People

Farzad Kaviani Hamedani

Thesis Topic

Multi-Scale Morphology-Informed Constitutive Models using AI-Derived Correlations.

Farzad’s thesis investigates how multiscale morphological characteristics of granular materials influence their static and dynamic mechanical properties. The study involves an extensive micro-mechanical characterization of natural and synthetic materials. Various macro-scale mechanical properties are also determined using advanced testing methods such as stress path triaxial and true triaxial tests. The research will then  use Artificial Intelligence approach to incorporate multiscale morphological data into constitutive models for improved material behavior prediction.

About

Farzad Kaviani Hamedani is an experienced geotechnical engineer with a strong academic background, holding a Master’s degree in Geotechnical Engineering from Amirkabir University of Technology. His expertise spans experimental investigations, soil anisotropy, and constitutive modeling, with a focus on the behavior of soils under different stress conditions. He has contributed to international dam engineering projects and research, including the design and manufacturing of advanced soil testing apparatus. Farzad has published several papers in leading journals and presented at key geotechnical conferences, earning recognition for his work on fabric evolution and shear wave velocity measurements.

Supervisors

Associate Professor Arman Khoshghalb and Professor Nasser Khalili

 


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