Research Topics
The IMOM Lab develops artificial intelligence (AI) and data-driven methods to improve mine transport efficiency, reduce carbon emissions, and enable safe and intelligent mining operations.
Intelligent Mine Transport Systems
This research develops interpretable AI models to understand, predict, and optimize the performance of mining transport and material handling systems.
Sustainable and Low-Carbon Mining
This research develops intelligent solutions to reduce carbon emissions and improve the sustainability of mining operations and mineral processing.
Intelligent Monitoring and Safe Mining
This research develops intelligent monitoring tools and decision-support systems to enhance the safety and reliability of mining operations.
Geologic CO2 Storage Risk Management
This research develops data-driven and AI-based models to assess storage integrity, predict leakage risks, and support risk management for GCS systems.
Research Funding and Project Support
2026-2028: FRQ-Établissement de la relève professorale, Modélisation efficace en données pour la prévision et l'optimisation de la productivité des camions miniers
2026-2031: NSERC/RGPIN, Data-Driven and Transferable Modeling for Mine Truck Haulage: From Manned to Unmanned
2026: Mitacs Globalink, Apply Machine Learning to Sustainable Mining
2025-2026: NRC CBMI, Selective Precipitation Development for Next Generation Battery Materials
2024-2028: Université Laval, Faculté des sciences et de génie, Start-up Grant