Overview
Professor (Amir)Hossein Salahshoor came to Duke from Caltech, where he conducted his postdoctoral studies. Prior to that, and pursuant to his undergraduate studies at the University of Tehran, he obtained his Ph.D in Aerospace Engineering from Georgia Tech, along with an MS in Mathematics. His research interests broadly lie at the intersection of mechanics of materials and structures, computational and data science, biology, and applied mathematics, whereby focusing on developing data-driven and computational frameworks to predict, control, and engineer the behavior of complex material systems, he aims to address mechanistic challenges in sustainability and health.
Current Duke Appointments & Affiliations
Assistant Professor of Civil and Environmental Engineering
·
2023 - Present
Civil and Environmental Engineering,
Pratt School of Engineering
Assistant Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
·
2023 - Present
Thomas Lord Department of Mechanical Engineering and Materials Science,
Pratt School of Engineering
Faculty Network Member of the Duke Institute for Brain Sciences
·
2023 - Present
Duke Institute for Brain Sciences,
University Institutes and Centers
Recent Scholarly Works
A probabilistic framework for learning solution operators of deterministic high-frequency Helmholtz equations
Journal article Computer Methods in Applied Mechanics and Engineering · November 1, 2026 Deterministic neural operators perform well on many PDEs but can struggle with the approximation of high-frequency wave phenomena, where strong input-to-output sensitivity makes operator learning challenging, and spectral bias blurs oscillations. We argue ... Full text CiteData-driven material identification in heterogeneous viscoelastic media
Journal article Journal of the Mechanics and Physics of Solids · July 1, 2026 Full-field material characterization techniques are increasingly improving and new techniques are emerging, providing us altogether with unprecedented access to kinematic measurements. Extracting material properties from data has been a long quest, with th ... Full text CiteData-Driven-Design (D3) of multi-material systems: A novel framework and its application to viscoelastic metamaterials
Journal article International Journal of Solids and Structures · April 1, 2026 While multimaterial additive manufacturing enables finely programmed heterogeneity, there remains no robust and objective-driven framework to assign materials across complex architectures under practical constraints. We introduce Data-Driven-Design (D ... Full text CiteEducation
Georgia Institute of Technology ·
2018
Ph.D.