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.

Farzad Safi Jahanshahi – Transportation Engineering – Best Researcher Award

Published on by Civil Engineering

Mr. Farzad Safi Jahanshahi | Transportation Engineering | Best Researcher Award

Researcher- Engineer | Sirjan University of Technology | Iran

Mr. Farzad Safi Jahanshahi has built a strong research foundation in civil engineering with a focus on geotechnical and pavement materials. His work emphasizes soil and road layer stabilization, asphalt performance, and sustainable construction practices using industrial by-products such as mine tailings and overburden soil. He has contributed to the development of predictive models for unconfined compressive strength, resilient modulus, and pavement roughness by applying advanced statistical methods, machine learning, and hybrid ensemble learning techniques. Farzad Safi Jahanshahi’s studies highlight the mechanical and durability characteristics of cement-treated soils, magnetite and hematite tailings, and dune sands stabilized with geopolymers, aiming to improve long-term road performance and environmental sustainability. His collaborative works extend into intelligent modeling of geotechnical properties, application of gene expression programming, and development of mechanistic empirical pavement design approaches. Publications cover topics such as RCPT modeling of concrete, bond strength in reinforced concrete systems, and liquefaction-induced displacement prediction, showing broad interdisciplinary applications. He has presented at several national conferences on asphalt, soil stabilization, and pavement technologies, reinforcing practical knowledge transfer. His research experience includes field testing at Golgohar Mine, integrating laboratory findings with real-world construction challenges. Alongside academic contributions, he has professional experience in road construction supervision, micropile installation, and laboratory testing of soils and asphalts. He also contributes as an instructor, teaching geometric road design and related courses, linking research with education. Technical expertise spans MATLAB, Civil 3D, AutoCAD, and laboratory test methods essential for pavement and soil characterization. Farzad Safi Jahanshahi’s scholarly contributions reflect an integration of experimental studies with artificial intelligence, advancing sustainable pavement design and infrastructure engineering. His achievements demonstrate a balance of theoretical modeling, applied experimentation, and industry practice, providing valuable insights for the future of sustainable civil engineering. 53 Citations 11 Documents 5 h-index.

Profile: Scopus | ORCID | Linked In 
Featured Publications:

Ghavami, S., Naseri, H., & Safi Jahanshahi, F. (2025). Enhanced prediction and uncertainty modeling of pavement roughness using machine learning and conformal prediction. Infrastructures, 10(7), 166.

Nouri, Y., Ghanizadeh, A. R., Safi Jahanshahi, F., & Fakharian, P. (2025). Data-driven prediction of axial compression capacity of GFRP-reinforced concrete column using soft computing methods. Journal of Building Engineering, 111831.

Safi Jahanshahi, F., & Ghanizadeh, A. R. (2025). Machine learning approaches for resilient modulus modeling of cement-stabilized magnetite and hematite iron ore tailings. Scientific Reports, 15, 86978.

Fakharian, P., Nouri, Y., Ghanizadeh, A. R., Safi Jahanshahi, F., Naderpour, H., & Kheyroddin, A. (2024). Bond strength prediction of externally bonded reinforcement on groove method (EBROG) using MARS-POA. Composite Structures, 118532.

Safi Jahanshahi, F., & Ghanizadeh, A. R. (2024). Compressive strength, durability, and resilient modulus of cement-treated magnetite and hematite iron ore tailings as pavement material. Construction and Building Materials, 138076.

Elise Mansour – Pavement engineering – Best Researcher Award

Published on by Civil Engineering

Elise Mansour - Pavement engineering - Best Researcher Award

Louisiana State university - United States

AUTHOR PROFILE

SCOPUS

RESEARCHER IN PROPOSALS COMPLIANCE AND INFRASTRUCTURE

Elise Mansour is currently building large language models to ensure compliance against Louisiana's Infrastructure Program Manual. Under the guidance of Dr. Roy Haggerty at Louisiana State University, she employs advanced machine-learning techniques to verify the adherence of project proposals to required standards, significantly contributing to the Resilient Communities Infrastructure Program Policy of Louisiana.

