Flex Conference (Physical / Digital)

International Conference on Transfer Learning in Engineering Applications - (ICTLEA-26)

17th - 18th October 2026 , Suva - Fiji

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Call For Papers

The (ICTLEA-26) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Data Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Transfer learning in engineering domains
  • Domain adaptation techniques for engineers
  • Improving model performance with transfer learning
  • Applications of transfer learning in robotics
  • Case studies in engineering transfer learning
  • Challenges in transfer learning applications
  • Transfer learning for predictive maintenance
  • Multi-task learning in engineering contexts
  • Transfer learning for sensor data analysis
  • Deep learning and transfer learning synergy
  • Cross-domain knowledge transfer methods
  • Evaluating transfer learning effectiveness
  • Real-world applications of transfer learning
  • Data scarcity solutions using transfer learning
  • Transfer learning in structural engineering
  • Ethical considerations in transfer learning
  • Transfer learning for smart manufacturing
  • Innovative architectures for transfer learning
  • Transfer learning in environmental engineering
  • Future directions in transfer learning research

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.