Assoc. Prof. Dr Odey Alshboul | Construction management | Best Researcher Award

Assoc. Prof. Dr, THE HASHEMITE UNIVERSITY, Jordan

Dr. Odey AlShboul is an Associate Professor and Department Head of Civil Engineering at The Hashemite University, Jordan. With a Ph.D. in Civil Engineering from the University of Central Florida (2019), he has extensive academic and professional experience in construction engineering and management. Dr. AlShboul’s career spans various academic roles, including research and teaching assistant positions at international universities. He is dedicated to enhancing the civil engineering field through leadership in education, research, and industry collaborations.

Professional Profile

Google Scholar

Strengths for the Award

1. Strong Educational Background: Dr. Odey AlShboul has a robust academic foundation, holding a Ph.D. in Civil Engineering with a focus on Construction Engineering and Management from the University of Central Florida, alongside multiple relevant master’s degrees from prestigious institutions. This background positions him well for research and teaching excellence.
2. Leadership and Management Experience: Dr. AlShboul is currently serving as the Civil Engineering Department Head at The Hashemite University, Jordan. His responsibilities include strategic direction, faculty management, ABET accreditation, and curriculum development. This leadership experience demonstrates his ability to guide academic and research teams, further enhancing his qualifications for a research-focused award.
3. Research Excellence: Dr. AlShboul has made significant contributions to the field, with several influential publications in journals such as Automation in Construction, Sustainability, and Construction and Building Materials. His work in machine learning applications for construction management, geopolymer concrete, and risk assessment in construction is groundbreaking. His published works are highly cited, with contributions to both theory and practical applications in construction engineering.
4. Innovative Use of Technology: His focus on machine learning, artificial intelligence, and predictive models for construction management and structural performance is notable. Dr. AlShboul’s work in applying these technologies to construction conflicts, cost prediction, and construction equipment residual value is a testament to his innovative approach.
5. Collaboration and Networking: He has demonstrated his ability to establish research collaborations with various institutions and industry partners, enhancing his research output and the impact of his work.

Areas for Improvement

1. Broadening Interdisciplinary Collaboration: While Dr. AlShboul has a strong foundation in civil engineering, particularly in construction management and machine learning, there is potential to expand his research into more interdisciplinary fields, such as sustainability, environmental impact, or smart infrastructure. This could further diversify the scope and reach of his work.
2. Grant Acquisition and Funding: Although Dr. AlShboul has experience managing departmental budgets and seeking funding, his record of securing research grants could be further enhanced. Increased focus on securing funding for innovative research could elevate his career and broaden the scope of his projects.
3. Industry Application: While his research is highly valuable to academia, further emphasis on translating his findings into industry practices could further strengthen the practical impact of his work. Increased collaboration with industry partners and government agencies might allow for greater real-world application of his research.

Education

Dr. AlShboul holds a Ph.D. in Civil Engineering (Construction Engineering and Management) from the University of Central Florida (2019). He also earned two M.S. degrees, one in Civil Engineering (Construction Engineering and Management) from the University of Central Florida (2018), and another in Civil Engineering (Structural) from Jordan University of Science and Technology (2014). His undergraduate degree in Civil Engineering is also from Jordan University of Science and Technology, obtained in 2012.

Experience

Dr. AlShboul’s professional experience includes roles as a Site Engineer and Assistant Project Manager in Jordan, where he managed project planning, budgeting, and scheduling. In academia, he has served as a teaching assistant, lecturer, and researcher in various prestigious institutions. At The Hashemite University, he is the Department Head, overseeing strategic direction, curriculum development, faculty management, and accreditation. He also provides consulting services in construction engineering.

Awards and Honors

Dr. AlShboul has received recognition for his significant contributions to construction engineering research, particularly in machine learning applications for construction management. His work has been cited extensively in academic journals. Additionally, his contributions to teaching, mentoring, and curriculum development have earned him awards and honors, highlighting his role as a thought leader in his field.

Research Focus

Dr. AlShboul’s research focuses on the intersection of construction engineering and machine learning, particularly in areas like construction equipment management, green building cost prediction, and structural optimization. He is deeply involved in using AI and data-driven approaches to enhance construction efficiency and sustainability. His recent studies explore forecasting residual values, predicting construction costs, and improving material performance.

Publication Top Notes

1. Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost regression 📊
2. Production of geopolymer concrete using natural pozzolan: A parametric study 🏗️
3. Extreme gradient boosting-based machine learning approach for green building cost prediction 🌱
4. Selection of heavy machinery for earthwork activities: A multi-objective optimization approach using a genetic algorithm 🛠️
5. Risk assessment model for optimal gain–pain share ratio in target cost contract for construction projects ⚖️
6. Evaluating the impact of external support on green building construction cost 🌍
7. Deep and machine learning approaches for forecasting the residual value of heavy construction equipment: A management decision support model 📉
8. Forecasting liquidated damages via machine learning-based modified regression models for highway construction projects 🛣️
9. Prediction liquidated damages via ensemble machine learning model: Towards sustainable highway construction projects 🔮
10. Machine learning algorithm for shear strength prediction of short links for steel buildings 🏗️

Conclusion

Dr. Odey AlShboul is an excellent candidate for the Best Researcher Award, based on his significant academic achievements, strong leadership, and impactful research contributions in construction engineering and management. His work demonstrates an innovative use of technology, particularly in machine learning, which sets him apart from many other researchers in the field. By focusing on expanding interdisciplinary collaborations and securing more industry partnerships, Dr. AlShboul could further amplify the practical significance and global reach of his work. With his proven track record and ongoing contributions to advancing construction technology, he is well-deserving of recognition through such an award.