Andreas Koch

E-Mail:	[email protected]
Phone:
Room:	9377.01.109
Address:	Airbus Defence and Space GmbH Andreas Koch Abteilung Telecom Processing Germany (TSTCG-TL2) Willy-Messerschmitt-Straße 9 82024 Taufkirchen

Research Interests

• Deep Learning
• Anomaly Detection in Satellite Telemetry
• Satellite Payload Data Processing
• AI hardware acceleration

Projects

• Machine Learning for Telecommunication Satellites (MaLeTeSa): This Airbus Defence and Space project aims to develop a custom machine learning module for satellite communication processors and is funded by Deutsches Zentrum für Luft- und Raumfahrt (DLR). To this end, various ML approaches are researched and applications include anomaly detection in telemetry data, identification of different users of the radio frequency spectrum and optimization of communication networks.

Publications

1. Petry, M., Koch, A., & Werner, M. (2024). Zero-Copy AI-augmented Signal Processing Pipeline on Heterogeneous Satellite Processors. Asilomar Conference on Signals, Systems, and Computers 2024. [PDF]
2. Petry, M., Parlier, B., Koch, A., & Werner, M. (2024). Auto-Regressive RF Synchronization Using Deep-Learning. IEEE International Conference on Machine Learning for Communication and Networking. [PDF]
3. Kiprit, G. N., Koch, A., Petry, M., & Werner, M. (2024). Graph Neural Networks for Anomaly Detection in Spacecraft. Proceedings of the First Joint European Space Agency SPAICE Conference / IAA Conference on AI in and for Space. [PDF]
4. Koch, A., Petry, M., & Werner, M. (2024). AI-augmented Anomaly Detection Pipeline for Real-Time Onboard Processing of Spacecraft Telemetry. Proceedings of the First Joint European Space Agency SPAICE Conference / IAA Conference on AI in and for Space. [PDF]
5. Koch, A., Petry, M., & Werner, M. (2024). Extended Framework and Evaluation for Multivariate Streaming Anomaly Detection with Machine Learning. Proceedings of MulTiSA 2024, the 1st Workshop on Multivariate Time Series Analytics in Conjunction with ICDE 24, 1–8. [PDF]
6. Petry, M., Koch, A., & Werner, M. (2023). Envisioning Physical Layer Flexibility Through the Power of Machine-Learning. 2023 IEEE Globecom Workshops (GC Wkshps), 50–55. https://doi.org/10.1109/GCWkshps58843.2023.10464871 [PDF]
7. Petry, M., Wuwer, G., Koch, A., Gest, P., Ghiglione, M., & Werner, M. (2023). Accelerated Deep-Learning Inference on the Versal adaptive SoC in the Space Domain. 2023 European Data Handling & Data Processing Conference (EDHPC), 1–8. https://doi.org/10.23919/EDHPC59100.2023.10396011 [Online]
8. Koch, A., Krstova, A., Hegwein, F., De Lera, M. C., Ales, F., Petry, M., Ali, R., Mallah, M., Hili, L., Ghiglione, M., & Werner, M. (2023). On-Board Anomaly Detection on a Flight-Ready System. 2023 European Data Handling & Data Processing Conference (EDHPC), 1–4. https://doi.org/10.23919/EDHPC59100.2023.10395967 [PDF] [Online]
9. Koch, A., Dax, G., Petry, M., Gomez, H., Raoofy, A., Saroliya, U., Ghiglione, M., Furano, G., Werner, M., Trinitis, C., & Langer, M. (2023). Reference Implementations for Machine Learning Application Benchmark. 2023 European Data Handling & Data Processing Conference (EDHPC), 1–3. https://doi.org/10.23919/EDHPC59100.2023.10396582 [PDF] [Online]
10. Koch, A., Petry, M., Ghiglione, M., Raoofy, A., Dax, G., Furano, G., Werner, M., Trinitis, C., & Langer, M. (2023). Machine Learning Application Benchmark. 20th ACM International Conference on Computing Frontiers (CF ’23), May, 2023, Bologna, Italy. https://doi.org/10.1145/3587135.3592769 [PDF]
11. Petry, M., Gest, P., Koch, A., Ghiglione, M., & Werner, M. (2023). Accelerated Deep-Learning inference on FPGAs in the Space Domain. 20th ACM International Conference on Computing Frontiers (CF ’23), May, 2023, Bologna, Italy. https://doi.org/10.1145/3587135.3592763 [PDF]
12. Petry, M., Koch, A., Werner, M., Hoch, U., Helfers, T., & Wiest, R. (2023). Machine Learning on Telecommunication Satellite. DATA SYSTEMS IN AEROSPACE - 2023 DASIA. [PDF]
13. Zhu, X. X., Wang, Y., Kochupillai, M., Werner, M., Häberle, M., Hoffmann, E. J., Taubenböck, H., Tuia, D., Levering, A., Jacobs, N., & others. (2022). Geoinformation harvesting from social media data: A community remote sensing approach. IEEE Geoscience and Remote Sensing Magazine, 10(4), 150–180. [PDF]

Other Publications

1. Hagerer, G., Szabo, D., Koch, A., Dominguez, M. L. R., Widmer, C., Wich, M., Danner, H., & Groh, G. (2021). End-to-End Annotator Bias Approximation on Crowdsourced Single-Label Sentiment Analysis. In M. Abbas & A. A. Freihat (Eds.), Proceedings of the 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021) (pp. 1–10). Association for Computational Linguistics. https://aclanthology.org/2021.icnlsp-1.1 [Online]