Explore my complete portfolio of API Development, data science, GIS, and engineering work
Forecasts drought severity (SPEI-3) over the Al-Kharj–Riyadh Basin, Saudi Arabia, comparing an interpretable XGBoost baseline against a ConvLSTM spatiotemporal deep learning model. Fuses CHIRPS, ERA5-Land, MODIS and GLDAS/FLDAS onto a common 5 km grid, 2000–2024, evaluated with RMSE, R² and KGE.
View Project
How basin geomorphology controls drought severity across eight Middle Eastern river basins, using GRACE/GRACE-FO water storage anomalies, a 12.5 m ALOS PALSAR DEM and explainable XGBoost with SHAP. Includes a counterfactual isolating how much land-use change amplified drought.
View Project
Machine learning and deep learning flood-prone area prediction from RGB orthophotos, DTM and DSM. Engineers terrain features (slope, aspect, curvature), hydrological features (D8 flow accumulation, HAND, distance to water) and infrastructure proximity.
View Project
Land use / land cover classification from high-resolution orthophoto imagery, benchmarking models with and without DSM/DTM elevation inputs to quantify what elevation data contributes to accuracy.
View Project
Research into how land use change amplifies hydrological drought, combining machine learning with remote sensing time series.
View Project
Spatiotemporal analysis and forecasting of population growth hotspots in Nigeria using WorldPop data and ArcGIS Pro space-time pattern mining. Presented at the ESRI User Conference 2025.
View Project
Machine learning model classifying land cover pixels into forest, cocoa plantation and palm plantation from satellite imagery.
View Project
GeoAI challenge entry predicting surface NO&sub2; concentrations from satellite and ancillary data using machine learning.
View Project
End-to-end machine learning pipeline predicting soil organic carbon, built on Google Earth Engine and GEEMAP for data extraction and modelling.
View Project
Visualize and analyze forest data in Nigeria using remote sensing datasets and various forest-related indices.
View Project
Monitor agricultural lands using satellite imagery, computing vegetation indices like NDVI and NDMI.
View Project
Spatial statistical analysis of HIV prevalence patterns across the United States with socio-demographic factors.
View Project
GEE app to visualize and analyze land use changes in the Amazon, exploring deforestation trends.
View Project
Machine learning classification of mangroves and land use in Benin Republic achieving 90%+ accuracy.
View Project
Automated geospatial pipeline using ArcGIS and Earth Engine for tree health monitoring.
View Project
GIS analysis of education and healthcare accessibility in Zamfara State, Nigeria.
View Project
EPA monitoring station data analysis to model Ozone, Nitrogen, and PM2.5 distribution using R Spatial.
View Project
Machine learning model predicting flood likelihood based on topographical and environmental factors.
View Project
Spatial modeling framework for predicting SOC concentrations in Mato Grosso, Brazil using ML.
View Project
Spatial analysis of Airbnb listings and housing market dynamics in London using advanced techniques.
View Project
Analysis of the 2022 Mosquito Fire in California using satellite imagery and Geemap.
View Project
WebGIS platform measuring healthcare accessibility and identifying optimal locations for new facilities.
View Project
Location intelligence analysis to find the perfect restaurant spot near Osun-Osogbo Sacred Grove.
View Project
Bespoke end-to-end platform: React dashboards with in-browser GIS, a FastAPI + PostGIS backend, MinIO storage, and a YOLO bunch-detection model integrated into a field mobile app — including core GIS built to detect fraud in field reporting. I owned the frontend, backend, data engineering, ML, and infrastructure.
View Project
Demand intelligence platform for the CGIAR Science Program Accelerator. Mines policy documents and secondary data from governments, NGOs, and international organisations into 380+ evidence-backed demand signals, explorable by country on an interactive map and filterable by domain and CGIAR impact area.
View Project
I designed, built, and deployed a complete API endpoint that allows Property Owners and Real Estate Professionals to instantly understand the Climate Risk associated with the land or properties they are considering purchasing — plus the cloud-native data architecture behind it.
View Project
ETL pipeline built with Apache Airflow and Docker, extracting foreign exchange data on a schedule, transforming it and loading it for analysis.
View Project
End-to-end analytics on Uber trip data in Google Cloud: raw data in Cloud Storage, Mage orchestrating the ETL on Compute Engine, BigQuery for analytics and Looker for reporting.
View Project
ETL pipeline extracting data from ArcGIS Feature Services and transforming it into JSON and GeoDataFrame formats for downstream processing.
View Project
Ingests points of interest — schools, police facilities, hospitals — from multiple sources, then transforms and loads them into a unified geospatial store.
View Project
Scalable data pipeline extracting country data from APIs, transforming and visualizing in Metabase.
View Project
Automated scraping of YouTube trending videos using Selenium and AWS Lambda.
View Project
Extract and blend property datasets across Greater London into one comprehensive master list.
View Project
AWS-based system using Lambda, S3, EventBridge, and DynamoDB to collect weather data for Lagos.
View Project
Visual report analyzing airline passenger satisfaction feedback using Tableau.
View Project
Dashboard analysis exploring and uncovering insights into Unicorn company performance metrics using Looker.
View Project