Knowledge Discovery in Simulation Data
Machine learning, explainable AI, and visual analytics for automated simulation-data analysis.
My doctoral research investigated how the process of knowledge discovery in simulation data can be automated and made accessible to users with different levels of data-science expertise.
The work covered intelligent experiment design, meta-learning, machine learning, explainable AI, visual analytics, and rule-based recommendations for data visualization. Methods were implemented in prototypes and in the modular SimAssist environment, including a Python interface for integrating machine-learning workflows.
The dissertation was completed at the Technical University of Ilmenau in December 2025 with magna cum laude.