Dr. Zahid Ur Rehman is a distinguished researcher and academic in the field of Mining Engineering, specializing in rock mechanics, tunnel design, and numerical modeling for geotechnical analysis. His scholarly contributions emphasize the study of rock mass behavior under varied loading conditions, focusing on the stability and safety of underground structures in complex geological environments. Through extensive research on the Lowari Tunnel and Kohat Tunnel projects in Pakistan, Zahid Ur Rehman has developed advanced modeling techniques using FEM and DEM approaches to predict deformation, stress distribution, and support system performance. His work integrates theoretical and empirical methods to optimize tunnel support systems, enhance slope stability, and mitigate risks associated with rock bursts and collapses. Beyond tunnel engineering, his studies extend to dimension stone mining, ore reserve estimation, explosive engineering, and sustainable mineral extraction. His collaborative publications explore artificial intelligence applications for rock mass characterization, risk assessment in mining operations, and the environmental management of mineral industries. Zahid Ur Rehman has supervised multiple undergraduate projects investigating geotechnical variability, squeezing potential, and predictive modeling in tunnel environments, demonstrating a commitment to fostering research innovation. His proficiency with tools such as RocLab, RS2, and Matlab strengthens his expertise in simulation and modeling for ground support design. Additionally, his involvement with the Society of Mining Engineers and Pakistan Engineering Council highlights active engagement in professional development and academic leadership. His academic output, including journal articles and a co-authored book chapter on slope engineering, contributes significantly to advancing mining and geotechnical sciences. Zahid Ur Rehman has 92 citations across 11 research documents with an h-index of 6, reflecting substantial influence and research impact in the mining engineering discipline.
Featured Publications
Jan, M. S., Hussain, S., Zahra, R. E., Emad, M. Z., Khan, N. M., Rehman, Z. U., Cao, K., Alarifi, S. S., Raza, S., Sherin, S., et al. (2023). Appraisal of different artificial intelligence techniques for the prediction of marble strength. Sustainability.
Hussain, S., Khan, N. M., Emad, M. Z., Naji, A. M., Cao, K., Gao, Q., Rehman, Z. U., Raza, S., Cui, R., Salman, M., et al. (2022). An appropriate model for the prediction of rock mass deformation modulus among various artificial intelligence models. Sustainability.
Gul, A., Shahzada, K., Alam, B., Badrashi, Y. I., Khan, S. W., Khan, F. A., Ali, A., & Rehman, Z. U. (2020). Experimental study on the structural behavior of cast in-situ hollow core concrete slabs. Civil Engineering Journal (Iran).
Hussian, S., Mohammad, N., Rehman, Z. U., Khan, N. M., Shahzada, K., Ali, S., Tahir, M., Raza, S., & Sherin, S. (2020). Review of the geological strength index (GSI) as an empirical classification and rock mass property estimation tool: Origination, modifications, applications, and limitations. Advances in Civil Engineering.
Tahir, M., Rehman, Z. U., Husain, S., Muhammad, N., Nazir, M., Sadiq, M., & Hussain, I. (2020). Up-gradation of black shale of Chimiari region of Pakistan by flotation scheme. Journal of Himalayan Earth Sciences.