Marco Antonio Cotrina Teatino

Editorial Board · Mining & AI

PhD in Science and Engineering · MSc in Mining Engineering

Research professor at the School of Mining Engineering of the National University of Trujillo (UNT), where he serves as a tenured faculty member and RENACYT Researcher – Level II.

He currently holds the position of Director of the Professional School of Mining Engineering, Editor-in-Chief of the scientific journal Journal of Advanced Mining Modeling, coordinating lead of the UNT–UNI cooperation agreement, coordinator of the emerging research group “Mine Design and Planning – DIPLAMIN”, and member of the research group “Geology, Mining, Metallurgy and Environment – GEOMETAMB-UNT”, in addition to serving as Chair of the Technical Committee for the Mining Engineering Curriculum.

• PhD in Science and Engineering – National University of Trujillo.
• MSc in Mining Engineering – University of Chile.
• Mining Engineer – National University of Trujillo (Peru).
• Bachelor’s Degree in Mining Engineering – National University of Trujillo.

His scientific activity focuses on geostatistics, mining modeling and planning, mining and mineral processing, as well as environmental and geological engineering applied to the extractive industry. He has complemented his academic training with specialized programs in risk analysis, mining economics and competitiveness, mineral markets, and applied statistics, primarily at the University of Chile.

He has a sustained record of scientific publications indexed in Scopus (Q1–Q4), addressing topics such as machine learning and deep learning techniques for mineral resource estimation, deposit classification, drilling and haulage optimization, fuel consumption in mining equipment, recovery of critical elements, and circular economy approaches applied to mine tailings and mining waste.

His current research interests include artificial intelligence applied to mining, evaluation and valorization of tailings, environmental geosciences, risk management and operational safety, as well as the development of analytical models to support decision-making under sustainability and environmental responsibility frameworks.