Our group includes PostDocs, PhD students, and student assistants, and is headed by Prof. Felix Naumann. If you are interested in joining our team, please contact Felix Naumann.
For bachelor students we offer German lectures on database systems in addition to paper- or project-oriented seminars. Within a one-year bachelor project, students finalize their studies in cooperation with external partners. For master students we offer courses on information integration, data profiling, and information retrieval enhanced by specialized seminars, master projects and we advise master theses.
Most of our research is conducted in the context of larger research projects, in collaboration across students, across groups, and across universities. We strive to make available most of our datasets and source code.
Ph.D. student at the chair for Infomation Systems at Hasso Plattner Institute for Digital Engineering. I am in the distributed computing research group, where we investigate computationally complex problems and how they can be solved in distributed environments.
Contact Information
Hasso-Plattner-Institut für Digital Engineering gGmbH Prof.-Dr.-Helmert-Str. 2-3 D-14482 Potsdam
Large-Scale Time Series Analytics (Master, 2021/2022)
Sustainable Machine Learning on Edge Device Clusters (Master, 2020, assistance)
Lectures:
Guest Lecture about Order Dependencies for the Data Profiling course (2023)
Guest Lecture about distributed discovery of Order Dependencies for the Data Profiling course (2020/2021)
Master Thesis (supervision):
DPQLEngine: Processing the Data Profiling Query Language (Marcian Seeger UMR, 2023, supervision assistance)
Correlation Anomaly Detection in High-Dimensional Time Series (Niklas Köhnecke, 2023)
HYPEX: Explainable Hyperparameter Optimization in Time Series Anomaly Detection (Mats Pörschke, 2022)
Time Series Anomaly Detection: An Aircraft Turbine Case Study (Jacopo Roberto Nicosia, 2022)
A2DB: A Reactive Database for Theta-Joins (Julian Weise, 2020, supervision assistance)
Publications
Anthony Bagnall, Matthew Middlehurst, Germain Forestier, Ali Ismail-Fawaz, Antoine Guillaume, David Guijo-Rubio, Arik Ermshaus, Patrick Schäfer, Thorsten Papenbrock, Phillip Wenig, Sebastian Schmidl: An Introduction to Machine Learning from Time Series. Proceedings of the European Conference on Machine Learning and Data Mining (ECML PKDD), 2024 (to appear)
Phillip Wenig, Sebastian Schmidl, Thorsten Papenbrock: Anomaly Detectors for Multivariate Time Series: The Proof of the Pudding is in the Eating. Proceedings of the Workshop on Multivariate Time Series Analytics (MulTiSA), 2024 (to appear) [Paper]
Marcian Seeger, Sebastian Schmidl, Alexander Vielhauer, Thorsten Papenbrock: DPQL: The Data Profiling Query Language. Proceedings of the conference on Database Systems for Business, Technology, and Web (BTW), 2023 [Paper][DOI:10.18420/BTW2023-19]
Sebastian Schmidl, Phillip Wenig, Thorsten Papenbrock: HYPEX: Hyperparameter Optimization in Time Series Anomaly Detection. Proceedings of the conference on Database Systems for Business, Technology, and Web (BTW), 2023 [Paper][Project Page][DOI:10.18420/BTW2023-22]
Phillip Wenig, Sebastian Schmidl, Thorsten Papenbrock: TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms. PVLDB 12:(15), 2022 [Paper][Project Page][DOI:10.14778/3554821.3554873]
Julian Weise, Sebastian Schmidl, Thorsten Papenbrock: Optimized Theta-Join Processing. Proceedings of the Conference on Database Systems for Business, Technology, and Web (BTW), 2021 [Paper][Project Page][DOI:10.18420/btw2021-03]
Sebastian Schmidl, Frederic Schneider, Thorsten Papenbrock: An Actor Database System for Akka. Proceedings of the conference on Database Systems for Business, Technology, and Web (BTW) - Workshopband, 2019 [Paper][DOI:10.18420/btw2019-ws-23]
