Julian Oelhaf

Julian Oelhaf, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.157
Martensstr. 3
91058 Erlangen

Research Project: Developing advanced machine learning techniques to enhance coordinated protection strategies in power systems, ensuring reliability and resilience under fault conditions.

Research Areas: Electricity Grid Management, Fault Detection and Diagnosis, Time Series Data Analysis, and Reinforcement Learning for Decision-Making in Power Systems.

Academic CV

  • Since 2024:
    PhD Student at the Pattern Recognition Lab, FAU Erlangen-Nürnberg
  • 2021 – 2024
    Master’s degree in Computer Science, FAU Erlangen-Nürnberg
  • 2017 – 2020
    Bachelor’s degree in Aerospace Computer Science, JMU Würzburg

Projects

2024

  • Coordinated grid protection based on machine learning methods

    (Third Party Funds Single)

    Term: July 1, 2024 - June 30, 2027
    Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)

Publications

2025

Conference Contributions

Bachelor/Master Thesis

Type Title Status
MA thesis Advanced Machine Learning-Based High Demand Forecasting of Household Energy Consumption for Enhancing Grid Operations running
MA thesis Deep Learning-Based Fault Detection and Classification in Power System Protection: A Comparative Study running
MA thesis Wind Power Forecasting through Probabilistic Machine Learning Models running