Shamayleh, AbdulrahimAlsuwaidi, Mariam2025-07-082025-07-082025-0435.232-2025.18https://hdl.handle.net/11073/26193A Master of Science thesis in Engineering Systems Management by Mariam Alsuwaidi entitled, “Analysis of Fat-track Projects in the Public Sector in the United Arab Emirates”, submitted in April 2025. Thesis advisor is Dr. Abdulrahim Shamayleh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The United Arab Emirates (UAE) has emerged as a global leader in large-scale public infrastructure projects, driven by an ambitious national development agenda. To meet pressing deadlines and accommodate growing demands, many governmental projects adopt a fast-tracking approach. Although this method shortens delivery timelines, it also brings about significant challenges, including cost overruns, quality risks, coordination difficulties, and heightened safety concerns. This study investigates the practical application of fast-track project management in the UAE public sector using a mixed-methods approach. It incorporates literature review, in-depth regional case studies, a structured survey of UAE-based project managers, and advanced analysis using Bayesian Belief Networks to uncover relationships between key success factors.The results reveal that frequent changes in project requirements, limited adoption of digital tools, and gaps in stakeholder communication are major barriers to success. Technologies like Building Information Modeling (BIM), Artificial Intelligence (AI), Machine Learing (ML), and Internet of Things (IoT) remain underutilized despite their potential to improve project performance. Recommendations include developing structured fast-track frameworks, promoting technology integration, enhancing contingency planning, and utilizing post-project evaluations. The findings offer practical guidance for improving fast-track execution and provide a foundation for future research into sustainable and technology-driven project delivery.en-USFast-trackingBayesian Belief networksPublic infrastructureProject managementThesis