ODEY HASAN FAROUQ ALSHBOUL

Odey Hasan Farouq Alshboul	Associate Professor
	Projects Management
Faculty of Engineering	Department of Civil Engineering
odey.shboul@hu.edu.jo	http://staff.hu.edu.jo/odey
ORCID ID : 272936663
Office No. :	EXT : 5234

C.V. Document file as PDF:

Ph.D.	University of Central Florida	The United States of America,2019
Master	Jordan University of Science and Technology	Jordan,2015
Bachelor	Jordan University of Science and Technology	Jordan,2012

•	Construction project management and engineering.
•	Construction contract design.
•	Risk management.
•	Risk Assessment
•	Automation in construction projects.
•	Comprehensive mathematical models using vast techniques. 
•	AI Applications in Construction Management and Engineering
•	Developing of Strategic Plans for Managing Infrastructure
•	Asset Inventory for Infrastructure Management Systems
•	Data Collection Methods to Manage Infrastructure Assets
•	Condition Assessment of Infrastructure Assets
•	Development of Performance Models
•	Forecasting Network Condition of Infrastructure Assets
•	Network Level Needs-Gap Analysis
•	Impact Scenarios Analysis
•	Prioritization of Treatment Needs for Budget Allocation
•	Quantifying Benefits for Trade-off Funding Allocation Analysis
•	Maintenance Strategies to Preserve Infrastructure Assets
•	Value Engineering
•	Life-Cycle Cost Analysis
•	Applications of Geographic Information Systems (GIS)
•	Structural Engineering Analysis
•	Machine learning techniques.
•	Stacking classifier processing.
•	Optimization methods and techniques.
•	New materials (Carbon-fiber–reinforced polymer, carbon-fibre–reinforced plastic or carbon-fibre–reinforced thermoplastic (CFRP, CRP, CFRTP).
•	Recent building materials applications for efficient and economical use.

