Ömer Ekmekcioğlu 
- (2024): Predicting Cost Impacts of Nonconformances in Construction Projects Using Interpretable Machine Learning. In: Journal of Construction Engineering and Management, v. 150, n. 1 (Januar 2024).
- (2023): Developing a Hybrid Fuzzy Decision-Making Model for Sustainable Circular Contractor Selection. In: Journal of Construction Engineering and Management, v. 149, n. 10 (Oktober 2023).
- : Critical success factors for construction industry transition to circular economy: developing countries’ perspectives. In: Engineering, Construction and Architectural Management.
- (2023): On the identification of most appropriate green roof types for urbanized cities using multi-tier decision analysis: A case study of Istanbul, Turkey. In: Sustainable Cities and Society, v. 96 (September 2023).
- (2023): Developing a National Data-Driven Construction Safety Management Framework with Interpretable Fatal Accident Prediction. In: Journal of Construction Engineering and Management, v. 149, n. 4 (April 2023).
- (2022): Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment. In: Sustainable Cities and Society, v. 87 (Dezember 2022).
- (2022): Prediction of construction accident outcomes based on an imbalanced dataset through integrated resampling techniques and machine learning methods. In: Engineering, Construction and Architectural Management, v. 30, n. 9 (Juni 2022).
- (2022): Multi-criteria analysis of barriers to building information modeling (BIM) adoption for SMEs in New Zealand construction industry. In: Engineering, Construction and Architectural Management, v. 30, n. 9 (Juni 2022).
- (2022): Towards flood risk mapping based on multi-tiered decision making in a densely urbanized metropolitan city of Istanbul. In: Sustainable Cities and Society, v. 80 (Mai 2022).
- (2022): Accident prediction in construction using hybrid wavelet-machine learning. In: Automation in Construction, v. 133 (Januar 2022).
- (2021): Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers. In: Automation in Construction, v. 131 (November 2021).
- (2020): Tree-based nonlinear ensemble technique to predict energy dissipation in stepped spillways. In: European Journal of Environmental and Civil Engineering, v. 26, n. 8 (September 2020).
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