On March 13, 2025, Stefan Gaugel successfully defended his PhD thesis entitled 
 

Advancing Machine Learning Methods for Multivariate and Multiphase Time Series to Automate Test Cycle Optimization
 

at Ulm University, Germany. The DBIS team is pleased to congratulate Stefan on his successful PhD defense (Dr. rer. nat.) and wishes him all the best for his future career. 
Stefan Gaugel was supervised by Prof Manfred Reichert as part of his industrial doctoral project - the industrial partner was Bosch Rexroth AG. In his thesis he proposes a data-driven framework that leverages advanced machine learning to automate test cycle optimization in the context of industrial manufacturing, unlocking cost-saving potential. The goal was to enable faster, more cost-effective quality inspections while maintaining fault detection efficiency by identifying the minimum subset of essential test phases and sensors. The framework was validated using a real-world industrial data set, called Hydraulic Pump Testing (HyPT), which was collected by the candidate in a manufacturing plant. The main results of the cumulative dissertation have been published in high-calibre journals.
 

Members of the PhD committee
 

• Prof. Dr. Manfred Reichert (Ulm University, Supervisor & Referee)
• Prof. Dr. Rüdiger Pryss (University of Wurzbürg, External Referee)
• Prof. Dr. Hans Kestler (Ulm University, Committee Member)
• apl. Prof. Dr. Friedhelm Schwenker (Ulm University, Committee Member)
• Prof. Dr. Matthias Tichy (Ulm University, Chairman)