Prof. Dr.-Ing. Daniel Böhnke

Portrait of Daniel Böhnke© A. Diekötter

Engineering Computer Science

Schwentinestrasse 13
24149 Kiel
Room: C05-0.37

Prof. Dr.-Ing. Böhnke holds the professorship for Engineering Informatics in the Department of Mechanical Engineering. The focus of his work is the interface between engineering sciences and computer science. In both teaching and research, he is engaged with the digitalization of mechanical engineering. His teaching portfolio includes the fundamental principles of computer science for engineers, as well as specialized courses in machine learning and the programming of numerical methods.

In the field of research, the focus is on the application of machine learning methods in an engineering context, particularly in production. Some of the topics covered include condition monitoring, predictive maintenance, numerical optimization, and the processing of CAD data with AI.

Prof. Böhnke is also the head of the Practice-Oriented Studies (PBS) program at the university of applied sciences.

Information about the individual courses can be found in the module database.

       

      • Professor of engineering computer science at the Kiel University of Applied Sciences
      • Product Owner Data Science at Lufthansa Industry Solutions
      • Project manager and deputy department head at DLR, Institute for Air Transport Systems
      • Doctorate Dr.-Ing. at the Technical University of Hamburg
      • Dipl.-Ing. Aerospace Engineering University of Stuttgart & Southampton

      Projects

      • AI Transfer Hub SH (2020-2023) 
      • Argus AI (2023-2025)
      • Offer AI (2023-2026)
      • AI Application Center SH (2023-2028)

      Audio Anomaly Detector (AAD)

      The AAD is a device that can be used to monitor machines based on their noise. To do this, an AI model is trained with sound recordings of the machine so that it can recognize deviations from normal operation. Information about the anomalies can be tracked live via dashboard. More information

      ORCID-ID: 0000-0003-2781-2685

      The consultation hour takes place on Tuesdays at 1:30 PM (usually online). Please register in advance via email.

      If you are interested in a thesis, a separate consultation hour is held every two weeks. Please also send a short email to register.