AISE-M | 1. WS 2025 | Analytics and Knowledge Discovery | IL
AITB-M | 1. WS 2025 | Analytics & Knowledge Discovery | IL
CYSB-M | 3. WS 2025 | Privacy-Enhancing Technologies | IL
ITS-B | 1. WS 2025 | Mathematics 1 | IL
ITSB-B | 1. WS 2025 | Mathematics 1 | IL

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)

• FTZ CyberSec: Cybersecurity – FTZ for Data-Based Evaluation of Security and Privacy Technologies
  The objective of the project is to ensure an open and comprehensive transfer of knowledge in the fields of AI security and data protection for... 07/2025 - 12/2028
• DAWN: Data-driven Analysis and Optimization of Low Voltage Networks
  The increased use of renewable energy sources and the shift towards electromobility are leading to greater volatility in the energy system. Grid... 01/2025 - 12/2026
• PRISMATICS: Privacy and Security for Modelling and Assessing Threats to Industrial Complex Systems
  Im Kontext von modernen Industrieanwendungen (Industrie 4.0) erfolgt eine verstärkte Digitalisierung des Produktionsprozesses. Dabei werden räumlich... 05/2021 - 04/2026

• Evaluating the Efficacy of LINDDUN GO for Privacy Threat Modeling for Local Renewable Energy Communities
  While security is considered an essential aspect of the design and implementation of many systems, privacy is often overlooked, especially in early planning phases. Although methodologies for the...
  2025
• Inferring the Hidden: Privacy Risks of Microaggregation in Smart Meter Data
  2025
• Predicting Socio-Demographic Characteristics from Load Profiles with Varying Time Granularities
  Energy consumption data from smart meters has been shown to infer socio-demographic characteristics, which impacts privacy. However, the impact of time granularity on the ability to classify such...
  2025

• Elf EU-Millionen für Forschungszentrum
  
• Wenn das Stromnetz schlauer werden muss
  

• Best Paper Award DACH+ Conference on Energy Informatics
  30. Oct 2020