MSc Geoinformatics | Geospatial AI & Earth Observation

I specialize in bridging the gap between Deep Learning and Remote Sensing. My work focuses on building intelligent systems (GIS Agents) and high-precision mapping models using state-of-the-art foundation models and geospatial libraries.

Category	Tools & Technologies
Languages
Geospatial	GDAL
AI / Machine Learning
Data & Databases
DevOps & Cloud

Foundation Model for Land Use and Land Cover (LULC).

• Utilized the Clay Foundation Model for fine-tuning on multi-spectral satellite imagery.
• Improved classification accuracy in heterogeneous landscapes by leveraging self-supervised pre-training weights.

Canopy Height Model Generation.

• Developed a high-resolution CHM estimation pipeline using the DinoV3 (Vision Transformer) architecture.
• Trained on the CHM2 dataset, pushing the boundaries of monocular height estimation from satellite/aerial imagery.