Thomas Seidler

ORCID: 0000-0002-6870-5846
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About
Contact & Profiles
Research Areas
  • Distributed and Parallel Computing Systems
  • Scientific Computing and Data Management
  • Radiation Detection and Scintillator Technologies
  • Robotics and Automated Systems
  • Advanced Research in Systems and Signal Processing
  • Radiation Effects in Electronics
  • Solar Radiation and Photovoltaics
  • Particle Detector Development and Performance
  • Software System Performance and Reliability
  • Cloud Computing and Resource Management
  • Energy Load and Power Forecasting

University of Potsdam
2021-2024

Czech Academy of Sciences, Institute of Physics
2021

Czech Technical University in Prague
2018

Seidler et al., (2024). Mantik: A Workflow Platform for the Development of Artificial Intelligence on High-Performance Computing Infrastructures. Journal Open Source Software, 9(98), 6136, https://doi.org/10.21105/joss.06136

10.21105/joss.06136 article EN cc-by The Journal of Open Source Software 2024-06-02

10.5220/0012435000003636 article EN cc-by-nc-nd Proceedings of the 14th International Conference on Agents and Artificial Intelligence 2024-01-01

A network of Timepix (TPX) devices installed in the ATLAS cavern has unique capability measuring luminosity with thermal neutron counting Large Hadron Collider proton-proton collisions at 13 TeV. Compared hit-counting method, method advantage that it is not affected by induced radioactivity. The results determination are presented for several independently operated TPX detectors. long-term time stability measurements individual and between different devices. high-statistics data sets allow a...

10.1109/tns.2018.2839683 article EN cc-by IEEE Transactions on Nuclear Science 2018-05-22

<p>Earth system modeling is virtually impossible without dedicated data analysis. Typically, are big and due to the complexity of system, adequate tools for analysis lie in domain machine learning or artificial intelligence. However, earth specialists have other expertise than developing deploying state-of-the art programming code which needed efficiently use modern software frameworks computing resources. In addition, Cloud HPC infrastructure frequently run analyses with...

10.5194/egusphere-egu21-9632 article EN 2021-03-04

<p>Obtaining a quantitative measure for the uncertainty of forecasts renewable energy has proven to be challenging problem in past. We present results on predicting forecast conditioned large weather situation (Großwetterlage). As first attempt, we use objective classification by German Meteorological Service (DWD), which sorts into 40 situations based wind direction, cyclonality and moisture atmosphere.</p><p>The considered concern...

10.5194/egusphere-egu21-13132 article EN 2021-03-04
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