Prof. Dr.-Ing. Tobias Meisen
Professor of Technologies and Management of Digital Transformation
Area of Research:
- Deep and Machine Learning
- Deep Reinforcement Learning
- Explainable and Transparent Artificial Intelligence
- Knowledge Graphs
- Semantic Interoperability
Biography
Tobias Meisen is Professor of the Institute for Technologies and Management of Digital Transformation (TMDT) at the University of Wuppertal since September 2018. He is also chair of the Interdisciplinary Center for Data Analytics and Machine Learning (IZMD) and has been a founding ambassador of the School of Electrical, Information and Media Engineering since October 2018. He is also co-founder of Hotsprings GmbH, which is now a part of umlaut.
In his daily work, Tobias Meisen is dedicated to digital transformation, especially modern information management in a networked, digital world. The focus of his research is the conceptual design, development and implementation of autonomous technical systems with a focus on deep learning and machine learning. In his second research area, he is dedicated to the collection and integration of digital data with a special focus on the evolutionary construction and management of Knowledge Graphs.
Tobias Meisen studied computer science with a specialization in data mining as well as data exploration and management and holds a PhD in engineering. From October 2015 to August 2018, Tobias Meisen was a junior professor at RWTH Aachen University. He contributed his research results here as part of the Cluster of Excellence "Integrative Production Technology for High-Wage Countries". In March 2010, he was awarded the Young Researcher Award as part of the first funding phase of the Excellence Initiative. Tobias Meisen is co-author and author of more than one hundred scientific publications and regularly serves as a reviewer for various conferences and journals. In recent years, he and his team have successfully supported a large number of research and development projects with partners from research and industry.
Publications
- 2021
- Steiniger, Y., Groen, J., Stoppe, J., Kraus, D., & Meisen, T. (2021). "A study on modern deep learning detection algorithms for automatic target recognition in sidescan sonar images" , Proceedings of Meetings on Acoustics ,
- Müser, S. (2021). "Die Erfassung des bildungswissenschaftlichen Wissens im Lehramtsstudium: Konstruktion und Validierung des ESBW-Tests sowie die Untersuchung des Praxisschocks im Praxissemester" , {University of Duisburg-Essen} .
- Pomp, A., Paulus, A., Burgdorf, A., & Meisen, T. (2021). "A Semantic Data Marketplace for Easy Data Sharing within a Smart City" in Proceedings of the 30th ACM International Conference on Information & Knowledge Management , Demartini, Gianluca and Zuccon, Guido and Culpepper, J. Shane and Huang, Zi and Tong, Hanghang, Eds. New York, NY, USA : ACM 4774—4778.
ISBN: 9781450384469
- Scheiderer, C., Dorndorf, N., & Meisen, T. (2021). "Effects of Domain Randomization on Simulation-to-Reality Transfer of Reinforcement Learning Policies for Industrial Robots" in Advances in Artificial Intelligence and Applied Cognitive Computing , Arabnia, Hamid R. and Ferens, Ken and de {La Fuente}, David and Kozerenko, Elena B. and {Olivas Varela}, José Angel and Tinetti, Fernando G., Eds. Cham : Springer International Publishing and Imprint Springer , 157—169.
ISBN: 978-3-030-70295-3
- Steiniger, Y., Stoppe, J., Kraus, D., & Meisen, T. (2021). "Erzeugung von synthetischen Seitensichtsonar-Bildern mittels Generative Adversarial Networks" , Hydrographische Nachrichten , 30—34.
