Pieter is a Professional Geoscientist with education and experience in geology, chemistry, soil science, applied mathematics, terrain evaluation and satellite analysis, business administration, mineral exploration and corporate strategy. He also developed and applied Machine and Deep Learning models for a variety of agricultural, forestry and environmental rehabilitation applications.
He founded and sold a company performing satellite analysis for mineral exploration and developed novel Artificial Intelligence models to utilize satellite and soil sample data to quantify organic matter, nutrients and micronutrients in agricultural applications.
Pieter provides the Axiom Group with critical expertise for enhanced performance and efficiency in mineral exploration, advanced data analytics, data forecasting, project management, strategic operations and planning, financial modelling, probabilistic risk modelling, mining and milling portfolio optimization, mineral resource management and more.
Pieter is a Professional Geoscientist with Tertiary education in Geology, Chemistry, Soil Science, Mathematics, Applied Mathematics, Terrain Evaluation, including satellite analysis and Business Administration. His career started in the 1990’s where geological expertise and satellite analysis was applied to mineral exploration projects. He has a broad spectrum of international experience from mineral exploration to corporate strategy across several commodities, including gold, diamonds, uranium, coal, base metals, oil shales and mineral sands. Pieter managed US$100 million per annum exploration programs that employed over 300 people in Canada.
He founded and sold a company for satellite analysis on mineral exploration and developed novel Artificial Intelligence models to utilize satellite and soil sample data to quantify organic matter, nutrients and micronutrients in agricultural applications. He also developed Machine and Deep learning models for applications in forestry and environmental rehabilitation using satellite, helicopter and UAV based spectral data to identify tree and other vegetation species.
Pieter also developed novel Machine Learning models to quantify Kaolinite and Halloysite minerals from spectral data for a project in Australia, resulting in several orders of magnitude cost savings for the client and an international publication.