Yannik Hahn

Yannik Hahn serves as a Scientific Researcher and doctoral student at the Institute for Technologies and Management of Digital Transformation (TMDT) at the University of Wuppertal since June 2021, focusing on machine learning applications for industrial and environmental systems.

His educational background includes a Bachelor's and Master's degree in Computer Science from Heinrich Heine University Düsseldorf, specializing in machine learning and deep learning. His Master's thesis investigated cross-lingual text summarization using transformer-based neural networks.

Hahn's research spans Machine Learning, Deep Learning, Natural Language Processing, Explainable AI, and Reinforcement Learning, with emphasis on practical implementations in manufacturing quality control and environmental forecasting. His work bridges theoretical AI advancements with real-world industrial challenges.

Analysis of his publications reveals a consistent focus on transformer architectures and deep learning for time-series applications, particularly in arc welding quality prediction and flood forecasting. His research demonstrates innovation in representation learning, out-of-distribution detection, and efficient continual learning systems for industrial deployment.

No scientific awards are documented in the available materials.

As a doctoral candidate, Hahn has no listed advisees or formal mentoring responsibilities. No research grants or funding sources are specified in the provided documentation.

He operates within the Institute for Technologies and Management of Digital Transformation (TMDT), which specializes in digital transformation technologies and their industrial implementation, particularly in manufacturing and environmental monitoring contexts.