Alireza Rahai | Civil Engineering | Best Researcher Award

Prof. Dr. Alireza Rahai | Civil Engineering | Best Researcher Award

Prof. Dr. Alireza Rahai, Department of Civil and Environmental Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran

Prof. Dr. Alireza Rahai is a distinguished Professor of Civil and Environmental Engineering at Amirkabir University of Technology, specializing in Structural and Earthquake Engineering ๐Ÿ—๏ธ๐ŸŒ. With an h-index of 24 and over 2,000 citations on Scopus ๐Ÿ“Š, he has made impactful contributions to infrastructure resilience, bridge engineering, and advanced composite materials. He has supervised numerous PhD and MSc theses, shaping future engineers through cutting-edge research and innovation ๐ŸŽ“๐Ÿ”ฌ. His work emphasizes seismic performance, health monitoring, and structural optimization, making him a prominent figure in civil engineering research globally

Publication Profile

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๐Ÿ›๏ธ Academic Employment

Prof. Dr. Alireza Rahai is a distinguished faculty member at Amirkabir University of Technology, located in Tehran, Iran ๐Ÿ‡ฎ๐Ÿ‡ท. He has dedicated a significant portion of his academic career to this prestigious institution, contributing as a professor, mentor, and researcher in the field of civil and structural engineering. His involvement at Amirkabir University has been instrumental in advancing both undergraduate and postgraduate education, fostering innovation in structural mechanics, and leading impactful research projects. His longstanding commitment reflects his dedication to academic excellence and engineering development in Iran and beyond.

๐Ÿ“š Supervision Highlights

Prof. Dr. Alireza Rahai has played a pivotal role in mentoring over 75 MSc and several PhD theses in structural and civil engineering. His supervision covers diverse topics such as FRP-confined concrete, composite shear walls, bridge performance, damage detection, health monitoring, and progressive collapse assessment. With a focus on innovation and real-world applications, his students have investigated modern construction materials, seismic resilience, and infrastructure durability. His recent guidance includes theses on prestressed concrete bridges, cyclic loading on steel structures, and structural health monitoring, showcasing his commitment to advancing engineering through research and mentorship.

๐Ÿ”ฌ Research Focus

Prof. Dr. Alireza Rahai’s research primarily focuses on structural engineering, with emphasis on structural health monitoring, finite element modeling, damage detection, and reinforced concrete behavior under various loading conditions. His work integrates advanced methods like artificial neural networks ๐Ÿค–, fuzzy logic, and genetic programming ๐Ÿงฌ to predict bond strength, damage, and service life of concrete structures. He also explores CFRP strengthening techniques, composite shear walls, and nonlinear behavior of structural elements. His interdisciplinary approach bridges civil engineering, materials science, and computational mechanics for safer and smarter infrastructure.

Publication Top Notes

๐Ÿ“˜ A structural damage detection method using static noisy data โ€“ 210 citations (2005)ย 
๐Ÿ“˜ Structural model updating using frequency response function and quasi-linear sensitivity equation โ€“ 182 citations (2009)ย 
๐Ÿ“˜ Prediction of bond strength using ANN and fuzzy logic โ€“ 148 citations (2012)ย 
๐Ÿ“˜ Evaluation of composite shear wall behavior under cyclic loadings โ€“ 136 citations (2009)ย 
๐Ÿ“˜ Experimental study of RC columns strengthened with CFRP under eccentric loading โ€“ 116 citations (2010)ย 
๐Ÿ“˜ Finite element model updating using transfer function data โ€“ 110 citations (2010)ย 
๐Ÿ“˜ Damage assessment using incomplete measured mode shapes โ€“ 102 citations (2007)ย 
๐Ÿ“˜ ANN & GP for bond strength prediction of GFRP bars โ€“ 96 citations (2015)ย 
๐Ÿ“˜ Investigation on RC columns with CFRP under axial & biaxial loading โ€“ 79 citations (2014)ย 
๐Ÿ“˜ Bond behavior in self-compacting concrete โ€“ 75 citations (2014)ย 
๐Ÿ“˜ Damage diagnosis using natural frequencies and sensitivity equation โ€“ 74 citations (2013)