Flex Conference (Physical / Digital)

International Conference on Quantum Computing and Machine Learning - (ICQCML-27)

11th - 12th March 2027 , Mexico City - Mexico

Listener Participation Present at Conference
Registration Options →

Access Flexible Participation Categories

Call For Papers

The (ICQCML-27) 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 Machine Learning 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:

  • Quantum algorithms for machine learning
  • Quantum machine learning applications
  • Hybrid quantum-classical computing models
  • Quantum data encoding techniques
  • Error correction in quantum ML systems
  • Quantum neural networks and architectures
  • Applications of quantum computing in AI
  • Quantum-enhanced optimization algorithms
  • Machine learning for quantum system analysis
  • Quantum cryptography and machine learning
  • Scalability challenges in quantum ML
  • Quantum simulations for machine learning
  • Interdisciplinary approaches to quantum AI
  • Quantum machine learning frameworks
  • Impact of quantum computing on ML research
  • Quantum feature selection methods
  • Real-world applications of quantum ML
  • Ethical implications of quantum technologies
  • Future directions in quantum machine learning
  • Collaborative quantum computing initiatives

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.

Submit Your Research Work Register Now