Yaser Gamil 
- (2024): A scientometrics review of conventional and soft computing methods in the slope stability analysis. In: Frontiers in Built Environment, v. 10 (February 2024).
- (2024): Assessment of the Environmental Impacts of Utilizing Coal Ashes and OPC for Soil Stabilization Applications: Leachate Analysis in Response to Rainfall Interaction. In: Case Studies in Construction Materials, v. 21 (December 2024).
- (2024): Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Efficient numerical simulations on the forest barrier for seismic wave attenuation: engineering safe constructions. In: Frontiers in Built Environment, v. 10 (February 2024).
- (2024): Forecasting maximum formwork pressure for self-compacting concrete using ARX-Laguerre machine learning model. In: Developments in the Built Environment, v. 18 (April 2024).
- (2024): Comparing the efficacy of GEP and MEP algorithms in predicting concrete strength incorporating waste eggshell and waste glass powder. In: Developments in the Built Environment, v. 17 (March 2024).
- (2024): Estimating compressive strength of concrete containing rice husk ash using interpretable machine learning-based models. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Data-driven approaches for strength prediction of alkali-activated composites. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Influence of supply chain management on the sustainable construction industry in Algeria. In: Frontiers in Built Environment, v. 10 (February 2024).
- (2024): Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): oMachine Learning Based Prediction Models for Spilt Tensile Strength of Fiber reinforced Recycled Aggregate Concrete. In: Case Studies in Construction Materials, v. 20 (July 2024).
- (2024): Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete. In: Developments in the Built Environment, v. 17 (March 2024).
- (2023): Experimental and environmental investigations of the impacts of wood sawdust on the performance of reinforced concrete composite beams. In: Case Studies in Construction Materials, v. 19 (December 2023).
- (2023): Prediction of compressive strength of two-stage (preplaced aggregate) concrete using gene expression programming and random forest. In: Case Studies in Construction Materials, v. 19 (December 2023).
- (2023): An empirical investigation of automation technology as material waste mitigation measure at Johor construction sites. In: Frontiers in Built Environment, v. 9 (February 2023).
- (2023): Thermal curing effects on alkali-activated treated soils with palm oil fuel ash. In: Case Studies in Construction Materials, v. 19 (December 2023).
- (2023): Optimisation of compressive strength of foamed concrete with a novel Aspergillus iizukae EAN605 fungus. In: Case Studies in Construction Materials, v. 19 (December 2023).
- (2023): Formwork pressure prediction in cast-in-place self-compacting concrete using deep learning. In: Automation in Construction, v. 151 (July 2023).
- (2023): Experimental based assessment of formwork pressure theoretical design models for self-compacting concrete. In: Journal of Building Engineering, v. 68 (June 2023).
- (2023): Machine learning in concrete technology: A review of current researches, trends, and applications. In: Frontiers in Built Environment, v. 9 (February 2023).
- (2022): Digital Transformation of Concrete Technology—A Review. In: Frontiers in Built Environment, v. 8 (February 2022).
- (2020): Exploring the failure factors of Yemen construction industry using PLS-SEM approach. In: Asian Journal of Civil Engineering, v. 21, n. 6 (June 2020).
- (2018): Application of Scheffe's Theory to Develop Mathematical Prediction Model to Predict UCS for Hybrid Containing Organic Soil and POFA-OPC Additives. In: Civil Engineering and Architecture, v. 6, n. 2 (March 2018).
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