Dr. Asieh Hamidi, a CivMin postdoctoral fellow (PDF), is the recipient of a Women in Mining Canada 2025 Research Grant. WIM Canada supports graduate students conducting EDI-related research in the mining industry, as well as women conducting technical research in the mining industry.
Hamidi’s research is in the area of Tackling Uncertain and Unreliable Rock Engineering Data in Mining: Applications of AI and Bayesian Analysis. Her research is aimed at advancing the field of rock engineering in mining by establishing a foundation for integrating AI, machine learning (ML), and Bayesian methods into geotechnical decision-making.
Understanding rock behaviour for mining geotechnical engineering design generally begins by analyzing complex datasets obtained from various sources. Often these datasets are plagued by missing data, and may be unreliable. In this work she will use advanced data imputation to develop techniques to ‘fill the gaps’, and then apply ML schemes to develop reliable predictive models of key rock properties for engineering. AI-driven models allow us to uncover intricate relationships between rock properties, governing mechanisms, and engineering performance, and has great potential to lead to safer and more optimized mining designs. However, uncertainty remains a critical factor in predictions of factors such as rock mass behaviour and in-situ stress state, and this hampers decision-making for surface and underground rock engineering designs. To address this, she will apply Bayesian inference to augment datasets with expert knowledge in a robust probabilistic fashion.
Overall, her work will contribute to a systematic data analysis approach for evaluating rock engineering behaviour, ultimately leading to more informed, reliable, and safer mining operations and designs.
The award announcement came via a LinkedIn post by WIM Canada.