Dr. Marcel Arpogaus studied Electrical Engineering and Information Technology at TH Nürnberg. He then moved to HTWG Konstanz for a Master's degree in Computer Science. Alongside his studies, he spent several years working in embedded and IoT development, most recently at Bosch.IO GmbH in Berlin. He wrote his Master's thesis there, supervised by Prof. Dr. Oliver Dürr, bringing both disciplines together for the first time.

He went on to complete a joint doctorate in Computer Science at the University of Göttingen and HTWG Konstanz. During his doctorate, he developed probabilistic deep learning methods for uncertainty quantification and control in resilient energy systems. The underlying question is how power grids can stay reliable when generation and consumption become ever harder to predict. This period also led to joint publications with Prof. Dr. Beate Sick.

Since 2026, Marcel has been a postdoctoral researcher at TIDIT in the Probabilistic AI Research Group (PAIR), working on probabilistic and causal modelling. He contributes his expertise and network in energy informatics to expand TIDIT's portfolio in this direction. For him, the transformation of the energy system remains the field in which reliable AI methods have to prove themselves.