
FH-Prof. Priv.-Doz. MMag. Dr.
Günther Eibl
Head of Research Group
Department Information Technologies and Digitalisation
Room: Urstein - 421
Teaching
ITS-B | 2. SS 2025 | Mathematics 2 | IL
ITSB-B | 2. SS 2025 | Mathematics 2 | IL
Focus
Teaching (50%)
- Mathematics
- Statistics
- Data Mining
Research (50%)
- Deputy head of the center for secure energy informatics
- Research interest: Privacy in the smart grid with 2 main parts
Privacy analyses
analyze the information that can be obtained from load profiles using primarily methods from machine learning, statisticsor whatever is useful
Privacy enhancing technologies
- Here, the focus in the past was on privacy-preserving data aggregation using homomorphic encryption, masking, differential privacy and wavelet analysis.
- Now the focus shifts to (i) tariffs and privacy-preserving price calculation and (ii) application of methods in order strictly proof privacy-preserving properties of proposed privacy-preserving protocols.
Publications:
- see https://scholar.google.de/citations?hl=de&user=n7TwAXcAAAAJ
- or http://www.en-trust.at/publications/
Education
- MSc in mathematics (numerics thesis)
- MSc in physics (plasma physics simulation thesis)
- PhD in machine learning (multiclass boosting thesis)