Turning satellite imagery, spatial data, and machine learning into actionable intelligence. Specializing in GIS, remote sensing, and geospatial AI across East Africa and beyond.
Designed and implemented a national geospatial addressing framework integrating house numbering, street naming, postcode systems, GIS, geocoding, and spatial data management. The project establishes a standardized digital addressing infrastructure aligned with ISO/TC 211 and UPU standards to support emergency response, logistics, urban planning, e-governance, and smart city development.
Upgraded the PeMOST App by integrating geospatial analytics, crop & pest modeling, and predictive machine learning for Tomato Leaf Miner management in Machakos County, Kenya.
Developed BAU scenario of land degradation and restoration opportunities in the GRV by 2030. Analyzed socioeconomic impacts on food security, income, and poverty. Used LULC mapping and RUSLE analysis.
Extracted spatial data from high-resolution street-level images using AI-powered tools (Mapillary, Mapilio) integrated with OSM iD editor to enhance map detail and accuracy.
Tested core functionalities of the Tasking Manager application after migrating its backend from Flask to FastAPI, ensuring correctness and stability of all features.
Modeled and predicted effects of climate variability on maize phenology in Muringato Catchment, Nyeri, using Sentinel-2 imagery, vegetation indices, and multivariate regression models.