About

I’m an Assistant Professor at the Faculty of Engineering and Sciences at Universidad Adolfo Ibáñez. I completed my Ph.D. in 2022 at the The Robert M. Buchan Department of Mining, Queen’s University, advised by Julian M. Ortiz. I’m currently working on projects related to mineral resource estimation, predictive geometallurgy, mineral exploration and predictive geomechanics.

Education

PhD in Mining Engineering

2022

Queen's University

BSc in Engineering with Major in Mining and Extractive Metallurgy

2015

Universidad de Chile

Selected Publications

Dual Random Fields and Their Application to Mineral Potential Mapping

Mathematical Geosciences
2025
doi.org/10.1007/s11004-025-10195-4

+ Abstract

This paper introduces the concept of dual random fields and explores their application in mineral potential mapping. We develop a novel statistical framework that leverages dual random fields to improve the accuracy and reliability of mineral resource predictions.

A Riemannian Tool for Clustering of Geo-Spatial Multivariate Data

with Julian M Ortiz

Mathematical Geosciences
2024
/doi.org/10.1007/s11004-023-10085-7

+ Abstract

This paper introduces a Riemannian tool for clustering geo-spatial multivariate data. By leveraging Riemannian geometry, we propose a novel approach to enhance the clustering of complex geological datasets.

Multivariate simulation using a locally varying coregionalization model

with Julian M Ortiz

Computers & Geosciences
2024
doi.org/10.1016/j.cageo.2024.105781

+ Abstract

This paper presents a novel approach to multivariate simulation using a locally varying coregionalization model, which allows for more accurate and flexible modeling of complex geological phenomena.

Uncertainty and value: Optimising geometallurgical performance along the mining value chain

with Julian M Ortiz, Sebastian Avalos, Oy Leuangthong, Nasser Madani, Max Frenzel

Elements
2023
doi.org/10.2138/gselements.19.6.377

+ Abstract

This paper presents a comprehensive framework for optimizing geometallurgical performance across the mining value chain. By integrating uncertainty quantification and value optimization techniques, we demonstrate how to enhance decision-making processes in mining operations.

My courses

Orebody Modeling and Resource Estimation

A comprehensive course covering resource estimation, geostatistics, sampling preparation theory and quality assurance techniques, and categorizing mineral resources according to their uncertainty. Includes hands-on exercises with Python and real-world case studies.

Duration: 16 weeks | Credits: 3 | Level: Undergraduate | Term: Winter 2025

Resource Estimation Geostatistics Sampling Preparation Quality Assurance Uncertainty Analysis