معرفی
Jonas Kloeckner is a PhD Candidate at the Federal University of Rio Grande do Sul (UFRGS) in the Mineral & Environmental Technology and Extractive Metallurgy Program, focusing on Geostatistics, and concurrently serves as a Visiting Research Scholar at Stanford University under Professor Jef Caers. His academic journey includes a MSc in Engineering and Mining Engineering from UFRGS, a Bac +5 degree from Ecole des Mines d'Alès (France), and a Visiting Student stint at Columbia University (USA).
His research interests span geostatistical modeling of carbonate facies, Bayesian approaches for uncertainty quantification, and applications of machine learning in geological and medical domains. Key technical areas include Markov Chain Random Fields, seismic data integration, and spatial continuity analysis, with a focus on improving sustainability in mining operations and reservoir characterization.
Notable contributions include advancements in covariance table methodologies for automated spatial analysis and risk assessment frameworks for bauxite mining. His work bridges geological data interpretation, stochastic simulation techniques, and computational tools for resource optimization. Currently affiliated with Stanford's energy geoscience initiatives, his research emphasizes interdisciplinary applications of geostatistical models.
