Zahid Ur Rehman | Geotechnical Engineering | Best Researcher Award

Published on by Civil Engineering

Dr. Zahid Ur Rehman | Geotechnical Engineering | Best Researcher Award

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.

Profile: Scopus | ORCID
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.

Ramin Vafaei Poursorkhabi | Geotechnical Engineering | Best Researcher Award

Published on by Civil Engineering

Assoc. Prof. Dr. Ramin Vafaei Poursorkhabi | Geotechnical Engineering | Best Researcher Award

Associate Professor | Islamic Azad University | Iran

Assoc. Prof. Dr. Ramin Vafaei Poursorkhabi has built a strong research profile focusing on civil engineering, geotechnical engineering, structural analysis, soil improvement techniques, and the application of artificial intelligence in solving complex engineering challenges. His work spans across diverse areas such as the stabilization of soils through innovative methods like geopolymerization, evaluation of dispersive clay properties, monitoring and analysis of dam structures, and the use of metaheuristic algorithms for seismic response reduction and subsurface modeling. He has contributed significantly to advancements in hydraulic conductivity estimation, environmental optimization in road construction, and the reinforcement of geotechnical stability through geogrid applications. His studies also include offshore platform reliability, wave–structure interaction, and improvements in rubble mound breakwater resistance, showcasing an interdisciplinary approach that connects geotechnical, structural, and coastal engineering. By integrating clustering techniques, fuzzy logic, wavelet-based artificial neural networks, and hybrid optimization methods, he has introduced innovative models to enhance predictive accuracy and engineering design efficiency. Several of his publications highlight practical applications through case studies of large infrastructure projects, including dams, offshore platforms, and municipal roads, providing a blend of theoretical modeling and applied research. Additionally, his collaboration with scholars across multiple institutions has fostered a multidisciplinary approach to engineering problems, producing solutions that are both technically sound and environmentally conscious. The consistent use of computational intelligence tools demonstrates his commitment to bridging traditional engineering with modern machine learning techniques, aiming to optimize performance, reduce risk, and ensure structural safety. His publications in international journals and conference proceedings reflect not only academic contribution but also practical impact in real-world infrastructure development. This research track record establishes Ramin Vafaei Poursorkhabi as an impactful contributor in advancing the fields of geotechnical and structural engineering with strong integration of intelligent systems. 105 Citations 31 Documents 6 h-index View.

Profile: Scopus | ORCID | Research Gate 
Featured Publications:

Using the clustering method to find the final environmental parameters coefficients in road construction projects. (2025). Scientific Reports.

Experimental investigation of a special chemical additive for improving the geotechnical properties of dispersive clay soils. (2025). Results in Engineering.

Estimation of hydraulic conductivity using gradation information through Larsen fuzzy logic hybrid wavelet artificial neural network and combined artificial intelligence models. (2025). Discover Applied Sciences.