Martin Trat studied industrial engineering at the University of Bayreuth, initially specializing in automotive/cybernetics. In his subsequent master's degree, he deepened his knowledge of the disciplines machine learning and vision at the Karlsruhe Institute of Technology. In the course of this, he went on a research stay at Bosch Rexroth in the Chicago metropolitan area, where he dealt with scrap prediction for highly automated machines based on artificial intelligence.

After completing his studies, he became research scientist in the FZI department Intelligent Systems and Production Engineering. Within this context, he deals with the long-term robustness of artificial intelligence (AI). Under the slogan “I think my AI is broken”, he tackles the problems that sooner or later happen exactly where it hurts: in the productive environment of industrial companies. Due to frequent changes in real-life circumstances and the data that represents and describes them, the catastrophic failure of AI is often inevitable without appropriate strategies in place.
His dissertation project, supervised by Prof. Dr. Dr.-Ing. Dr. h. c. Ovtcharova, also deals with the productive application of artificial intelligence (key terms: incremental learning, data stream mining) and smart strategies to handle concept drift.

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