On 22 June 2026, Alexander successfully defended his doctoral dissertation, "Towards Robust and Interpretable Machine Learning under Distributional Uncertainty."

During his time as a researcher at KIT (Karlsruhe Institute of Technology) and the FZI Forschungszentrum Informatik, Alexander seamlessly bridged academic rigor with real-world impact. His research addresses fundamental challenges in modern AI by developing methods that enhance model robustness and interpretability, ensuring reliable and trustworthy machine learning applications in industrial settings.

A special thank you to the examination committee consisting of Prof. Dr. Christof Weinhardt, Prof. Dr. York Sure-Vetter, Prof. Dr. Oliver Grothe, and Prof. Dr. Clemens Puppe for evaluating and supporting his work.

We warmly congratulate Dr. Alexander Grote on this outstanding milestone, thank him for his invaluable contributions, and wish him continued success in his future career!