On-location / Digital Conference

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

28th - 29th May 2027,Geneva, Switzerland

In Association With:

Call for Paper


Important Dates


Early Bird Registration

28th Apr 2027

Paper Submission Deadline

3rd May 2027

Registration Deadline

13th May 2027

Conference Date

28th - 29th May 2027

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Geneva ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Geneva conference.
  • Peer Review Process:
    The peer review process will begin soon for Geneva conference.
  • Networking with Global Experts:
    Join global experts at our conference in Geneva.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICQCML bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Quantum Computing and Machine Learning, encouraging applied research, case studies, and industry-driven innovations.

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

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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