Yannik Hahn, M.Sc.
Scientific Researcher
Area of Research:
- Machine and Deep Learning
- Natural Language Processing
- Explainable AI
Biography
Yannik Hahn joined the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal in June 2021 as a research assistant and doctoral student.
Mr. Hahn studied computer science at Heinrich Heine University in Düsseldorf in his bachelor's and then in his master's degree with a focus on machine learning and deep learning. In his master's thesis, he investigated the ability of transformer-based neural networks to summarize texts across languages. At the TMDT he will dedicate himself to the research topics Reinforcement Learning and Explainable AI.
Publications
- 2024
- Hahn, Y., Maack, R., Buchholz, G., Purrio, M., Angerhausen, M., Tercan, H., & Meisen, T. (2024). "Quality Prediction in Arc Welding: Leveraging Transformer Models and Discrete Representations from Vector Quantised—VAE" in Proceedings of the 33st ACM International Conference on Information & Knowledge Management .
ISBN: 979-8-4007-0436-9
- 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),
- 2023
- Hahn, Y., Langer, T., Meyes, R., & Meisen, T. (2023). "Time Series Dataset Survey for Forecasting with Deep Learning" , Forecasting , 5 (1), 315—335.
- Hahn, Y., Maack, R., Buchholz, G., Purrio, M., Angerhausen, M., Tercan, H., & Meisen, T. (2023). "Towards a Deep Learning-based Online Quality Prediction System for Welding Processes" , Procedia CIRP , 120 , 1047—1052.
- Bulow, F., Hahn, Y., Meyes, R., Meisen, T., & others, (2023). "Transparent and Interpretable State of Health Forecasting of Lithium-Ion Batteries with Deep Learning and Saliency Maps" , International Journal of Energy Research , 2023 ,
