Michael Stenger

Michael Stenger is a Researcher at the Chair of Software Engineering (Informatik II) under the Department of Computer Science at the University of Würzburg. His current role since May 2023 involves research in synthetic data generation, time series analysis, and machine learning. He coordinates the lecture 'Softwaretechnik' and supervises bachelor/master theses and seminar topics in software engineering.

Education:

• Master of Computer Science (2020-2023), University of Würzburg
• Bachelor of Computer Science (2017-2020), University of Würzburg
• Study Abroad: University of Saskatchewan, Canada (2021)

Research Interests: Focuses on synthetic data generation, time series analysis, and machine learning applications. His work emphasizes evaluation methodologies for synthetic data quality and hybrid forecasting approaches. He also contributes to data science and deep learning techniques for real-world problem-solving.

Publications & Conferences: Active contributor to venues like MASCOTS, ICPE, and VLDB. Recent work explores synthetic time series evaluation (STEB, 2025) and lightweight temporal feature encoding (TSRM, 2025). Trends show a strong emphasis on automated systems, benchmarking, and cross-domain applicability.

Supervision & Grants: Supervises student projects in software engineering and data science. Engaged in interdisciplinary collaborations through his roles in multiple academic chairs.

Labs/Teams: Part of the Software Engineering Group and Secure Software Systems Group at the University of Würzburg.