Muhammed Enes Duran
I turn geospatial methods into reliable software systems.
Six systems, each occupying one layer of the same stack: deterministic evaluation, geospatial knowledge for agents, guarded execution, reproducible data preparation, decision delivery, and simulation. Every claim below links to something you can inspect.
- Focus
- GeoAI agent systems, spatial ML, secure GIS automation
- Shipped
- 2 PyPI packages, 1 DOI release, 2 live products
- Method
- Invariants first, failure modes second, artifact last
- Based
- Türkiye · open to collaboration
Systems
06 · open each for diagramsbenchfck
Generates its own machine-state tasks and scores them exactly, so no learned judge sits between a model and its result.
geoai-skills
Eighteen agent skills that make an AI assistant fail loudly on CRS, leakage, units and uncertainty instead of quietly guessing.
arcgis-mcp-bridge
Exposes ArcGIS Pro geoprocessing to AI agents while keeping the licensed ArcPy runtime behind a validated process boundary.
sentinel-crop-pipeline
Takes Sentinel-2 scenes from search to training patches, counting every pixel it throws away along the way.
agri-dss
Turns regional agricultural data for 147 neighbourhoods into a crop plan a cooperative can pin to a village board.
FOUNDER.EXE
A startup simulation where cash, compliance, product and people interact under two real regulatory regimes.
* Routing metrics come from the frozen 18-skill, 167-case suite measured on Claude Code 2.1.214 with claude-sonnet-5 (2026-08-05). They describe routing behaviour, not answer quality.
Behind the systems
method & researchBuild spatial systems that hold up.
Available for collaboration around GeoAI agent systems, production-grade spatial data science, remote-sensing ML pipelines, GIS automation, decision-support products and applied simulations.
Based in Türkiye · Open-source, research and production collaboration welcome.