Alexander Schiendorfer is a research professor with 12 years’ experience applying AI, optimization, and machine learning to industrial manufacturing and energy systems. He leads the "AI-based optimization in Manufacturing for Mobility" group at Technische Hochschule Ingolstadt and drives funded research through AImotion Bavaria, focusing on practical AI engineering in cloud/edge environments. His work spans uncertainty-aware ML, transfer and federated learning, reinforcement learning, and decision-support systems built on constraint modeling (MiniZinc), bridging formal methods with industrial deployment. Previously he led AI methods groups and industrial projects at the University of Augsburg, mentoring multiple PhD students and translating research into manufacturing process improvements. Alexander’s background combines rigorous academic training (Dr. rer. nat., TUM/MSCA-affiliated programs) with hands-on software engineering experience from Siemens and industry, giving him a rare ability to move solutions from prototype to production. Colleagues describe him as a pragmatic researcher who prioritizes deployable models and robust ML systems in safety-critical manufacturing contexts.
12 years of coding experience
10 years of employment as a software developer
BSc, Software Engineering, BSc, Software Engineering at University of Applied Sciences Upper Austria
Master of Science - MS, Computer Software Engineering, Master of Science - MS, Computer Software Engineering at Technical University of Munich
Max-Weber-Programm, Max-Weber-Programm at Elite Network of Bavaria
BRG Schloss Traunsee
Dr. rer. nat., Computer Science, Dr. rer. nat., Computer Science at University of Augsburg
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Alexander Schiendorfer - Professor at Technische Hochschule Ingolstadt