Sebastian Strasser

I am a PhD student in Meike Klettke's group for Data Engineering. My research focuses on the monitoring of data pipelines, especially considering the effect data changes have on downstream applications.

Research Interests

• Data-centric AI
• Monitoring of data in ML pipelines
• Concept drift detection

Publications

• Sebastian Strasser, Meike Klettke: Transparent Data Preprocessing for Machine Learning, HILDA@SIGMOD, 2024 (DOI)

• Sebastian Strasser: Towards machine learning-aware data validation. GvDB, 2024 (PDF)

• Mark Lukas Möller, Dominique Hausler, Sebastian Strasser, Tanja Auge, Meike Klettke: Heterogeneity in NoSQL Databases - Challenges of Handling schema-less Data. LWDA, 2023 (PDF)

• Lucas Woltmann, Peter Benjamin Volk, Michael Dinzinger, Lukas Gräf,
  Sebastian Strasser, Johannes Schildgen, Claudio Hartmann, Wolfgang Lehner: Data Science Meets High-Tech Manufacturing - The BTW2021 Data Science Challenge. Datenbank Spektrum 22(1), 2022 (DOI)

Thesis

• Sebastian Strasser:
  Finding Potential Synthetic Cannabinoids in Forensic Drug Analysis Data.
  Master Thesis, University of Applied Sciences Regensburg, 2023 (pdf)