Jörn Hees

Prof. Jörn Hees is a Professor for Data Science at the Department of Computer Science, Hochschule Bonn-Rhein-Sieg (H-BRS), and serves as Chairman of the Computer Science Faculty Council. He is affiliated with the Institute for Artificial Intelligence and Autonomous Systems (A2S) and the Institute of Technology, Resource and Energy-efficient Engineering (TREE). His research focuses on Data & Graph Mining, Deep Learning, Anomaly Detection, Explainable AI, and AI-assisted education (e.g., automated grading systems).

He teaches courses such as Stochastics, Data Analysis and Visualization, Artificial Intelligence (Bachelor level), and Deep Learning Foundations, Natural Language Processing (Master level). His work bridges theoretical advancements with practical applications in finance, remote sensing, and education. Notable projects include federated outlier detection systems (Fin-Fed-OD), the TreeSatAI benchmark dataset for tree species classification, and AI-driven grading solutions using LLMs.

His publications emphasize anomaly detection techniques, multimodal fusion, and interpretable machine learning. Despite no explicit awards listed, his contributions to AI education and computational methods are evident through his extensive publication record. He coordinates research teams and advises on infrastructure for AI education and infrastructure monitoring via Earth observation data.