Dr. Charlotte Debus
- Junior Research Group Leader
-
charlotte debus ∂does-not-exist.kit edu
| since 2022 | Junior Research Group Leader | Steinbuch Centre for Computing (SCC), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany |
| 2020 - 2022 | Research Associate | Steinbuch Centre for Computing (SCC), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany |
| 2019 - 2020 | Research Associate | Institute of Software Technology, German Aerospace Center (DLR), Cologne, Germany |
| 2016 - 2019 | Research associate, project group leader | Department of Translational Radiooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany |
| 2013 - 2016 | PhD Physics | University of Heidelberg |
| 2013 | Trainee | European Synchrotron Radiation Facility (ESRF), Grenoble, France |
| 2010 - 2012 | Master of Science Physics | University of Heidelberg |
| 2011 | Semester abroad | Universidade de Lisboa, Portugal |
| 2007 - 2010 | Bachelor of Science Physics | University of Heidelberg |
List of publications KITopen
High-performance data analytics of hybrid rocket fuel combustion data using different machine learning approaches
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161
Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI
Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.
2017. Physics in Medicine & Biology, 62 (24), 9322–9340. doi:10.1088/1361-6560/aa8989
Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.
2017. Physics in Medicine & Biology, 62 (24), 9322–9340. doi:10.1088/1361-6560/aa8989
A point kernel algorithm for microbeam radiation therapy
Debus, C.; Oelfke, U.; Bartzsch, S.
2017. Physics in Medicine & Biology, 62 (21), 8341–8359. doi:10.1088/1361-6560/aa8d63
Debus, C.; Oelfke, U.; Bartzsch, S.
2017. Physics in Medicine & Biology, 62 (21), 8341–8359. doi:10.1088/1361-6560/aa8d63
Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation
Debus, C.; Afshar-Oromieh, A.; Floca, R.; Ingrisch, M.; Knoll, M.; Debus, J.; Haberkorn, U.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 14760. doi:10.1038/s41598-018-33034-5
Debus, C.; Afshar-Oromieh, A.; Floca, R.; Ingrisch, M.; Knoll, M.; Debus, J.; Haberkorn, U.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 14760. doi:10.1038/s41598-018-33034-5
Impact of 18F-FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon-Ion Radiotherapy
Debus, C.; Waltenberger, M.; Floca, R.; Afshar-Oromieh, A.; Bougatf, N.; Adeberg, S.; Heiland, S.; Bendszus, M.; Wick, W.; Rieken, S.; Haberkorn, U.; Debus, J.; Knoll, M.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 7201. doi:10.1038/s41598-018-25350-7
Debus, C.; Waltenberger, M.; Floca, R.; Afshar-Oromieh, A.; Bougatf, N.; Adeberg, S.; Heiland, S.; Bendszus, M.; Wick, W.; Rieken, S.; Haberkorn, U.; Debus, J.; Knoll, M.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 7201. doi:10.1038/s41598-018-25350-7
MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging–design, implementation and application on the example of DCE-MRI
Debus, C.; Floca, R.; Ingrisch, M.; Kompan, I.; Maier-Hein, K.; Abdollahi, A.; Nolden, M.
2019. BMC bioinformatics, 20 (1), Artkl.Nr.: 31. doi:10.1186/s12859-018-2588-1
Debus, C.; Floca, R.; Ingrisch, M.; Kompan, I.; Maier-Hein, K.; Abdollahi, A.; Nolden, M.
2019. BMC bioinformatics, 20 (1), Artkl.Nr.: 31. doi:10.1186/s12859-018-2588-1
Accelerating neural network training with distributed asynchronous and selective optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2022. Journal of Big Data, 9 (1), 14. doi:10.1186/s40537-021-00556-1
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2022. Journal of Big Data, 9 (1), 14. doi:10.1186/s40537-021-00556-1
Heat - A Distributed and Accelerated Tensor Framework for Data Analytics and Machine Learning
Comito, C.; Götz, M.; Debus, C.; Coquelin, D.; Tarnawa, M.; Krajsek, K.; Knechtges, P.; Siggel, M.; Hagemeier, B.; Basermann, A.; Streit, A.
2021, October 5. 1st Artificial Intelligence Symposium on Theory, Application & Research (AI STAR 2021), Online, October 5–6, 2021
Comito, C.; Götz, M.; Debus, C.; Coquelin, D.; Tarnawa, M.; Krajsek, K.; Knechtges, P.; Siggel, M.; Hagemeier, B.; Basermann, A.; Streit, A.
2021, October 5. 1st Artificial Intelligence Symposium on Theory, Application & Research (AI STAR 2021), Online, October 5–6, 2021
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
HeAT - A Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050
HeAT – a Distributed and GPU-accelerated TensorFramework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)
HeAT – a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
Courses
| Title | Type | Semester |
|---|---|---|
| Scalable Methods of Artificial Intelligence | Lecture with tutorial (VÜ) | WS 22/23 |
| Scalable Methods of Artificial Intelligence | Lecture with tutorial (VÜ) | WS 21/22 |
Theses
The RAI group offers a number of bachelor and master thesis projects in the topics of scalable and efficient artificial intelligence, quantification of uncertainties, and AI applications in energy informatics. Interested students are welcome to contact us via email.