Applying Machine Learning Methods to Sustainable Mining

This project aims to support the development of low-carbon materials for mining applications by using data-driven methods to better understand and predict material durability. The research focuses on analyzing existing experimental data to estimate carbonation depth in alternative concrete made from mine tailings, which can reduce the use of traditional cement and lower greenhouse gas emissions. By combining engineering knowledge with machine learning tools, the project will help improve confidence in the use of sustainable construction materials in the mining sector. The internship will strengthen research collaboration between Université Laval and an international partner institution, while providing valuable training opportunities for a highly motivated undergraduate student in applied data analysis and sustainable engineering.

Faculty Supervisor:

Chengkai Fan

Student:

Partner:

Universidade Tecnológica Federal do Paraná

Discipline:

Engineering

Sector:

Education

University:

Université Laval

Program: