Publications

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Productivity Pressure and Risk Perception Among a Multinational Construction Workforce in Saudi Arabia

Buildings | 2026

DOI: https://doi.org/10.3390/buildings16040774

Prediction of Compressive Strength for Recycled Rubber Aggregate Concrete Using Hybrid Machine-Learning Algorithms

International Journal of Concrete Structures and Materials | Vol. 20 | Issue 1 | 2026

DOI: https://doi.org/10.1186/s40069-026-00887-4

Prediction of mechanical strength and performance of alkali-activated binders concrete using optimized machine learning with partial dependence plot

Structures | Vol. 84 | Issue 2026 | 2026

DOI: https://doi.org/10.1016/j.istruc.2025.110896

Prediction of mechanical strength and performance of alkali-activated binders concrete using optimized machine learning with partial dependence plot

Structures | Vol. 84 | 2026

DOI: https://doi.org/10.1016/j.istruc.2025.110896

Predicting the mechanical performance of industrial waste incorporated sustainable concrete using hybrid machine learning modeling and parametric analyses

Scientific Reports | Vol. 15 | Issue 26330 | 2025

DOI: https://doi.org/10.1038/s41598-025-11601-x

Predicting the mechanical performance of industrial waste incorporated sustainable concrete using hybrid machine learning modeling and parametric analyses

SCIENTIFIC REPORTS | Vol. 15 | Issue 1 | 2025

DOI: https://doi.org/10.1038/s41598-025-11601-x

Physical properties of recycled concrete powder and waste tyre fibre reinforced concrete

Proceedings of the Institution of Civil Engineers - Engineering Sustainability | Vol. 70 | Issue 24 | 2025

DOI: https://doi.org/10.1680/jensu.24.00079

Physical properties of recycled concrete powder and waste tyre fibre reinforced concrete

Engineering Sustainability | Vol. 12 | Issue 11 | 2024

DOI: https://doi.org/10.1680/jensu.24.00079

Predicting the compressive strength of fiber-reinforced self-consolidating concrete using a hybrid machine learning approach

Innovative Infrastructure Solutions | Vol. 9 | 2024

DOI: https://doi.org/10.1007/s41062-024-01751-8

Predicting the compressive strength of fiber‑reinforced recycled aggregate concrete: A machine‑learning modeling with SHAP analysis

Asian Journal of Civil Engineering | 2024

DOI: https://doi.org/10.1007/s42107-024-01183-w

Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate

Engineering applications of artificial intelligence | 2023

DOI: https://doi.org/10.1016/j.engappai.2023.106958

Prediction of Offshore Wave at East Coast of Malaysia—A Comparative Study

Electronics | 2022

DOI: https://doi.org/10.3390/electronics11162527

Predicting the Lateral Load Carrying Capacity of Reinforced Concrete Rectangular Columns: Gene Expression Programming

Materials | 2022

DOI: https://doi.org/10.3390/ma15072673

Performance Characteristics of Asphalt Mixtures with Industrial Waste/By-Product Materials as Mineral Fillers under Static and Dynamic Loading

Road Materials and Pavement Design, Talyor & Francis, Impact Factor 3.79 Quartile (Civil Engineering- Q1, Web of Science) | Vol. 35 | Issue Pages 335-357 | | 2022

DOI: https://doi.org/10.1080/14680629.2020.1826347

Performance of Manufactured and Recycled Steel Fibres in Restraining Concrete Plastic Shrinkage Cracks

Materials | Vol. 16 | Issue 2 | 2022

DOI: https://doi.org/10.3390/ma16020713

Prospect of biobased antiviral face mask to limit the coronavirus outbreak

Environmental Research (Elsevier) | 2020

DOI: https://doi.org/10.1016/j.envres.2020.110294

Performance of isolated and folded footings

Journal of Computational Design and Engineering | 2016

DOI: https://doi.org/10.1016/j.jcde.2016.09.001