GEOSPATIAL DATA SCIENCE • GEOAI • GIS • EARTH INTELLIGENCE
I’m Gael Ndi Nkwain, Ph.D., a geospatial data scientist and geoscientist. I transform complex spatial, geological, environmental and subsurface data into validated geospatial databases, maps, models and analytical products for real-world decisions.
Acquire → Validate → Integrate → Analyze → Visualize → Decide
FEATURED PROJECTS
Virginia Atlantic Coastal Plain pilot integrating geology, USGS NURE geochemistry, mineral occurrences and geographic layers into a spatially queryable PostgreSQL/PostGIS environment.
Built to convert fragmented public geoscience data into analysis-ready spatial evidence for critical-mineral assessment.
Connected borehole location and depth, core observations, biostratigraphy, wireline logs, legacy records and regional geology to support cross-site correlation and regional subsurface interpretation.
Integrated geographic position, water depth, biological proxy observations, stable isotopes, environmental variables and time to identify environmental patterns across marine datasets.
Integrating hydrogeological observations and geospatial layers to reveal vulnerability patterns and translate water-resource data into interpretable spatial intelligence.
EXPERIENCE
Developing geospatial intelligence workflows that integrate public geology, geochemistry and mineral-resource information for critical-mineral and Earth-intelligence applications.
Atlantic Coastal Plain subsurface research at the Florence Bascom Geoscience Center: boreholes, cores, stratigraphy, biostratigraphy, legacy records, regional correlation and data integration.
Geology & Geophysics. Built reproducible environmental datasets and applied multivariate analysis, stable-isotope interpretation and spatial context to Arctic and Bering Sea research.
M.Sc. in Geology for Energy Resources at the University of Perugia, Erasmus+ research at Aarhus University, and earlier geology/hydrogeology experience in Cameroon.
TECHNICAL STACK
From ingestion and validation to spatial databases, analysis, modeling and communication.
GIS & Spatial Analysis
ArcGIS Pro · QGIS · GeoPandas · Rasterio · Folium · vector/raster workflows · overlays · spatial joins · CRS
Spatial Data Engineering
Python · SQL · PostgreSQL/PostGIS · Pandas · ingestion · harmonization · provenance · coordinate and attribute validation
GeoAI & Analytics
Random Forest · clustering · feature engineering · multivariate analysis · dimensionality reduction · R
Visualization & Delivery
Interactive maps · Power BI · Tableau · ggplot2 · Matplotlib · Git/GitHub/GitLab
RESEARCH & SCIENTIFIC FOUNDATION
My research background includes paleoenvironmental reconstruction, marine environmental change, benthic foraminiferal assemblages, calcareous nannofossils, stable isotopes and biostratigraphy. On this portfolio, that scientific depth supports the larger goal: rigorous interpretation of complex Earth datasets.
LET’S CONNECT
I’m interested in geospatial data science, GeoAI, GIS, Earth intelligence, critical minerals, environmental intelligence and subsurface analytics.