معرفی
Hirad Daneshvar is a Contract Instructor at Carleton University's School of Civil Engineering within the Faculty of Engineering and Design. His research focuses on structural engineering, particularly the application of machine learning to predict material behavior and structural performance under extreme conditions such as high temperatures, impact loads, and corrosion. He specializes in advanced materials like fiber-reinforced cementitious matrix (FRCM) and recycled plastic-based concrete, leveraging numerical modeling and AI-driven methodologies.
His work bridges theoretical and experimental approaches, addressing challenges in reinforced concrete (RC) structures, composite shear walls, and fire performance of steel-concrete systems. Key topics include strengthening techniques, thermal degradation effects, and seismic behavior analysis. Recent studies emphasize predictive modeling using artificial intelligence and stochastic finite element methods.
Publications span from 2013 to 2025, highlighting consistent contributions to structural mechanics, material science, and computational engineering. His research trends reflect a strong emphasis on integrating machine learning with traditional engineering practices to enhance infrastructure resilience and sustainability.
