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Special Session 3: Advanced Technologies in Affective Computing and Mental Health Diagnostics
 

With the rapid development of AI and pattern recognition, affective computing has become pivotal in mental health. This workshop focuses on interdisciplinary research spanning emotion analysis and AI-assisted diagnostics, aiming to decode emotional patterns, predict psychological states, and address ethical dilemmas, ultimately advancing intelligent mental healthcare solutions.

 

Organizer: Dr. Shanliang Yang, Shandong University of Technology, China

 

The topics of interest include, but are not limited to:

1. Fundamental Techniques of Emotion Analysis

  • Multimodal emotion data fusion (text, speech, visual)
  • Real-time sentiment monitoring in social media
  • Cross-lingual/cultural emotion recognition

    • 2. Affective Computing in Mental Health Diagnostics

  • Quantitative emotion biomarkers for depression/anxiety
  • Deep learning-based psychological crisis early-warning systems
  • VR-integrated interactive therapy systems

    • 3. Explainability and Ethics in Affective Models

  • Interpretability of black-box models for clinical adoption
  • Privacy-preserving mechanisms for mental health data
  • Societal norms and accountability in AI diagnostics

    • 4. Pattern Recognition for Mental Health Big Data

  • Representation learning for unstructured psychological data
  • Graph-based behavior-emotion correlation mining
  • Few-shot learning for low-resource scenarios


    • Submission Guideline

    Please submit your manuscript via Electronic Submission System (account is needed). (Please remark the session number when you make the submission.)

     

    Important Dates

    • Submission of Full Papers: July 05, 2025
    • Notification of Review Result of Papers from Special Sessions: August 25, 2025
    • Registration Deadline: September 25, 2025