معرفی
Jef Caers is a Professor of Earth and Planetary Sciences at Stanford University, with a courtesy appointment in Geophysics. He holds a PhD (1997) and MSc (1993) in Mining Engineering and Geophysics from Katholieke Universiteit Leuven, Belgium. His research focuses on decision-making under uncertainty in critical mineral supply chains and geothermal energy development, emphasizing sustainable transitions to renewable energy. He founded the Mineral-X initiative to advance global mineral stewardship.
His work integrates geostatistics, machine learning, and data science to address subsurface uncertainties in energy and mineral resources. Key contributions include Bayesian evidential learning for uncertainty quantification and AI-driven exploration tools like the Intelligent Prospector. He has authored/co-authored five seminal books in geostatistics and data science for geosciences, and received the IAMG's Krumbein Medal for career achievements.
Recent research highlights include POMDP frameworks for lithium supply chain optimization, CO2 leakage quantification in carbon storage, and AI applications for mineral processing. His methodologies bridge geological modeling with decision analysis, offering actionable insights for industry and policy.
Prof. Caers collaborates across disciplines, leading teams in Stanford's School of Earth, Energy & Environmental Sciences. His work emphasizes quantifying uncertainty in subsurface systems to enable robust decision-making for resource management, climate resilience, and sustainable development.
