Institute for Technologies and Management of Digital Transformation

Florian Hölken, M.Sc.

Scientific Researcher

Area of Research:

  • Semantic Interoperability
  • Dataspaces
  • Machine and Deep Learning
  • Explainable and Transparent Artificial Intelligence

 

Biography

Florian Hölken has been a research assistant at the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal since September 2023. He initially joined the institute as a technical assistant in January 2022.

His research focuses on the semantic interoperability of networked digital systems with the aim of enabling consistent and cross-contextual information exchange between heterogeneous systems. Another focus is on dataspaces, which support the secure, sovereign, and value-adding use of data across organizational boundaries.

In addition, he works on machine learning and deep learning methods for analyzing complex data sets and developing intelligent, data-driven applications. He pays particular attention to explainable and transparent artificial intelligence, especially with regard to traceability, trustworthiness, and the responsible design of algorithmic decision-making systems.

Publications

2025
Hütten, N., Hölken, F., Tercan, H., & Meisen, T. (2025). Detection Transformers Under the Knife: A Neuroscience-Inspired Approach to Ablations.
Hütten, N., Hölken, F., Tercan, H., & Meisen, T. (2025). Detection Transformers Under the Knife: A Neuroscience-Inspired Approach to Ablations.
Hölken, F., Paulus, A., Meisen, T., & Pomp, A. (2025). "Smart City Urban Heat Monitoring using a Solid-based Dataspace" in The Third International Workshop on Semantics in Dataspaces, co-located with the Extended Semantic Web Conference .
2024
Hütten, N., Alves Gomes, M., Hölken, F., Andricevic, K., Meyes, R., & Meisen, T. (2024). "Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open- Access Papers" , Applied System Innovation , 7 (1),
Paulus, A., Hölken, F., Chmielewski, S., & Pomp, A. (2024). "IoT4H: Datengewinnung und -nutzung für innovative Geschäftsmodelle im Handwerk" , HMD Praxis der Wirtschaftsinformatik , 61 (6), 1540—1550.