Review of Existing Straight-Ray CT Codes and Architecture of a New Proton CT Code, Workshop “Recent Developments in Proton Computed Tomography”, 09.06.2022, Bergen, Norway
  • Design of a Modular CT Reconstruction Framework, 8th Annual Loma Linda Workshop, 18.07.2022, virtual, website
  • Towards Algorithmic Differentiation of GATE/Geant4, Second MODE Workshop on Differentiable Programming for Experiment Design, 13.09.2022, Colymbari, Greece, website
  • Forward-Mode Automatic Differentiation of Compiled Programs, Scientific Computing Seminar, 03.11.2022, Kaiserslautern, Germany, website

Publications


2022

M. Aehle, J. Blühdorn, M. Sagebaum, N.R. Gauger

Reverse-Mode Automatic Differentiation of Compiled Programs Miscellaneous

arXiv:2212.13760, 2022.

Links | BibTeX

M. Aehle, J. Blühdorn, M. Sagebaum, N. R. Gauger

Forward-Mode Automatic Differentiation of Compiled Programs Miscellaneous

arXiv:2209.01895, 2022.

Abstract | Links | BibTeX

T. Dorigo, A. Giammanco, P. Vischia, M. Aehle, M. Bawaj, A. Boldyrev, P. de Castro Manzano, D. Derkach, J. Donini, A. Edelen, F. Fanzago, N. R. Gauger, et al.

Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper Miscellaneous

arXiv:2203.13818, 2022.

Abstract | Links | BibTeX

M. Aehle, J. Alme, G. Barnaföldi, J. Blühdorn, T. Bodova, V. Borshchov, A. van den Brink, M. Chaar, V. Eikeland, G. Feofilov, C. Garth, N.R. Gauger, et al.

Derivatives in Proton CT Miscellaneous

arXiv: 2202.05551, 2022.

Abstract | Links | BibTeX

2021

H. Pettersen, M. Aehle, J. Alme, G. Barnaföldi, V. Borshchov, A. van den Brink, M. Chaar, V. Eikeland, G. Feofilov, C. Garth, N.R. Gauger, et al.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks Journal Article

In: Acta Oncologica, 1-6, 2021.

Links | BibTeX