Alisson Silva | Construction Management | Best Researcher Award

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Mr. Alisson Silva | Construction Management | Best Researcher Award

Mr. Alisson Silva, Federal University of Bahia, Brazil

Mr. Alisson Silva is a dedicated researcher in the field of Construction Engineering, currently pursuing his Ph.D. at the Federal University of Bahia, Brazil, where he also earned his Master’s degree specializing in Building Construction and Materials. His research focuses on the application of drones, computer vision, and machine learning for automated inspection and quality control in civil infrastructure. With a solid academic background, including a B.Sc. in Building Construction and an MBA in Project Management, Alisson has significantly contributed to advancing smart construction technologies. He has authored numerous peer-reviewed journal articles and conference papers addressing topics such as facade inspection, YOLOv8-based damage detection, and BIM-integrated maintenance. Alisson is an active member of the Research Group in Construction Management and Technology (GETEC-UFBA) and collaborates with multidisciplinary teams across Brazil. His innovative work is recognized through publications in top-tier journals and global conferences, positioning him as a rising expert in intelligent construction systems

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Educational Background

Mr. Alisson Silva has built a strong academic foundation in Construction Engineering, currently pursuing a Ph.D. at the Federal University of Bahia, Brazil, with a concentration in Building Construction and Materials under the guidance of Professor Dayana Bastos Costa. He previously completed his M.Sc. from the same institution (2021–2023), focusing on the automation of construction failure recognition in façade execution using drones and machine learning, co-advised by Reymard Sávio Sampaio de Melo. Prior to his master’s, he earned an MBA in Project Management in 2020 from Alta Floresta Faculty, reflecting his keen interest in construction planning and leadership. His academic journey began with a B.Sc. in Building Construction (2015–2019), also at Alta Floresta Faculty, located in Mato Grosso, Brazil. This educational trajectory demonstrates a consistent focus on integrating advanced technologies with civil engineering practices, positioning him as a capable researcher and practitioner in the evolving field of intelligent construction systems.

Research Focus

Mr. Alisson Silva’s research primarily focuses on intelligent construction systems, with a particular emphasis on integrating digital technologies such as drones (UAS), computer vision, BIM, machine learning (including CNN and YOLO algorithms), and data augmentation for automated inspection and maintenance in civil engineering. His work is rooted in enhancing quality control, structural monitoring, and damage detection in building construction—especially façades, rooftops, and precast concrete elements. Through innovative methodologies, he contributes to automating the detection of anomalies, streamlining construction management, and supporting infrastructure maintenance in public and educational buildings. His scholarly contributions are aligned with the emerging domains of Construction 4.0, smart maintenance systems, and digital twins, making his research both cutting-edge and highly applicable to modern urban development. By combining artificial intelligence with traditional construction engineering principles, Mr. Silva is advancing the field toward sustainable, efficient, and technology-driven construction practices, particularly within the Brazilian and Latin American contexts.

Publication Top Notes

📘 Web platform for building roof maintenance inspection using UAS and artificial intelligence – Cited by: 12 | Year: 2025 📡🏗️🤖
📘 Análise do uso de tecnologias digitais para identificação automatizada de patologias em construções – Cited by: 8 | Year: 2022 🏚️💻🔍
📘 Modelo de aprendizado de máquina para inspeção automatizada de fachadas de paredes de concreto – Cited by: 6 | Year: 2023 🧱🤖🛠️
📘 Proposal for integrating drone images and BIM in educational public buildings to support maintenance management – Cited by: 3 | Year: 2024 🚁🏫📐
📘 Automated facade inspection: Application and challenge in using Artificial Intelligence for construction defect recognition – Cited by: 3 | Year: 2023 🏢🤖⚙️
📘 Método para reconhecimento automatizado de falhas construtivas na execução de fachadas com uso de drones e aprendizado de máquina – Cited by: 2 | Year: 2023 🚧🚁📊
📘 CNN-based model for automated anomaly recognition in facade execution to support Quality Management – Cited by: 1 | Year: 2025 🧠🏗️🔧
📘 Method of automated inspection for reinforcement cages of precast concrete elements – Cited by: 1 | Year: 2024 🧱🔎📸
📘 Colaboração BIM em software de projetos estruturais – Cited by: 1 | Year: 2023 📐💬🏗️
📘 Using digital technologies for automated identification of building pathologies: A literature review – Cited by: 1 | Year: 2022 📊🏚️📑
📘 Lições do uso de videogrametria para inspeções de qualidade em armaduras de pré-fabricados de concreto – Year: 2025 🏗️📷🔍
📘 Lessons from the use of videogrammetry for quality inspections of precast concrete reinforcement – Year: 2025 🏗️🧰🛰️
📘 Method for quality inspection during the execution of facades based on UAS images and Machine Learning algorithms – Year: 2025 🚁📋🧠
📘 Modelo baseado em CNN para reconhecimento automatizado de anomalias na execução de fachadas visando apoio à Gestão da Qualidade – Year: 2025 🤖🏢📉
📘 Computer Vision-based YOLO11 for automated damage assessment of public building roofs supporting maintenance management – Year: 2025 🧠🏫🛰️

Alireza Rahai | Civil Engineering | Best Researcher Award

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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 🏗️🌍. With an h-index of 24 and over 2,000 citations on Scopus 📊, 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 🎓🔬. 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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🏛️ Academic Employment

Prof. Dr. Alireza Rahai is a distinguished faculty member at Amirkabir University of Technology, located in Tehran, Iran 🇮🇷. 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.

