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
- 2017
- Meyes, R., Tercan, H., Roggendorf, S., Thiele, T., Büscher, C., Obdenbusch, M., Brecher, C., Jeschke, S., & Meisen, T. (2017). "Motion Planning for Industrial Robots using Reinforcement Learning" , Procedia CIRP , 63 , 107—112.
- Haßler, M., Kohlschein, C., & Meisen, T. (2017). "Similarity Analysis of Time Interval Data Sets—A Graph Theory Approach" , ITISE 2017: Time Series Analysis and Forecasting , 159—171.
- Haßler, M., Kohlschein, C., & Meisen, T. (2017). "Similarity Analysis of Time Interval Data Sets---A Graph Theory Approach" , ITISE 2017: Time Series Analysis and Forecasting , 159--171.
- Haßler, M., Jeschke, S., & Meisen, T. (2017). "Similarity Analysis of Time Interval Data Sets Regarding Time Shifts and Rescaling" , Proceedings International work-conference on Time Series , 995—1006.
- Hoffmann, M., Thomas, P., Schütz, D., Vogel-Heuser, B., Meisen, T., & Jeschke, S. (2017). "Semantic Integration of Multi-agent Systems Using an OPC UA Information Modeling Approach" , IEEE International Conference on Industrial Informatics (INDIN) , 744—747.
