As a Ph.D. candidate at the University of Würzburg, my research focuses on creating social cognitive computing systems. I apply Machine Learning, Deep Learning, GraphML, and XAI methods to aid and enhance decision-making in different domains. Furthermore, I am eager to explore and understand the impact of algorithm-based decision-making on societal dynamics, businesses, and individual behaviors. My approach incorporates a blend of qualitative, quantitative, and computational research methodologies.

I have co-created and organized the local “Decision Support Systems and Machine Learning” reading group, as well as the Information Systems Engineering Group.

I have several years of Industry Experiance. After my master’s degree in 2014, and prior to my doctorade, I worked in the IT consultancy sector, specializing in advanced planning and optimization within Supply Chain Networks. This role allowed me to collaborate with multinational corporations, including BMW, Daimler, Osram, and Thyssen Krupp, delivering IT-Solutions, Algorithms, and Technical Concepts. After four years in industry, in 2019, I transitioned back into academia, commencing my doctoral studies at my alma mater. My research work at the University of Würzburg is inspired by the two research projects, that financed my work. In project “DeepScan” we focused on algorithm theory, computational complexity, and the explainability of machine learning algorithms, in the context of anomaly detection. In project “PipeAI” we worked on harnessing Explainable Artificial Intelligence (XAI) to predict and analyze industrial processes.