Trevor Rombora

I’m a Geospatial Engineering student skilled in GIS, remote sensing, spatial data analysis, and Python-based geospatial development. I build GeoAI and machine learning solutions that turn spatial data into practical insights for real-world agricultural, environmental, and urban planning needs.

In a JKUAT Hackathon project, I developed Mkulima, a GeoAI-powered web application for data-driven crop yield predictions, crop recommendations, and profit analysis for farmers. I built ML models (Random Forest, Gradient Boost, XGBoost), achieving 86% accuracy, and integrated realtime market prices plus an LLM to produce farmer-friendly outputs. I also ranked top 50 nationally.

Through my Data Science Intern experience at CodeAlpha (October 2025), I built highly accurate Machine Learning models including Random Forest, Gradient Boost and XGBoost, and used Python libraries like Pandas and Scikit-learn for data cleaning and feature engineering. This strengthened my end-to-end workflow from data preparation to model development.

I’m especially passionate about automating geospatial workflows and applying remote sensing datasets through tools like QGIS, GeoPandas, and Google Earth Engine. I want opportunities where I can combine GIS engineering, spatial analytics, and machine learning to deliver actionable decision support.