Chair for Technologies and Management of Digital Transformation
Univ. Prof. Dr. Ing. Tobias Meisen
Prof. Dr.-Ing. Tobias Meisen
Chair of Technologies and Management of Digital Transformation
Office: FME 01.03d
Tel.: +49 202 439 1039
Mobil: +49 151 12208097
Prof. Dr.-Ing. Tobias Meisen
Professor for Technologies and Management of Digital Transformation
- Deep and Machine Learning
- Knowledge Graphs
- Semantic Interoperability
- Transfer Learning
- Explainable and Transparent Artificial Intelligence
Tobias Meisen is Professor of the Chair for Technologies and Management of Digital Transformation at the University of Wuppertal since September 2018. He is member of the board of the Interdisciplinary Center for Data Analytics and Machine Learning (IZMD) and since October 2018 founding ambassador of the School of Electrical Engineering, Information and Media Engineering. Tobias Meisen is second chairman of the VDI Aachener Bezirksverein and co-founder of Hotsprings GmbH.
In his daily work he is dedicated to modern information management in a networked digital world. His research focuses on the conceptual design, development and implementation of autonomous technical systems with a focus on machine learning and deep learning. Furthermore, he dedicates his work to semantic integration, especially the automatic construction and management of knowledge graphs. In the context of deep learning he researches the traceability and explainability of decisions in deep neural networks.
Tobias Meisen holds a degree in computer science with a focus on data mining and data exploration and management as well as a doctorate in engineering. From October 2015 to August 2018 Tobias Meisen was junior professor at the RWTH Aachen. Among other things, he contributed his research results to 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. He is co-author and author of more than ninety scientific publications and regularly acts as reviewer for various conferences and journals.
In recent years, he and his team have successfully accompanied the introduction and application of machine learning methods in productive, industrial environments and the development of suitable integration architectures in numerous research and development projects with the industrial sector.
Generating Synthetic Sidescan Sonar Snippets Using Transfer-Learning in Generative Adversarial NetworksJournal of Marine Science and Engineering, 9(3):239
System Design to Utilize Domain Expertise for Visual Exploratory Data AnalysisInformation, 12(4):140
Synergiepotenziale von Virtual City Twins im Bereich automatisiertes Fahren -- Beschleunigung der technischen Entwicklung und Überwindung von Akzeptanzbarrieren
Proff, Heike, editor, Making Connected Mobility Work Volume 119
Publisher: Springer Fachmedien Wiesbaden, Wiesbaden
Manufacturing Control in Job Shop Environments with Reinforcement Learning
Proceedings of the 13th International Conference on Agents and Artificial Intelligence , page 589--597.
Publisher: SCITEPRESS - Science and Technology Publications,
Recent Advances and Future Challenges of Semantic Modeling
2021 IEEE 15th International Conference on Semantic Computing (ICSC) , page 70--75.