Dr Mohamed Tharwat

Dr. Elnabwy's research is multidisciplinary, spanning construction management, infrastructure engineering and environmental systems. His research interests focus on applied, data-driven engineering approaches, particularly the integration of artificial intelligence, digital construction technologies, and sustainability frameworks to enhance construction and infrastructure performance and resilience. His main research areas are:

• Artificial Intelligence Applications in Construction and Infrastructure Management
• Circular Economy and Construction Waste Management
• Smart Infrastructure and Structural Health Monitoring
• Infrastructure Resilience to Climate Change
• Building Information Modeling (BIM) and Digital Construction

• Please visit the Pure Research Information Portal for further information
• Coastal Road Resilience in Nile Delta, Egypt: A Comprehensive Multihazard Risk Assessment, Sahlo, D., Elbeltagi, E., El-Badawy, S., Motawa, I., Elnabwy, M. 1 Feb 2026, In: Natural Hazards Review
• Integrated Ensemble Learning for Enhanced Accuracy in Satellite-Derived Bathymetry of Shallow Coastal Zones, Elnabwy, M., Kaloop, M., Ahmad, F., El-Diasty, M., Hu, J., Samui, P., ElGharbawi, T., Zarzoura, F. 1 Jan 2026, In: Journal of the Indian Society of Remote Sensing
• Modeling regional mean sea level based on climate measurements using a stacked ensemble approach, Elnabwy, M., Kaloop, M., Elbeltagi, E., Hu, J. 19 Feb 2026, In: Environmental Monitoring and Assessment
• An integrated ISM-MICMAC approach to identify and prioritize civil engineering-related hazards: a case study in Egypt, Elkholy, A., Elshikh, M., Elaidi, A., Elnabwy, M. 2 Jul 2025, In: Construction Innovation
• An integrated machine learning approach for evaluating critical success factors influencing project portfolio management adoption in the construction industry, Elnabwy, M., Khalaf, D., Mlybari, E., Elbeltagi, E. 25 Nov 2025, In: Engineering, Construction and Architectural Management
• Conceptual prediction of harbor sedimentation quantities using AI approaches to support integrated coastal structures management, Elnabwy, M., Elbeltagi, E., Banna, M., Elsheikh, M., Motawa, I., Hu, J., Kaloop, M. 1 Feb 2025, In: Journal of Ocean Engineering and Science
• Fuzzy AHP Approach for Enhancing Excavation Support System Selection in Building Projects: Balancing Safety and Cost-Effectiveness, Wefki, H., Elbeltagi, E., Elgamal, A., Alturki, M., Alkharisi, M., Elnabwy, M. 6 May 2025, In: Buildings
• Identifying Root Causes and Sustainable Solutions for Reducing Construction Waste Using Social Network Analysis, Salah, M., Elbeltagi, E., Almoshaogeh, M., Alharbi, F., Elnabwy, M. 24 Aug 2025, In: Sustainability
• An integrated deep learning approach for modeling dissolved oxygen concentration at coastal inlets based on hydro-climatic parameters, Elnabwy, M., Alshahri, A., El-Gamal, A. 1 Sep 2024, In: Journal of Environmental Management
• Critical Success Factors for the Widespread Adoption of Virtual Alternative Dispute Resolution (VADR) in the Construction Industry: A Structural Equation Modeling Analysis, Salem, M., Al-Sabah, R., Elnabwy, M., Elbeltagi, E., Tantawy, M. 22 Sep 2024, In: Buildings