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.

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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.