Flex Conference (Physical / Digital)

International Conference on Human-Computer Interaction with Machine Learning - (ICHCIML-26)

9th - 10th October 2026 , Taipei City - Taiwan

Registration Options

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Call For Papers

The (ICHCIML-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 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:

  • User experience design with machine learning
  • AI for accessibility in human-computer interaction
  • Natural language interfaces and interaction
  • Personalization in user interfaces using AI
  • Emotion recognition in HCI applications
  • Machine learning for adaptive systems
  • Usability testing with AI technologies
  • Augmented reality in human-computer interaction
  • AI-driven user feedback analysis
  • Cognitive modeling for user behavior prediction
  • Ethics of AI in user interaction
  • Collaborative interfaces using machine learning
  • Machine learning for user engagement strategies
  • Impact of AI on user experience
  • Gamification in human-computer interaction
  • Future of HCI technologies with AI
  • Data visualization techniques in HCI
  • AI for cross-cultural user experience design
  • Human-centered AI design principles
  • Interdisciplinary approaches to HCI 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.