EXPERT IN AIRFIELD PAVEMENT MANAGEMENT

Her work with the Transportation Consortium of South-Central States (Tran-SET) involves creating an advanced airfield pavement management framework. Elise extracted and analyzed pavement condition data from FAA PAVEAIR for over 89 airports, leveraging machine-learning algorithms to develop predictive models that enhance airfield maintenance and management practices.

PIONEER IN ASPHALT CONCRETE OVERLAYS PERFORMANCE

Elise has conducted extensive research on the long-term field performance of asphalt concrete overlays across Southern states. By developing a machine-learning framework and a VBA tool, she has modernized the Southern Pavement Management System, providing state agencies with enhanced tools for pavement maintenance and decision-making.

INNOVATOR IN PAVEMENT MARKINGS DETERIORATION ANALYSIS

Her contributions to the Tran-SET initiative also include the modeling and analysis of restriping waterborne paints and thermoplastic pavement markings. Elise collected and analyzed data on pavement markings deterioration, developing predictive models and tools to assist the Louisiana Department of Transportation in scheduling timely maintenance repairs.

SPECIALIST IN MECHANISTIC MODELING OF AIRPORT PAVEMENTS

At the University of Nevada, Elise has been involved in the advanced modeling, design, and analysis of instrumented airport pavement sections. Her work at the National Airport Pavement Test Facility includes conducting backcalculation of layer moduli, analyzing dynamic sensor responses, and utilizing software like MODULUS 6.0 and ELMOD6 for comprehensive pavement evaluation.

AWARDED SCHOLAR AND LEADER

Elise's academic excellence has been recognized through numerous awards, including the Outstanding Master Scholarship Award by the Honor Society Phi Kappa Phi and the LSU Study Abroad Scholarship. Her leadership roles include serving as the Student Vice-President of the LSU Honor Society of Phi Kappa Phi and being a student leader in the Association of Asphalt Paving Technologists (AAPT) LSU Chapter.

DEDICATED EDUCATOR

Elise is also committed to education, serving as a lecturer for courses in Construction Jobsite Management and Ethics and Leadership in Construction Management at the Lebanese American University. Additionally, she has been a teaching assistant for various construction management courses at Louisiana State University, demonstrating her dedication to nurturing the next generation of engineers and construction managers.

NOTABLE PUBLICATION

Machine-Learning-Based Framework for Prediction of the Long-Term Field Performance of Asphalt Concrete Overlays in a Hot and Humid Climate
Authors: E. Mansour, M.R. Mousa, H. Dhasmana, M. Hassan
Year: 2023
Journal: Transportation Research Record, 2677(10), pp. 375–385

Modeling of Restriping of Waterborne Paints Using Transverse Test Deck Data in Hot and Humid Climate
Authors: E. Mansour, M.R. Mousa, M. Hassan
Year: 2023
Journal: Transportation Research Record, 2677(7), pp. 509–519

Prediction of Long-Term Field Performance of Asphalt Concrete Overlays in a Southern State Using Supervised Machine-Learning
Authors: E. Mansour, M.R. Mousa, H. Dhasmana, M. Hassan
Year: 2023
Conference: Airfield and Highway Pavements 2023: Design, Construction, Condition Evaluation, and Management of Pavements - Selected Papers from the International Airfield and Highway Pavements Conference 2023, 1, pp. 416–428

Prediction of Performance of Asphalt Overlays Using Decision Tree Algorithm
Authors: E. Mansour, M.R. Mousa, M. Hassan
Year: 2022
Conference: Tran-SET 2022 - Proceedings of the Tran-SET Conference 2022, pp. 16–24

Service Life Assessment of Thermoplastic Pavement Markings in Region 6
Authors: E. Mansour, I. Elnaml, M.R. Mousa, M. Hassan, O. Omar
Year: 2021
Conference: Tran-SET 2021 - Proceedings of the Tran-SET Conference 2021, pp. 101–109