Prof. Dr. Felix Naumann

Phillip Wenig

Ph.D. student at the Infomation Systems Research Group at Hasso Plattner Institute for Software Systems Engineering

Contact Information

für Softwaresystemtechnik
Prof.-Dr.-Helmert-Straße 2-3
D-14482 Potsdam

Phone: +49 331 5509 237
Fax: +49 331 5509 237
Room: F-2.04
Email: Phillip.Wenig

Research Interests

  • Distributed Computing
  • Machine Learning
  • Time Series Analysis


Time Series Anomaly Detection

  • DADS (Distributed Detection of Sequential Anomalies in Univariate Time Series)

Distributed Machine Learning


Summer semester 2020

Winter semester 2020 / 2021

Summer semester 2021

Winter semester 2021 / 2022

  • Large-Scale Time Series Analytics (PS, Master)

Winter semester 2022 / 2023

Published Software

  • Actix Telepathy (Rust extension for Actix to allow remote actors)
  • DataGossip (PyTorch extension for asynchronous distributed data parallel machine learning)


  • 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 (to appear)
  • 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]
  • Sebastian Schmidl, Phillip Wenig, Thorsten Papenbrock: Anomaly Detection in Time Series: A Comprehensive Evaluation. PVLDB 9:(15), 2022
    [Paper]  [Poster]  [Project Page]  [DOI:10.14778/3538598.3538602]
  • Phillip Wenig, Thorsten Papenbrock: DataGossip: A Data Exchange Extension for Distributed Machine Learning Algorithms. Proceedings of the International Conference on Extending Database Technology (EDBT), 2022
    [Paper]  [GitHub]  [DOI:10.48786/edbt.2022.24]
  • Johannes Schneider, Phillip Wenig, Thorsten Papenbrock: Distributed detection of sequential anomalies in univariate time series. The VLDB Journal (2021)
    [Paper]  [Poster]  [Project Page]  [DOI:10.1007/s00778-021-00657-6]