Research Projects
AIMEX develops and coordinates research directions at the intersection of economic geology, geochemistry, spatial data science, and artificial intelligence. Public repositories listed below remain under the founder’s personal GitHub where they originated; they are linked here as research foundations relevant to AIMEX.
Pyrite AI metallogenic typing
Global pyrite-geochemistry research for metallogenic discrimination using interpretable machine learning and deposit-aware validation.
Galena geochemistry and metallogenic discrimination
Big-data analysis of galena geochemistry for Pb-Zn metallogenic discrimination using machine-learning workflows designed for imbalanced geological datasets.
Gunga Pb-Zn pyrite machine learning
Pyrite trace-element and isotope data used to evaluate machine-learning discrimination of Pb-Zn mineralization and geological classes.
Gunga sphalerite deep learning
Sphalerite geochemistry and isotope research focused on mineralization-zone discrimination and critical-metal signals, including Ge-bearing sphalerite.
GeoAI methodology development
AIMEX research directions include:
- Mineral-system-aware GeoAI
- Geochemical anomaly detection
- Mineral potential mapping methodology
- Remote-sensing evidence integration
- Spatially defensible validation
- Geological database and benchmark design
- Prospective testing and independent benchmarking
Proprietary employer, client, or collaboration code is not published here unless release is explicitly authorized.