cv
Basics
| Name | Georg Schramm |
| Label | Asssitant Professor in Molecular Image Reconstruction and Analysis |
| Url | https://gschramm.github.io/ |
| Summary | Assistant Professor at KU Leuven who focusses on enhancing the diagnostic image quality of molecular images through advanced modeling of imaging systems, implementing cutting-edge reconstruction algorithms, and applying sustainable machine learning techniques. |
Work
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2023 - Present -
2022 - 2023 Instructor
Radiological Sciences Laboratory, Department of Radiology, Stanford University, CA, US
As an instructor in the lab of Prof. Fernando Boada, I worked on structure-guided reconstruction of sodium MR images incluing joint decay estimation.
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2015 - 2022 Postdoctoral Researcher
Department of Imaging and Pathology, Division, Nuclear Medicine, KU Leuven
As a PostDoc in the lab of Prof. Johan Nuyts, I investigated advanced method for iterative PET image reconstruction (e.g. structural priors) and the application of deep learning in PET reconstruction and image analysis.
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2011 - 2015 PhD Student
Institute for Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
As a PhD student in the lab of Prof. Jörg van den Hoff, I was evaluating and improving whole-body MR-based attenuation correction using one of the first combined PET/MR systems world-wide.
Education
Awards
- 2014
HZDR PhD Award
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Yearly award for the best PhD thesis at HZDR
- 2014
Award for notable achievements in nuclear medicine imaging
German society of Nuclear Medicine (DGN)
Yearly DGN award for the best young investigator in the field of nuclear medicine imaging
- 2011
Ehrenfried Walter von Tschirnhaus Urkunde
TU Dresden
Yearly award given to the five best graduates of the faculty of science at TU Dresden
Skills
| PET imaging | |
| image reconstruction | |
| ML-based PET imaging | |
| PET physics |
| Scientific computing | |
| python | |
| CUDA | |
| pytorch | |
| git | |
| cmake | |
| conda-forge |
| Applied Maths | |
| optimization | |
| inverse problems |
Languages
| German | |
| Native speaker |
| English | |
| Fluent |
| Dutch | |
| Fluent |
Interests
| Physics | |
| Nuclear physics | |
| PET physics |
| Imaging | |
| Medical imaging | |
| Imaging as an inverse problem | |
| ML-based methods for imaging | |
| Image-based dosimetry |
| Scientific computing | |
| high-performance optimization | |
| high-performance image reconstruction |
References
| Professor Johan Nuyts | |
| KU Leuven |
| Professor Fernando Boada | |
| Stanford University |
| Professor Jörg van den Hoff | |
| Helmholtz-Zentrum Dresden-Rossendorf |
| Professor Kris Thielemans | |
| University College London |