Dr.-Ing. Richard Meyes, M.Sc.
Scientific Researcher
Head of the Research Field "Interpretable Learning Models"
Area of Research:
- Artificial Intelligence and Machine Learning for Industrial Appliations
- Predictive Analysis of Time Series Data in Industrial Sensor Systems
- Structured Representations in Artificial Neural Networks
Biography
Dr.-Ing. Richard Meyes has been a research associate at the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal since December 2018. His research focuses on the development and investigation of artificial intelligence methods, with a focus on artificial neural networks, in various application fields, including automotive and manufacturing.
Publications
- 2026
- Busch, D., Bohn, C., Kurbiel, T., Friedrichs, K., Meyes, R., & Meisen, T. (2026). Faster Training, Fewer Labels: Self-Supervised Pretraining for Fine-Grained BEV Segmentation.
- 2024
- Alves Gomes, M., Meyes, R., Meisen, P., & Meisen, T. (2024). "It's Not Always about Wide and Deep Models: Click-Through Rate Prediction with a Customer Behavior-Embedding Representation" , Journal of Theoretical and Applied Electronic Commerce Research , 19 (1), 135—151.
- Busch, D., Freeman, I., Meyes, R., & Meisen, T. (2024). Improved Single Camera BEV Perception Using Multi-Camera Training.
- Hahn, Y., Kienitz, P., Wönkhaus, M., Meyes, R., & Meisen, T. (2024). "Towards Accurate Flood Predictions: A Deep Learning Approach Using Wupper River Data" , Water , 16 (23),
- 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),
