Waqas Ahmad

Employment

• COMSATS University Islamabad Lecturer
  2020 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (69)

• Correction: Yuan et al. Machine Learning Prediction Models to Evaluate the Strength of Recycled Aggregate Concrete. Materials 2022, 15, 2823
  Materials 2025 DOI: 10.3390/ma18235288
  +Save
• A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector
  Construction and Building Materials 2023 DOI: 10.1016/j.conbuildmat.2023.133485
  +Save
• A soft-computing-based modeling approach for predicting acid resistance of waste-derived cementitious composites
  Construction and Building Materials 2023 DOI: 10.1016/j.conbuildmat.2023.133540
  +Save
• Evaluating the relevance of eggshell and glass powder for cement-based materials using machine learning and SHapley Additive exPlanations (SHAP) analysis
  Case Studies in Construction Materials 2023 DOI: 10.1016/j.cscm.2023.e02278
  +Save
• Investigating the feasibility of genetic algorithms in predicting the properties of eco-friendly alkali-based concrete
  Construction and Building Materials 2023 DOI: 10.1016/j.conbuildmat.2023.134101
  +Save
• Predictive modelling for the acid resistance of cement-based composites modified with eggshell and glass waste for sustainable and resilient building materials
  Journal of Building Engineering 2023 DOI: 10.1016/j.jobe.2023.107325
  +Save
• Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques
  Case Studies in Construction Materials 2023 DOI: 10.1016/j.cscm.2023.e02102
  +Save
• Performance characteristics of cementitious composites modified with silica fume: A systematic review
  Case Studies in Construction Materials 2023 DOI: 10.1016/j.cscm.2022.e01753
  +Save
• Sustainable strategy of eggshell waste usage in cementitious composites: An integral testing and computational study for compressive behavior in aggressive environment
  Construction and Building Materials 2023 DOI: 10.1016/j.conbuildmat.2023.131536
  +Save
• Testing and modeling methods to experiment the flexural performance of cement mortar modified with eggshell powder
  Case Studies in Construction Materials 2023 DOI: 10.1016/j.cscm.2022.e01759
  +Save
• Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods
  Heliyon 2023 DOI: 10.1016/j.heliyon.2023.e16288
  +Save
• Predicting the crack width of the engineered cementitious materials via standard machine learning algorithms
  Journal of Materials Research and Technology 2023 DOI: 10.1016/j.jmrt.2023.04.209
  +Save
• Evaluating the compressive strength of glass powder-based cement mortar subjected to the acidic environment using testing and modeling approaches
  PLOS ONE 2023 DOI: 10.1371/journal.pone.0284761
  +Save
• Investigating the feasibility of using waste eggshells in cement-based materials for sustainable construction
  Journal of Materials Research and Technology 2023 DOI: 10.1016/j.jmrt.2023.02.057
  +Save
• Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar
  PLOS ONE 2023 DOI: 10.1371/journal.pone.0280761
  +Save
• Development of the New Prediction Models for the Compressive Strength of Nanomodified Concrete Using Novel Machine Learning Techniques
  Sohaib Nazar, Jian Yang, Waqas Ahmad +3 more
  Buildings 2022 DOI: 10.3390/buildings12122160
  +Save
• Self-healing concrete: A scientometric analysis-based review of the research development and scientific mapping
  Case Studies in Construction Materials 2022 DOI: 10.1016/j.cscm.2022.e01521
  +Save
• Sustainable use of waste eggshells in cementitious materials: An experimental and modeling-based study
  Case Studies in Construction Materials 2022 DOI: 10.1016/j.cscm.2022.e01620
  +Save
• Knowledge Mapping of the Literature on Fiber-Reinforced Geopolymers: A Scientometric Review
  Polymers 2022 DOI: 10.3390/polym14225008
  +Save
• Application of Soft-Computing Methods to Evaluate the Compressive Strength of Self-Compacting Concrete
  Materials 2022 DOI: 10.3390/ma15217800
  +Save