Kevin Styp-Rekowski | Research assistant @ TU Berlin

I am a research associate and PhD student at the HEIBRiDS (Helmholtz Einstein International Berlin Research School in Data Science) program and working in the interdisciplinary "Multi-satellite Approach of Monitoring Atomsphere/Magnetosphere Space Weather Interactions" project. Thus, I am associated with the TU Berlin in the distributed systems group of Odej Kao and with the GFZ Potsdam in the geomagnetism section of Claudia Stolle. We investigate the use of non-dedicated satellites to improve the data availabilty for geomagnetic observations of the earth's magnetic field in space. By making more data accessible, the enlargened coverage of the earth's surface can deepen the knowledge about the earth's interior. For the publication of our datasets, also visit our dedicated publication website.
Organizations worked for: Servermeile, KSB

GitHub: Github-Link
ResearchGate: ResearchGate-Link
Mail: styp-rekowski at tu-berlin.de

Kevin Styp-Rekowski

Peer-reviewed Publications (journal or conference)

2022:
  • I. Michaelis, K. Styp-Rekowski, J. Rauberg, C. Stolle, and M. Korte (2022). Geomagnetic data from the GOCE satellite mission. Earth, Planets, and Space. [Preprint] https://doi.org/10.1002/essoar.10511006.1
  • K. Styp-Rekowski, I. Michaelis, C. Stolle, J. Baerenzung, M. Korte, and O. Kao (2022). Machine Learning-based Calibration of the GOCE Satellite Platform Magnetometers. Earth, Planets, and Space. [Preprint] https://doi.org/10.21203/rs.3.rs-1607576/v1
2021:
  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao (2021). Calibration of the GRACE-FO Satellite Platform Magnetometers and Co-estimation of Intrinsic Time Shift in Data 2021 IEEE International Conference on Big Data, 5283-5290. https://doi.org/10.1109/BigData52589.2021.9671977
  • C. Stolle, I. Michaelis, C. Xiong, M. Rother, T. Usbeck, Y. Yamazaki, J. Rauberg, and K. Styp-Rekowski (2021). Observing Earth’s magnetic environment with the GRACE-FO mission Earth, Planets and Space, 73, 51. https://doi.org/10.1186/s40623-021-01364-w
2020:
  • S. Ahmad, K. Styp-Rekowski, S. Nedelkoski, and O. Kao. Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines In 2020 IEEE International Conference on Big Data, 4093-4102.
  • K. Styp-Rekowski, F. Schmidt, and O. Kao. Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series In 2020 IEEE International Conference on Big Data, 2217-2222.
2019:
  • D. T. Schroeder, K. Styp-Rekowski, F. Schmidt, A. Acker, and O. Kao. Graph-based Feature Selection Filter Utilizing Maximal Cliques In 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS). IEEE.
  • A. Lommatzsch, B. Kille, K. Styp-Rekowski, M. Karl, J. Pommering. A Framework for Analyzing News Images and Building Multimedia-Based Recommender In International Conference on Innovations for Community Services. Springer, Cham.

Presentations at Conferences

2022:
  • K. Styp-Rekowski, I. Michaelis, C. Stolle, and O. Kao. Magnetic Datasets from Non-dedicated Satellites. (Oral Presentation), Living Planet Symposium, Bonn, Germany, 23-27 May 2022.
2021:
  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Calibration of the GRACE-FO Satellite Platform Magnetometers and Co-Estimation of Intrinsic Time Shift in Data. (Oral Presentation), IEEE Big Data 2021, Online, 15-18 December 2021.
  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Calibration of GRACE-FO and GOCE Platform Magnetometers Using Machine Learning. (Oral Presentation), Swarm Data Quality Workshop, Athens, Greece, 11-16 October 2021.
  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Machine Learning-based Information Extraction from Non-dedicated Sensors. (Oral Presentation), Photonics Days Berlin Brandenburg, Berlin, Germany, 4-7 October 2021.
  • K. Styp-Rekowski, C. Stolle, O. Kao, and I. Michaelis. Satellite Platform Magnetometer Calibration Using Machine Learning. (Oral Presentation), Joint Scientific Assembly IAGA-IASPEI, Online, 21-27 August 2021.
  • K. Styp-Rekowski, C. Stolle, O. Kao, and I. Michaelis. Automatic Calibration of Satellite Platform Magnetometers with Neural Network-based Time Shift Approximation. (Oral Presentation), Joint Scientific Assembly IAGA-IASPEI, Online, 21-27 August 2021.
2020:
  • S. Ahmad, K. Styp-Rekowski, S. Nedelkoski, and O. Kao. Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines (Oral Presentation), IEEE Big Data 2020, Online, 10-13 December 2020.
  • K. Styp-Rekowski, F. Schmidt, and O. Kao. Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series (Oral Presentation), IEEE Big Data 2020, Online, 10-13 December 2020.
2019:
  • D. T. Schroeder, K. Styp-Rekowski, F. Schmidt, A. Acker, and O. Kao. Graph-based Feature Selection Filter Utilizing Maximal Cliques (Oral Presentation), Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS), Granada, Spain, 22-25 October 2019.
    • In 2019 . IEEE.

Supervised Theses

Completed:
  • Implementierung eines WEKA-Plugins am Beispiel einer graphen-basierten Feature Selection mit maximalen Cliquen - Trieu Minh Bui
  • Application of Neural Networks in Unsupervised Anomaly Detection from Time and Frequency Data of Rotating Machines - Sabtain Ahmad

Theses

  • Streaming-based Regions of Interest Extraction for Contrast-Enhanced Ultrasound Videos. Kevin Styp-Rekowski. Master thesis submitted at TU Berlin in December 2018.
  • Generation of Adaptations Using Genetic Algorithms (Generierung von Adaptationen mithilfe von Genetischen Algorithmen). Kevin Styp-Rekowski. Bachelor thesis submitted at TU Berlin in June 2016.

© Kevin Styp-Rekowski | Last Update: 04 Jul 2022