Engr. Maaz Khan

Maaz Khan is a Civil Engineering researcher specializing in sustainable construction materials, waste valorization, environmental remediation, and data-driven material performance assessment. His research integrates experimental investigation, advanced material characterization, life-cycle assessment (LCA), and machine learning to develop sustainable and high-performance construction materials. He has research experience in sustainable cementitious composites, photocatalytic materials, biochar-based materials, and 3D concrete printing.

Education

M.Sc. in Civil Engineering
Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan 

2024-2026.

B.Sc. in Civil Engineering
University of Engineering and Technology (UET), Peshawar, Pakistan

2020-2024

Research Work

Maaz Khan has worked as a Research Assistant in the Department of Civil Engineering at GIKI, focusing on sustainable construction materials and biochar-based cementitious composites. His research activities include material characterization using UV–Vis, XRD, FTIR, and SEM, mechanical and durability testing, and experimental data analysis. He has also gained practical research experience in 3D Concrete Printing (3DCP), particularly in the development and evaluation of printable cementitious mixtures and their fresh-state properties.

His research further combines experimental methods with machine learning, computer vision, and LCA to evaluate and predict the performance and environmental sustainability of construction materials.

Research Interests

• Sustainable Construction Materials: Eco-friendly, high-performance materials.
• Waste Valorization: Converting waste/biomass into construction materials.
• Environmental Remediation: Materials for pollution control and water treatment.
• Photocatalytic Materials: Self-cleaning, pollution-degrading cement systems.
• Life-Cycle Assessment (LCA): Environmental impact evaluation of construction materials.
• Data-Driven Engineering: ML-based prediction of material properties.
• 3D Concrete Printing: Sustainable printable cementitious materials.

Publications

1. Khan, M., Javed, M. F., & Asif, U. (2026). Performance Evaluation of Sustainable Concrete Incorporating Mineral Fillers: Experimental Insights and Predictive Modeling Using Advanced Machine Learning.
   DOI: https://doi.org/10.1007/s41062-026-02802-y
2. Khan, M., Javed, M. F., Alabduljabbar, H., & Ahmad, F. (2025). Explainable Machine Learning and Ensemble Models for Predicting Fresh Properties of Self-Consolidating Concrete.
   DOI: https://doi.org/10.1038/s41598-025-21305-x
3. Khan, M., Asif, U., Rind, T. A., & Panhyar, M. F. (2025). Formulation of Penetration Resistance, Softening Point and Viscosity of Plastic Modified Bitumen Using Genetic Expression Programming.
   DOI: https://doi.org/10.64615/fjes.1.1.2025.3
4. Suliman, M., Khan, M., Rind, T. A., Ullah, F., Khan, S., & Mahmood, Z. Prediction of Soil Shear Strength Using Hybrid Machine Learning Approaches for Performance and Interpretability Analysis.
   DOI: https://doi.org/10.1038/s41598-026-57764-z
5. Rind, T. A., Khan, M. A., Ahmed, S., Ahmed, S., & Khan, M. Development of Gene Expression Programming–Based Rutting Prediction Model for Smart Pavement Management Using LTPP Data.
   DOI: https://doi.org/10.1155/adce/8657453

 Conference Papers & Presentations

• Khan, M., Riaz, N., & Javed, M. F. (2025). Assessment of Self-Cleaning Performance and Photocatalytic Activity of Photocatalytic Concrete. 5th NUST Flagship International Conference on Water, Energy and Environment for Sustainability (IC-WEES).
• Khan, M., et al. (2025). A Comprehensive Review of Photocatalytic Concrete Using Conventional and Scientometric Approaches. International Conference on Green Sustainable Technology and Management (ICGSTM2025).
• Khan, M., et al. (2025). Integrating Road Pricing into Urban Traffic Management Systems on Saddar Road, Rawalpindi, Pakistan.

Google Scholar: https://scholar.google.com/citations?user=lV0XLKUAAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Maaz-Khan-63?ev=hdr_xprf

Email: maazzkhan692@gmail.com