Marc Rußwurm

Marc Rußwurm is an Assistant Professor of Machine Learning and Remote Sensing at Wageningen University, affiliated with the Laboratory of Geo-information Science and Remote Sensing. He holds a Ph.D. in Remote Sensing Technology from Technical University of Munich (2022) and completed postdoctoral research at EPFL (2021-2023). His work focuses on applying modern machine learning methods to real-world remote sensing challenges, including vegetation classification using satellite time series and marine debris detection. He is particularly interested in domain shifts and transfer learning in geographic data.

Education:

• Ph.D. (Dr.Ing), Technical University of Munich (2018-2021)
• Postdoctoral Researcher, Swiss Federal Institute of Technology Lausanne (EPFL, 2021-2023)

Research Interests:

• Machine learning for remote sensing
• Satellite time series analysis
• Transfer learning and domain adaptation
• Marine debris detection
• Geospatial data modeling

Recent Research Trends: His articles emphasize innovative applications of machine learning in environmental monitoring, including spectral index searches for marine debris, location embeddings via satellite imagery, and data-centric approaches for Earth observation. He also explores challenges in model extrapolation and cross-resolution analysis.

Advising & Grants:

• Co-promotor for PhD candidates V. Nedungadi (Machine Learning for Agriculture) and C. Robin (Spatiotemporal Ecosystem Dynamics)
• Involved in collaborative projects on tropical forest loss and Antarctic ice mapping

Labs/Teams: Active in the Laboratory of Geo-information Science and Remote Sensing at Wageningen University, contributing to interdisciplinary research on geospatial technologies.