Mohamed T. Elnabwy 
- : An integrated machine learning approach for evaluating critical success factors influencing project portfolio management adoption in the construction industry. In: Engineering, Construction and Architectural Management.
- (2024): Critical Success Factors for the Widespread Adoption of Virtual Alternative Dispute Resolution (VADR) in the Construction Industry: A Structural Equation Modeling Analysis. In: Buildings, v. 14, n. 9 (25 August 2024).
- (2024): Leveraging convolutional neural networks for efficient classification of heavy construction equipment. In: Asian Journal of Civil Engineering, v. 25, n. 8 (24 September 2024).
- (2024): Social network analysis for identifying the significant drivers of off-site construction adoption in Egypt. In: Built Environment Project and Asset Management, v. 14, n. 4 (3 July 2024).
- (2024): Harbor Sedimentation Management Using Numerical Modeling and Exploratory Data Analysis. In: Advances in Civil Engineering, v. 2024 (January 2024).
- (2024): Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study. In: Construction and Building Materials, v. 436 (July 2024).
- (2015): Bridge Monitoring with Wavelet Principal Component and Spectrum Analysis Based on GPS Measurements: Case Study of the Mansoura Bridge in Egypt. In: Journal of Performance of Constructed Facilities (ASCE), v. 29, n. 3 (June 2015).
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