Our research group maintains active collaborations with a network of strategic industry partners and governmental institutions to ensure the real-world relevance, scalability, and national alignment of our machine learning research—particularly in the application of Gene Expression Programming (GEP) to civil engineering challenges. These partnerships bridge the gap between academic research and practical implementation, strengthening the societal and industrial impact of our work.
We work in close partnership with the Structural Section of the Ministry of Public Works and Housing to address critical infrastructure needs across Jordan. This collaboration includes:
Joint Research Projects: Collaborative efforts on evaluating and predicting the performance of existing infrastructure such as bridges, highways, and public buildings under various load and environmental conditions.
Structural Health Monitoring and Assessment: Use of GEP models to support early detection of structural deficiencies and degradation, contributing to preventive maintenance strategies.
Retrofitting and Rehabilitation Solutions: Data-driven support for designing optimal retrofitting techniques, particularly in post-fire or earthquake-affected structures.
Policy Support: Providing the Ministry with insights and decision-support tools to inform sustainable construction policies, structural safety regulations, and infrastructure resilience planning.
Through this collaboration, our group contributes directly to improving the durability, safety, and sustainability of Jordan’s national infrastructure network.
Our long-standing collaboration with the Jordan Engineers Association focuses on advancing civil engineering practice through applied research, knowledge exchange, and workforce development:
Capacity Building: Conducting training sessions and workshops on AI applications in engineering, including GEP fundamentals, predictive modeling, and data analysis for practicing engineers.
Professional Development: Supporting JEA's continuing education programs by introducing modern computational tools and case studies in structural, transportation, and environmental engineering.
Research Dissemination: Collaborating on co-authored reports, white papers, and conferences that promote best practices in AI-integrated engineering processes.
Standards and Practice Integration: Assisting in the development of practical guidelines for the application of AI/ML in engineering design, inspection, and maintenance workflows.
This partnership ensures a two-way transfer of knowledge—bringing field insights into our research and extending academic advancements into everyday engineering practice.
We actively engage with several leading construction firms and engineering consultancies in Jordan to apply our research to real-world projects. These collaborations support:
Project-Specific Modeling: Applying GEP models to predict material behavior, assess construction risk, and optimize design parameters for active infrastructure projects.
Quality Control and Process Optimization: Using AI algorithms to analyze construction data in real-time, supporting anomaly detection, defect prediction, and productivity improvement.
Cost and Resource Estimation: Developing machine learning models for more accurate forecasting of material usage, labor needs, and budgeting for large-scale construction efforts.
AI Tool Integration: Assisting engineering firms in adopting AI-enabled platforms for automated design checking, planning, and monitoring—enhancing efficiency, safety, and sustainability.
These partnerships allow our group to validate research findings on-site, refine models based on operational data, and help shape the future of AI-enhanced construction practices.
Together, these collaborations reflect our group’s commitment to producing research that is not only theoretically sound but also practically impactful, professionally integrated, and nationally relevant.