Roghanchi, Schafrik, Moradi, Agioutantis, Siddique and Wilson receive grant to implement courses on artificial intelligence in the mining industry

UK Pigman College of Engineering researchers in the Department of Mining Engineering Pedram Roghanchi, Zach Agioutantis, Ali Moradi and Steven Schafrik, Muhammad Abu Bakar Siddique in the Department of Computer Science and Sarah Wilson in the Department of Chemical and Materials Engineering have received a nearly $442,000 grant from the National Science Foundation for their project, “IGE Track 1: Integrating Artificial Intelligence Technologies into Mining Education.” 

The three-year grant aims to implement a specialized series of courses focusing on the applications of artificial intelligence (AI) in the mining industry. With the mining industry experiencing unprecedented growth in the use of AI in mine operations, the proposed courses aim to bridge the gap between industry demand and skilled workforce supply by equipping graduating students with AI skills tailored to mining operations.

This proposal aims to implement a specialized series of courses focusing on the applications of artificial intelligence (AI) in the mining industry. With the mining industry experiencing unprecedented growth in the use of AI in mine operations, the proposed courses aim to bridge the gap between industry demand and skilled workforce supply by equipping graduate students with AI skills tailored to mining operations.

A new course (intro to AI) will be developed while two existing courses (mine automation course, and mine planning and optimization) will be adapted to encompass diverse facets of AI applications in mining operations. This will be achieved by employing a thorough research methodology involving collaboration with industry and academic partners. The curriculum will be pilot tested and evaluated to ensure its alignment with industry demands and emerging trends. The dissemination of educational outcomes will include knowledge sharing and collaboration within the mining education community, advancing a sustainable and competitive industry.

This proposal will focus on three courses: (1) Artificial Intelligence for mining industry (new course): Introduction to AI in mining; data collection and preprocessing; predictive analytics for mining; safety and risk management; engineering ethics in AI era; generative AI and large language. (2) Automation in the mining industry (modified course): Fundamental ethernet network and configuration; programming human-machine interface; machine control; process control; sensors. (3) Mine planning and optimization (modified course): Digital twin for mining applications; virtual reality/augmented reality; neural network and deep learning; optimization algorithms.