Muhammad Nasir Amin 
- (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 (März 2024).
- (2024): Development and evaluation of basaltic volcanic ash based high performance concrete incorporating metakaolin, micro and nano-silica. In: Developments in the Built Environment, v. 17 (März 2024).
- (2024): Data-driven approaches for strength prediction of alkali-activated composites. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2024): Evaluating the Effect of Cement and ARG Fiber on the Mechanical and Microstructural Properties of Dune Sand. In: Advances in Civil Engineering, v. 2024 (Januar 2024).
- (2023): Artificial intelligence-based optimized models for predicting the slump and compressive strength of sustainable alkali-derived concrete. In: Construction and Building Materials, v. 409 (Dezember 2023).
- (2023): A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector. In: Construction and Building Materials, v. 407 (Dezember 2023).
- (2024): Evaluation of the mechanical properties, microstructure, and environmental impact of mortar incorporating metakaolin, micro and nano-silica. In: Case Studies in Construction Materials, v. 20 (Juli 2024).
- (2023): Evaluating the relevance of eggshell and glass powder for cement-based materials using machine learning and SHapley Additive exPlanations (SHAP) analysis. In: Case Studies in Construction Materials, v. 19 (Dezember 2023).
- (2023): An integral approach for testing and computational analysis of glass powder in cementitious composites. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques. In: Case Studies in Construction Materials, v. 18 (Juli 2023).
- (2023): Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations (SHAP). In: Construction and Building Materials, v. 377 (Mai 2023).
- (2023): A comprehensive GEP and MEP analysis of a cement-based concrete containing metakaolin. In: Structures, v. 53 (Juli 2023).
- (2023): Evaluating mechanical, microstructural and durability performance of seawater sea sand concrete modified with silica fume. In: Journal of Building Engineering, v. 72 (August 2023).
- (2023): Formulation of estimation models for the compressive strength of concrete mixed with nanosilica and carbon nanotubes. In: Developments in the Built Environment, v. 13 (März 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): Prediction model for rice husk ash concrete using AI approach: Boosting and bagging algorithms. In: Structures, v. 50 (April 2023).
- (2023): Performance characteristics of cementitious composites modified with silica fume: A systematic review. In: Case Studies in Construction Materials, v. 18 (Juli 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): Hybrid ANN models for durability of GFRP rebars in alkaline concrete environment using three swarm-based optimization algorithms. In: Construction and Building Materials, v. 352 (Oktober 2022).
- (2022): Potential use of waste eggshells in cement-based materials: A bibliographic analysis and review of the material properties. In: Construction and Building Materials, v. 344 (August 2022).
- (2022): Mechanical and microstructure performance and global warming potential of blended concrete containing rice husk ash and silica fume. In: Construction and Building Materials, v. 346 (September 2022).
- (2021): Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete. 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): Effective use of micro-silica extracted from rice husk ash for the production of high-performance and sustainable cement mortar. In: Construction and Building Materials, v. 258 (Oktober 2020).
- (2010): Improving test methods to measure early age autogenous shrinkage in concrete based on air cooling. In: The IES Journal Part A: Civil & Structural Engineering, v. 3, n. 4 (November 2010).
- (2017): Influence of Fineness of Recycled Glass Waste and Slag on Compressive Strength of Sulphate Resisting Cement Mortars. In: The Open Construction and Building Technology Journal, v. 11, n. 1 (Dezember 2017).
- (2012): Estimation of temperature effects on autogenous shrinkage of concrete by a new prediction model. In: Construction and Building Materials, v. 35 (Oktober 2012).
- (2013): Application of a thermal stress device for the prediction of stresses due to hydration heat in mass concrete structure. In: Construction and Building Materials, v. 45 (August 2013).
- (2017): Influence of fineness of volcanic ash and its blends with quarry dust and slag on compressive strength of mortar under different curing temperatures. In: Construction and Building Materials, v. 154 (November 2017).
- (2010): Assessment of cracking in concrete due to hydration heat and autogenous shrinkage. In: International Journal of Structural Engineering, v. 1, n. 2 ( 2010).
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