Jean-Philippe Paiement

Jean-Philippe is a seasoned geostatistician with a strong background in structural, geological, and geochemical modeling and interpretation. His expertise extends to artificial intelligence, non-linear interpolation, and simulation techniques. Throughout his career, Jean-Philippe has developed innovative workflows and approaches to minimize interpretational risks associated with geological data. With a wealth of experience in mineral resource estimation, he has successfully applied his skills to diverse geological environments worldwide, covering precious metals, base metals, and industrial minerals. In 2016, Jean-Philippe made a groundbreaking contribution to the field by pioneering the application of Machine Learning to mineral exploration. His achievements were recognized when he won the Integra GoldRush challenge, showcasing the potential of machine learning in mineral deposit targeting. Since then, Jean-Philippe has remained at the forefront of advancing the application of machine learning to address geological and geophysical challenges. He combines his profound geological knowledge with both supervised learning and deep learning techniques, contributing significantly to the ongoing evolution of the field.