Assistant Professor of Intelligent Maintenance Systems at ETH Zürich and Research Affiliate at Massachusetts Institute of Technology. Before joining ETH faculty, was heading the Smart Maintenance research group, Zurich University of Applied Sciences (ZHAW). PhD in Civil Engineering on machine learning in fault detection and prediction in railway systems, ETH Zurich; Diploma degree in Industrial Engineering, Hamburg University of Technology. Has gained valuable industrial experience as reliability engineer for railway rolling stock and as reliability and maintenance expert for railway systems. Core of research is the development of intelligent algorithms for massive and heterogeneous condition monitoring data of complex industrial assets and critical infrastructure. It helps to improve performance, safety and availability, and make maintenance and operation more cost-efficient. Develops artificial intelligence algorithms that are not only applicable to one specific system but to entire fleets of systems, enabling the operating experience and fault patterns to be transferred between single systems. Research makes the algorithms generalizable and their development scalable. The systems considered in the research range from gas turbines and generators to railway rolling stock and airplanes.
