Prof Jef Caers
Professor Stanford University
Jef Caers received both an MSc (’93) in mining engineering / geophysics and a PhD (’97) in mining engineering from the Katholieke Universiteit Leuven, Belgium. Currently, he is Professor of Earth and Planetary at Stanford University. Jef Caers has pioneered research on data science, artificial intelligence and decision making under uncertainty in developing Earth resources. As the founder of Stanford Mineral-X, Prof. Caers collaborates with the mineral exploration industry to reduce cost and improve discovery. Jef Caers has authored six books on data science and decision making that blend academic rigor with practical industrial applications. He was awarded the Krumbein Medal of the International Association of Mathematical Geosciences for his career achievement.
2026 Agenda Sessions
Modern data science to accelerate discovery
This session explores how advanced analytical techniques, rooted in machine learning, network theory, and stochastic modelling, are transforming mineral exploration across Africa. Showcasing GeoChemNet, a novel approach to visualising geochemical datasets through network analysis, enabling geologists to identify meaningful outliers and patterns that traditional methods often miss. Participants will also examine how stochastic interpolation of flightline data is reducing false positives in geophysical surveys, improving the accuracy of subsurface targeting and saving millions in exploration costs.
Wednesday 11 February 14:50 - 15:50 Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall)
Disruptive technologies
This session explores how advanced analytical techniques, rooted in machine learning, network theory, and stochastic modelling, are transforming mineral exploration across Africa. Showcasing GeoChemNet, a novel approach to visualising geochemical datasets through network analysis, enabling geologists to identify meaningful outliers and patterns that traditional methods often miss. Participants will also examine how stochastic interpolation of flightline data is reducing false positives in geophysical surveys, improving the accuracy of subsurface targeting and saving millions in exploration costs.
Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall) Africa/JohannesburgAI-based optimisation of exploration, mining and mineral processing
This conversation begins with a look at AI-based prospect generation, where algorithms are now capable of synthesising geological data with economic viability, environmental constraints, and social impact models to identify targets that are not only rich in minerals but also feasible and responsible to develop.
Wednesday 11 February 16:10 - 17:10 Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall)
Disruptive technologies
This conversation begins with a look at AI-based prospect generation, where algorithms are now capable of synthesising geological data with economic viability, environmental constraints, and social impact models to identify targets that are not only rich in minerals but also feasible and responsible to develop.
Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall) Africa/Johannesburg
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