Ali Khalvandi

/ALI K/

Grad Research Asst Fellowship, Faculty of Engineering - Mechanical Engineering Dept

Pronouns: He/Him

Personal Website: https://scholar.google.com/citations?view_op=list_works&hl=en&hl=en&user=rw9BBgQAAAAJ

Contact Overview Publications

Contact

Grad Research Asst Fellowship, Faculty of Engineering - Mechanical Engineering Dept

Email: khalvand@ualberta.ca

Overview

Area of Study / Keywords

Molecular Dynamics Simulation Supervised Learning Biomedicine Computational Mechanics Porous Biomaterials

Featured Publications

A supervised learning-assisted multi-scale study for thermal and mechanical behavior of porous Silica

Ali Khalvandi, Saeed Saber-Samandari, Mohammad Mohammadi Aghdam

Heliyon. 2024 April; 10.1016/j.heliyon.2024.e28995

Prediction and optimization of 3D-printed sandwich beams with chiral cores

Saeed Kamarian, Ali Khalvandi, Ehsan Heidarizadi, Saeed Saber-Samandari, Jung-il Song

International Journal of Mechanical Sciences. 2024 January; 10.1016/j.ijmecsci.2023.108747

Data-driven supervised machine learning to predict the compressive response of porous PVA/Gelatin hydrogels and in-vitro assessments: Employing design of experiments

Ali Khalvandi, Lobat Tayebi, Saeed Kamarian, Saeed Saber-Samandari, Jung-il Song

International Journal of Biological Macromolecules. 2023 December; 10.1016/j.ijbiomac.2023.126906

Synergistic effects of egg shell powder and halloysite clay nanotubes on the thermal and mechanical properties of abacá/polypropylene composites

Reza Barbaz-Isfahani, Ali Khalvandi, Thanh Mai Nguyen Tran, Saeed Kamarian, Saeed Saber-Samandari, Jung-il Song

Industrial Crops and Products. 2023 December; 10.1016/j.indcrop.2023.117498

Fabrication, experimental study, and 2-D finite element computational homogenization of bone scaffolds under uniaxial and biaxial compressive loadings

Ali Khalvandi, Mohammad Mohammadi Aghdam, Saeed Saber-Samandari

Proceedings of the Institution of Mechanical Engineers, Part N: Journal of Nanomaterials, Nanoengineering and Nanosystems. 2022 September; 10.1177/23977914221082900

Application of artificial neural networks to predict Young's moduli of cartilage scaffolds: An in-vitro and micromechanical study

Biomaterials Advances. 2022 January; 10.1016/j.bioadv.2022.212768

Micromechanical Modeling of Gelatin-Based Nano-Composite Bone Scaffolds

2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME). 2020 November; 10.1109/icbme51989.2020.9319423

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