Aims & Scope

Journal of AI-Driven Civil Engineering (JAIDCE) is an international, peer-reviewed, open-access journal devoted to fundamental and applied research on artificial intelligence for safe, intelligent, resilient, and sustainable civil engineering systems.

The journal publishes original research articles, review papers, case studies, short communications, and viewpoints that advance the development, validation, and application of artificial intelligence in civil engineering. It aims to provide a multidisciplinary platform for researchers, engineers, practitioners, and decision-makers working at the interface of artificial intelligence and civil engineering.

The journal welcomes innovative studies on AI-enabled theories, methods, models, tools, and systems across all major areas of civil engineering, including structural, geotechnical, hydraulic, transportation, environmental, construction, building, urban, underground, and materials engineering. It covers the full life cycle of civil infrastructure, including planning, design, simulation, construction, operation, maintenance, assessment, retrofitting, risk management, resilience enhancement, and disaster mitigation.

The journal places particular emphasis on reproducible, reliable, and engineering-grounded research. Contributions are especially encouraged when they integrate artificial intelligence with domain knowledge, physical mechanisms, numerical simulation, laboratory testing, field monitoring, or real-world engineering applications. The journal also welcomes studies on trustworthy, explainable, transparent, and responsible AI for civil engineering. Robust validation, transparent workflows, and clear engineering significance are essential considerations for publication.

Journal of AI-Driven Civil Engineering is published quarterly online by Scilight Press.

Topics covered by the journal include, but are not limited to, the following themes:

  1. Artificial intelligence for civil engineering science and practice
  2. AI-enabled analysis, design, simulation, and optimization
  3. Data-driven, physics-informed, and hybrid modeling methods
  4. Machine learning, deep learning, and generative AI for civil engineering
  5. Intelligent sensing, monitoring, diagnosis, and assessment
  6. Digital twins, digital construction, and infrastructure life-cycle management
  7. Civil infrastructure operation, maintenance, safety, and resilience
  8. Risk assessment, disaster prevention, and emergency management
  9. Sustainable materials, structures, infrastructure, and built environments
  10. Robotics, automation, and intelligent construction systems
  11. Decision support systems, human–AI collaboration, and smart infrastructure
  12. Trustworthy, explainable, transparent, and responsible AI