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
- 2020
- Meyes, R., Waubert-de-Puiseau, C., Posada-Moreno, A., & Meisen, T. (2020). "Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations" .
- 2019
- Meyes, R., Donauer, J., Schmeing, A., & Meisen, T. (2019). "A Recurrent Neural Network Architecture for Failure Prediction in Deep Drawing Sensory Time Series Data" , Procedia Manufacturing , 34 , 789—797.
- Meyes, R., Lu, M., Waubert-de-Puiseau, C., & Meisen, T. (2019). "Ablation Studies in Artificial Neural Networks" , arXiv arXiv:1901.08644 .
- Meyes, R., Tercan, H., & Meisen, T. (2019). "Artificial Intelligence in Automotive Production" , Mobility in a Globalised World 2018 , 22 , 308—324.
- Baer, S., Bakakeu, J., Meyes, R., & Meisen, T. (2019). "Multi-Agent Reinforcement Learning for Job Shop Scheduling in Flexible Manufacturing Systems" in 2019 Second IEEE International Conference on Artificial Intelligence for Industries , Los Alamitos, CA : IEEE-Computer-Society 22—25.
ISBN: 978-1-7281-4087-2
