Fabian Gieseke

Prof. Dr. Fabian Gieseke is a Professor and Chair of Machine Learning and Data Engineering at the University of Münster. He holds a PhD in Computer Science from Carl von Ossietzky University of Oldenburg and a dual degree in Mathematics and Computer Science from the University of Münster. His research focuses on Machine Learning, High-Performance Computing, and their applications in Geosciences, Smart Cities, and Astrophysics.

Education:

• PhD in Computer Science (2012), Carl von Ossietzky University of Oldenburg
• University studies in Mathematics and Computer Science (2006–2011), University of Münster

Research Interests:

• Data Mining and Machine Learning
• High-Performance Computing & Distributed Systems
• Deep Learning Applications in Environmental Science and Astrophysics
• Geospatial Data Analysis using Satellite Imagery

Publications Trends: His recent work emphasizes large-scale environmental monitoring via deep learning, including canopy height estimation, forest biomass prediction, and national-scale tree counting. He also explores interactive systems for geospatial data retrieval and optimization of machine learning models for resource-constrained environments.

Advising & Grants: Supervised over 30 theses on topics like satellite image analysis, deep learning on microcontrollers, and data marketplaces for smart grids. Active in securing grants for interdisciplinary projects combining AI with Earth observation.

Labs/Teams: Leads the Machine Learning and Data Engineering group at the University of Münster, focusing on scalable AI solutions for real-world challenges in science and industry.