Muhammad Faisal Javed 
- (2024): Carbon dioxide emission evaluation of biochar based vegetation concrete for ecological restoration projects. In: Case Studies in Construction Materials, v. 21 (Dezember 2024).
- (2024): Innovative hybrid machine learning models for estimating the compressive strength of copper mine tailings concrete. In: Case Studies in Construction Materials, v. 21 (Dezember 2024).
- (2024): Data-driven evolutionary programming for evaluating the mechanical properties of concrete containing plastic waste. In: Case Studies in Construction Materials, v. 21 (Dezember 2024).
- (2024): Predicting natural vibration period of concrete frame structures having masonry infill using machine learning techniques. In: Journal of Building Engineering, v. 96 (November 2024).
- (2024): Indirect estimation of resilient modulus (Mr) of subgrade soil: Gene expression programming vs multi expression programming. In: Structures, v. 66 (August 2024).
- (2024): Evolutionary Algorithms for Strength Prediction of Geopolymer Concrete. In: Buildings, v. 14, n. 5 (24 April 2024).
- (2024): Predicting the mechanical properties of plastic concrete: An optimization method by using genetic programming and ensemble learners. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2024): Machine Learning Approaches for Predicting Shielding Effectiveness of Carbon Fiber-Reinforced Mortars.. In: Case Studies in Construction Materials, v. 20 (Juli 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 (Juli 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 (März 2024).
- (2023): Comparative study of genetic programming-based algorithms for predicting the compressive strength of concrete at elevated temperature. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): Forecasting the self-healing capacity of engineered cementitious composites using bagging regressor and stacking regressor. In: Structures, v. 54 (August 2023).
- (2023): Forecasting compressive strength and electrical resistivity of graphite based nano-composites using novel artificial intelligence techniques. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): Plastic concrete mechanical properties prediction based on experimental data. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): Bim-based energy analysis and optimization using insight 360 (case study). In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): An evolutionary machine learning-based model to estimate the rheological parameters of fresh concrete. In: Structures, v. 48 (Februar 2023).
- (2022): Machine learning based computational approach for crack width detection of self-healing concrete. In: Case Studies in Construction Materials, v. 17 (Dezember 2022).
- (2022): Development of the New Prediction Models for the Compressive Strength of Nanomodified Concrete Using Novel Machine Learning Techniques. In: Buildings, v. 12, n. 12 (1 Dezember 2022).
- (2021): Mechanical properties of novel PVA rubberized concrete. In: Structural Concrete, v. 23, n. 6 (Dezember 2021).
- (2022): Predicting Marshall Flow and Marshall Stability of Asphalt Pavements Using Multi Expression Programming. In: Buildings, v. 12, n. 3 (8 März 2022).
- (2022): Concrete filled double steel tube columns incorporating UPVC pipes under uniaxial compressive load at ambient and elevated temperature. In: Case Studies in Construction Materials, v. 16 (Juni 2022).
- (2022): Machine learning modeling integrating experimental analysis for predicting the properties of sugarcane bagasse ash concrete. In: Construction and Building Materials, v. 314 (Januar 2022).
- (2021): Geopolymer concrete as sustainable material: A state of the art review. In: Construction and Building Materials, v. 306 (November 2021).
- (2021): Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete. In: Advances in Civil Engineering, v. 2021 (Januar 2021).
- (2021): Compressive Strength of Fly-Ash-Based Geopolymer Concrete by Gene Expression Programming and Random Forest. In: Advances in Civil Engineering, v. 2021 (Januar 2021).
- (2020): Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete. In: Advances in Civil Engineering, v. 2020 (Januar 2020).
- (2020): Prediction model for compressive arch action capacity of RC frame structures under column removal scenario using gene expression programming. In: Structures, v. 25 (Juni 2020).
- (2017): FE modelling of the flexural behaviour of square and rectangular steel tubes filled with normal and high strength concrete. In: Thin-Walled Structures, v. 119 (Oktober 2017).
- (2018): Flexural behaviour of steel hollow sections filled with concrete that contains OPBC as coarse aggregate. In: Journal of Constructional Steel Research, v. 148 (September 2018).
- (2018): Assessment of Rheological and Piezoresistive Properties of Graphene based Cement Composites. In: International Journal of Concrete Structures and Materials, v. 12, n. 1 (Oktober 2018).
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