Dr.-Ing. Richard Meyes, M.Sc.
Wissenschaftlicher Mitarbeiter
Leiter des Forschungsbereichs "Interpretable Learning Models"
Forschungsinteressen:
- Artificial Intelligence and Machine Learning for Industrial Appliations
- Predictive Analysis of Time Series Data in Industrial Sensor Systems
- Structured Representations in Artificial Neural Networks
Biographie
Dr.-Ing. Richard Meyes ist seit Dezember 2018 wissenschaftlicher Mitarbeiter am Institute for Technologies and Management of Digital Transformation an der Bergischen Universität Wuppertal. Seine Forschungsschwerpunkte liegen in der Entwicklung und Untersuchung von Methoden der künstlichen Intelligenz, mit Fokus auf künstliche neuronale Netze, in verschiedenen Anwendungsfeldern, darunter Automotive und Produktion.
- 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), 11.
- Langer, T., Meyes, R., & Meisen, T. (2024). "Guided Exploration of Industrial Sensor Data" , Computer Graphics Forum , 43 (1),
- 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.
- 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.
- Jantunen, M., Meyes, R., Kurchyna, V., Meisen, T., Abrahamsson, P., & Mohanani, R. (2024). "Researchers’ Concerns on Artificial Intelligence Ethics: Results from a Scenario-Based Survey" in Proceedings of the 7th ACM/IEEE International Workshop on Software-intensive Business , New York, NY, USA : ACM 24—31.
ISBN: 9798400705717
