Prof. Dr. Michael Kohlegger

Senior Lecturer +43 512 2070 - 4334 michael.kohlegger@mci.edu

Prof. Dr. Michael Kohlegger is a lecturer in Data Engineering, Data Science, and Software Development at the Management Center Innsbruck. Until September 2024, he was the Vice-Rector of FH Kufstein Tirol and led the degree programs in Data Science & Intelligent Analytics, Web Engineering & IT Solutions, as well as Coding & Digital Design. His work focuses on the storage and analysis of data, emphasizing a holistic processing approach from data collection to analysis. In addition to his leadership and teaching roles at FH Kufstein Tirol and the University of Innsbruck, he advises companies on implementing data-driven projects. After studying and earning his doctorate in Business Informatics at the University of Innsbruck, he worked in the industry for several years before accepting a position at FH Kufstein Tirol.

Professional work experience

10/2024 - present
Senior Lecturer in Data Science - FH Kufstein Tirol - University of Applied Sciences
10/2024 - present
Senior Lecturer in Information Systems - WU - Wirtschaftsuniversität Wien
10/2024 - present
Professor for Data Science & Data Engineering - MCI | Die Unternehmerische Hochschule
12/2021 - 09/2024
Director of Studies - FH Kufstein Tirol - University of Applied Sciences
11/2021 - 09/2024
Vice Rector - FH Kufstein Tirol - University of Applied Sciences
09/2017 - 12/2021
Vice Director of Studies - FH Kufstein Tirol - University of Applied Sciences
07/2016 - 09/2024
Professor for Data Science & Data Engineering - FH Kufstein Tirol - University of Applied Sciences
12/2013 - 06/2016
Business Analyst - SOS Children's Villages International
04/2013 - 09/2013
Research Assistant - University of Innsbruck
04/2009 - 03/2013
University Assistant - University of Innsbruck

Education

10/2009 - 06/2013
Dr. - University of Innsbruck
Business Informatics
10/2004 - 06/2008
Mag. - University of Innsbruck
Business Informatics

Teaching (faculty internships etc.)

10/2012 - 07/2015
Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik
Information Systems
01/2009 - 07/2015
WIFI Tirol
Technical Mathematics

Practice related research and developmental project

01/2023 - 09/2024
Co-Project Leader and Co Scientific Advisor - FH Kufstein Tirol - University of Applied Sciences
Vision2Move-Multi-Object Tracking in Mobility Systems
07/2022 - present
Co- Project Leader and Lead Scientific Advisor - FH Kufstein Tirol - University of Applied Sciences
ALMODA - Anomaly detection for detecting faulty signals in autonomous mobility
12/2018 - 12/2020
Project member - FH Kufstein Tirol - University of Applied Sciences
Digital map for culinary experiences and training program for Tyrolean restaurants
02/2018 - 08/2021
Project leader - FH Kufstein Tirol - University of Applied Sciences/TWF
Usability of voice assistants
01/2018 - 04/2021
Project Member and Project Lead FH Kufstein - FH Kufstein Tirol - University of Applied Sciences/Tiroler Leuchtturmförderung
Digital Tourism Expert

Positions in professional/academic societies

05/2020 - present
Conference Board - International Conference on AI Research

Chapters in books

Kohlegger M., Ploder C. (2018). Data Driven Knowledge Discovery for Continuous Process Improvement. In North K., Maier R., Haas O. (Eds.), Knowledge Management in Digital Change (pp. 65 - 81). Wiesbaden: Springer, https://doi.org/10.1007/978-3-319-73546-7_4

Peer reviewed academic/professional meeting proceedings

Ascher, Sabine, Mirjam Klammsteiner, Michael Kohlegger. 2023. "Can you trust in me? A qualitative literature review on validation techniques for multi-sensory environments in autonomous driving." In: Proceedings of the Scientific Computing Conference 2023, Graz. pp. 136-141. https://2023.scientific-computing-conference.fh-joanneum.at/wp-content/uploads/sites/2/2023/04/Conference-Proceedings-Scientific-Computing.pdf
Klammsteiner, Mirjam, Mario Döller, Patrik Golec, Michael Kohlegger, Ehtsham Rashid, Stefan Mayr. 2023. "Vision based stationary railway track monitoring system." In Proceedings of the 33th FRUCT conference, IEEE Explore, Zilina, Slovakia. doi: 10.23919/FRUCT58615.2023.10143067
Ploder, C., & Kohlegger, M. (2018). A Model for Data Analysis in SMEs Based on Process Importance. In Knowledge Management in Organizations: 13th International KMO 2018, Proceedings (pp. 26-35). Cham: Springer. https://doi.org/10.1007/978-3-319-95204-8_3