📚 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.

🔬 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 🤖, fuzzy logic, and genetic programming 🧬 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

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

Fayiz Amin | Civil engineering | Young Scientist Award

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Mr. Fayiz Amin | Civil engineering | Young Scientist Award

Mr. Fayiz Amin, Univeristy of Alberta, Pakistan

Fayiz Amin is a passionate civil engineer based in Muscat, Oman, with expertise in structural design, modeling, and simulation. A graduate of the prestigious Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan, Fayiz combines practical site engineering experience with extensive academic research. He is currently working as a Junior Site Engineer at Shah Brothers & Co while actively publishing in reputed journals on topics such as CFRP strengthening and arch-shaped slabs. Fayiz is committed to sustainable and resilient infrastructure development and leverages advanced software tools and AI techniques in civil engineering applications.

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🎓 Education

Fayiz Amin earned his Bachelor of Science in Civil Engineering from GIKI (2018–2022), supported by the Chief Minister Khyber Pakhtunkhwa Merit-Based Scholarship. His thesis focused on improving load-carrying capacity of industrial slabs using arch-shaped geometry. Ranked 5th out of 39 students in his program, he was honored with the Dean’s Roll of Honor for academic excellence. He also attended Quaid-e-Azam College Swabi for higher secondary education, where he earned a talent-based scholarship and placed 3rd in his class with distinction (A1 grade, 86.21%). Fayiz actively participated in academic societies like ASCE and ICE during his studies.

🏢 Experience

Fayiz currently works as a Junior Site Engineer at Shah Brothers & Co, contributing to the construction of a four-story residential building, where he handles project design, data analysis, and risk assessments. He previously interned at the Irrigation Department Swabi and the Geotechnical Lab at GIKI, conducting tests such as UU and UC on sand-clay mixtures. Simultaneously, he pursued part-time research in modeling and simulation at GIKI. His hands-on and academic experiences allow him to bridge theory and practice effectively, leveraging software like ETABS, SAFE, and Revit for structural modeling, FEM analysis, and project management.

🏆 Awards and Honors

Fayiz Amin has earned multiple accolades, including the fully funded Chief Minister KPK Merit-Based Scholarship (PKR 3.2 million) for his undergraduate studies at GIKI. His final year project ranked among the top three groups at GIKI. He was also a recipient of a talent hunt scholarship during his intermediate studies. Fayiz received the Dean’s Honor Roll Certificate for academic excellence in Fall 2022. These honors reflect his academic brilliance, project innovation, and dedication to civil engineering, setting a foundation for his continuing research and professional journey in advanced structural systems and smart construction technologies.

🔬 Research Focus

Fayiz’s research revolves around experimental testing and finite element modeling of structural systems, especially in strengthening and retrofitting techniques using advanced materials such as CFRP, SMA, and ECC. He explores structural responses under extreme conditions—earthquakes, fires, blasts—and aims to improve resilience. He is also invested in integrating AI and machine learning into civil engineering problems, including construction automation. With 11 published articles (3 Q1, 2 Q2, 4 Q3, and 2 conference papers), his work reflects a blend of computational modeling, experimental validation, and interdisciplinary approaches for sustainable infrastructure solutions.

Publication Top Notes

📌 Seismic RC Beam-Column Retrofitting with Steel Haunches – Results in Engineering – 5 citations – 2024 📐🏗️
📌 CFRP-Strengthened Concrete Culverts vs. Corrosion – Infrastructures – 4 citations – 2024 💧🛠️
📌 Arch Action in Precast Slabs (Numerical + Experimental) – Results in Materials – 2 citations – 2024 🧱🔬
📌 BIM–IoT & Robots for Site Layout Printing – Buildings – 2 citations – 2023 🤖📊
📌 RC Deep Beams w/ Openings Strengthened by Metal Plates – 2 citations – Year not specified 🏗️🔩
📌 Seismic Retrofit of Steel Beam–Column Joints (CFRP & Bolts) – Engineering Reports – 1 citation – 2025 🛠️📎
📌 GFRP Pipes under Hoop Compression (FEM & Experimental) – EJCEA – 1 citation – 2024 ⚙️🔄
📌 Fatigue Strengthening of Asphalt Pavements via Tack Coat (FEM) – Engineering Proceedings – 1 citation – 2023 🛣️🧪
📌 Radial Compression of GFRP Pipes (Exp + FEM) – MMMED – 0 citations – 2025 🧵🧪
📌 Thin-Walled Sections Analysis via FEM – EJCEA – 0 citations – 2024 📏🧰
📌 Eco-Strengthening of RC Beams using ECC & Bamboo (GEP + ABAQUS) – SSRN – 0 citations – 2024 🌿🏗️💡