 •	Al-Shboul, K. F., Almasabha, G., Shehadeh, A., & Alshboul, O. (2023). Exploring the efficacy of machine learning models for predicting soil radon exhalation rates. Stochastic Environmental Research and Risk Assessment, 37(11), 4307-4321. https://doi.org/10.1007/s00477-023-02509-x 
•	Shehadeh, A., Alshboul, O., & Almasabha, G. (2024). Slope displacement detection in construction: An automated management algorithm for disaster prevention. Expert Systems with Applications, 237, 121505. https://doi.org/https://doi.org/10.1016/j.eswa.2023.121505
•	Alshboul, O., Almasabha, G., Al-Shboul, K. F., & Shehadeh, A. (2023). A comparative study of shear strength prediction models for SFRC deep beams without stirrups using Machine learning algorithms. Structures, 55, 97-111. https://doi.org/https://doi.org/10.1016/j.istruc.2023.06.026
•	Almasabha, G., Al-Shboul, K. F., Shehadeh, A., & Alshboul, O. (2023). Machine learning-based models for predicting the shear strength of synthetic fiber reinforced concrete beams without stirrups. Structures, 52, 299-311. https://doi.org/https://doi.org/10.1016/j.istruc.2023.03.170 Alshboul, O., A. Shehadeh, and O. Hamedat, Governmental Investment Impacts on the Construction Sector Considering the Liquidity Trap. Journal of Management in Engineering, 2022. 38(2): p. 04021099 DOI: 10.1061/(ASCE)ME.1943-5479.0001003.
•	Shehadeh, A., O. Alshboul, and O. Hamedat, Risk Assessment Model for Optimal Gain-Pain Share Ratio in Target Cost Contract for Construction Projects. Journal of Construction Engineering and Management, 2022. 148(2): p. 04021197 DOI: 10.1061/(ASCE)CO.1943-7862.0002222.
•	Shehadeh, A., O. Alshboul, R.E. Al Mamlook, and O. Hamedat, Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression. Automation in Construction, 2021. 129: p. 103827 DOI: https://doi.org/10.1016/j.autcon.2021.103827.
•	Alshboul, O., A. Shehadeh, M. Al-Kasasbeh, R.E. Al Mamlook, N. Halalsheh, and M. Alkasasbeh, Deep and machine learning approaches for forecasting the residual value of heavy construction equipment: a management decision support model. Engineering, Construction and Architectural Management, 2021. DOI: 10.1108/ECAM-08-2020-0614.
•	Rami H. Haddad, Odey Alshbuol, Production of geopolymer concrete using natural pozzolan: A parametric study, Construction and Building Materials, 114 (1), 2016, 699-707. https://doi.org/10.1016/j.conbuildmat.2016.04.011
•	Shehadeh, A., O. Alshboul, O. Tatari, M.A. Alzubaidi, and A. Hamed El-Sayed Salama, Selection of heavy machinery for earthwork activities: A multi-objective optimization approach using a genetic algorithm. Alexandria Engineering Journal, 2022. 61(10): p. 7555-7569 DOI: https://doi.org/10.1016/j.aej.2022.01.010.
•	Alshboul, O., A. Shehadeh, and O. Hamedat, Development of integrated asset management model for highway facilities based on risk evaluation. International Journal of Construction Management, 2021: p. 1-10 DOI: 10.1080/15623599.2021.1972204.
•	Shehadeh, A., O. Alshboul, and O. Hamedat, A Gaussian mixture model evaluation of construction companies’ business acceptance capabilities in performing construction and maintenance activities during COVID-19 pandemic. International Journal of Management Science and Engineering Management, 2021: p. 1-11 DOI: 10.1080/17509653.2021.1991851.
•	Alshboul, O., A. Shehadeh, O. Tatari, G. Almasabha, and E. Saleh, Multiobjective and multivariable optimization for earthmoving equipment. Journal of Facilities Management, 2022. DOI: 10.1108/JFM-10-2021-0129.
•	Maha Alkasasbeh, Hosam Olimat, Osama Abudayyeh, Odey Alshboul, & Ali Shehadeh (2021): DEA-based multi-criteria selection model and framework for design-build contracting, International Journal of Management Science and Engineering Management, DOI: 10.1080/17509653.2021.1982422.
•	Alshboul, O., M.A. Alzubaidi, R.E.A. Mamlook, G. Almasabha, A.S. Almuflih, and A. Shehadeh, Forecasting Liquidated Damages via Machine Learning-Based Modified Regression Models for Highway Construction Projects. Sustainability, 2022. 14(10): p. 5835; https://doi.org/10.3390/su14105835.
•	Alshboul, O., A. Shehadeh, G. Almasabha, and A.S. Almuflih, Extreme Gradient Boosting-Based Machine Learning Approach for Green Building Cost Prediction. Sustainability, 2022. 14(11): p. 6651 DOI: https://doi.org/10.3390/su14116651.
•	Alshboul, O., G. Almasabha, A. Shehadeh, O. Al Hattamleh, and A.S. Almuflih, Optimization of the Structural Performance of Buried Reinforced Concrete Pipelines in Cohesionless Soils. Materials, 2022. 15(12): p. 405; https://doi.org/10.3390/ma15124051. 
•	Alshboul, O., G. Almasabha, A. Shehadeh, R.E.A. Mamlook, A.S. Almuflih, and N. Almakayeel, Machine Learning-Based Model for Predicting the Shear Strength of Slender Reinforced Concrete Beams without Stirrups. Buildings, 2022. 12(8): p. 1166; https://doi.org/10.3390/buildings12081166.
•	Alshboul, O., A. Shehadeh, R.E.A. Mamlook, G. Almasabha, A.S. Almuflih, and S.Y. Alghamdi, Prediction Liquidated Damages via Ensemble Machine Learning Model: Towards Sustainable Highway Construction Projects. Sustainability, 2022. 14(15): p. 9303; https://doi.org/10.3390/su14159303.
•	Alshboul, O., A. Shehadeh, G. Almasabha, R.E.A. Mamlook, and A.S. Almuflih, Evaluating the Impact of External Support on Green Building Construction Cost: A Hybrid Mathematical and Machine Learning Prediction Approach. Buildings, 2022. 12(8): p. 1256; https://doi.org/10.3390/buildings12081256.
•	Almasabha, G., O. Alshboul, A. Shehadeh, and A.S. Almuflih, Machine Learning Algorithm for Shear Strength Prediction of Short Links for Steel Buildings. Buildings, 2022. 12(6): p. 775; https://doi.org/10.3390/buildings12060775. 
•	Halalsheh, N., O. Alshboul, A. Shehadeh, R.E. Al Mamlook, A. Al-Othman, M. Tawalbeh, A. Saeed Almuflih, and C. Papelis, Breakthrough Curves Prediction of Selenite Adsorption on Chemically Modified Zeolite Using Boosted Decision Tree Algorithms for Water Treatment Applications. Water, 2022. 14(16): p. 2519; https://doi.org/10.3390/w14162519.
•	I. M. Almadi, A., R.E. Al Mamlook, I. Ullah, O. Alshboul, N. Bandara, and A. Shehadeh, Vehicle collisions analysis on highways based on multi-user driving simulator and multinomial logistic regression model on US highways in Michigan. International Journal of Crashworthiness, 2022: p. 1-16 DOI: 10.1080/13588265.2022.2130608
•	Shehadeh A, Alshboul O, Alsmadi D. REINFORCING THE PROCESS OF TOTAL QUALITY MANAGEMENT OF STUDENTS LEARNING OUTCOMES ASSESSMENT: AN ADVANCED DIPLOMA COMPLEMENTS FOR ENGINEERING EDUCATIONAL PROGRAMS. Abstracts & Proceedings of ADVED 2022- 8th International Conference on Advances in Education, 10-12 October 2022. https://doi.org/10.47696/adved.202241
•	Alshboul O, Shehadeh A. MODERNIZATION OF CAPSTONE DESIGN COURSES FOR ENGINEERING STUDENTS: ECHOES OF SURVEY OUTCOMES ANALYSIS. Abstracts & Proceedings of ADVED 2022- 8th International Conference on Advances in Education, 10-12 October 2022. DOI: https://doi.org/10.47696/adved.202242

 •	Academic Advisor for the American Society for Engineering Education (ASEE) students' chapter in the Faculty of Engineering at The Hashemite University. 
•	Member of the Jordan Engineers Association (JEA), Jordan
•	Mentor of Hult Prize at The Hashemite University
•	Mentor of Hult Prize at Yarmouk University

•	British Embassy | Newton-Khalidi Science Talks: International Day of Water.
•	Erasmus+ Capacity-building in Higher Education - 2022 Call for proposals - 02/12/2021
•	European Union Side Events at COP26 December 2021
•	International Conference on Green Building, Civil Engineering, and Smart City
•	ITALIAN DESIGN DAY (IDD) 2022 edition at YU
•	Jordan Ireland Bilateral Networking Webinar
•	The Middle East and Africa Green Building Congress 2022
•	SDGs Workshop: SDG Progress: On-Campus and Beyond
•	UNAI SDGs Workshop "International Justice and Goal 16: Beyond the Targets" on 8/9/2022
•	MatSQ Workshop on 14/9/2022

ODEY HASAN FAROUQ ALSHBOUL

ODEY HASAN FAROUQ ALSHBOUL

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