The International Workshop on AI for Cognitive and Mental Health Support
AI4Mental @ KDD 2026
ACM KDD 2026 | Jeju, Korea | August 9, 2026
International Convention Center Jeju (ICC Jeju)
Join us at KDD'26 to explore how AI is transforming cognitive and mental health support
About AI4Mental
Cognitive and mental health (CMH) disorders are increasingly prevalent worldwide and pose significant societal, clinical, and economic challenges. While conventional mental health support methods remain limited by scalability and reactivity, recent advances in artificial intelligence have opened new opportunities for scalable, proactive, and personalized mental health support.
The AI4Mental workshop is a half-day interdisciplinary forum that brings together researchers and practitioners from data mining, machine learning, NLP, HCI, healthcare, and social sciences. The workshop focuses on three complementary pillars:
- 🧠AI as Assessment - Leveraging AI to assess cognitive states, mental health risks, and behavioral patterns
- 💬 AI as Emotional Support - AI systems that provide empathetic, supportive, and context-aware interactions
- 🎯 AI as Psychological Intervention - AI-driven interventions that actively support treatment and recovery
Important Dates
| Event |
Date |
| Paper Submission Deadline |
April 30th, 2026 |
| Notification to Authors |
June 4th, 2026 |
| Camera-ready Deadline |
TBD |
| Workshop Day |
TBD |
All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.
Topics of Interest
AI as Assessment
- Early detection and monitoring of mental health disorders (depression, anxiety, suicide risk, cognitive decline)
- Multimodal mental health assessment using text, speech, vision, physiological, and social signals
- Interpretable and fairness-aware assessment models for reliable clinical decision support
- Longitudinal modeling and personalized risk prediction across time and contexts
- Dataset construction, annotation strategies, and benchmark development
AI as Emotional Support
- Empathetic conversational agents and affect-aware dialogue systems
- Emotion recognition and adaptive response generation in mental health conversations
- Large Language Models (LLMs) for supportive dialogue, companionship, and mental well-being assistance
- Personalization, trust, and user engagement in AI-based emotional support systems
- Ethical considerations, safety alignment, and responsible deployment
AI as Psychological Intervention
- AI-assisted delivery of psychological interventions (CBT, mindfulness, motivational interviewing)
- Human-AI collaboration in therapeutic settings and clinician-in-the-loop systems
- Intervention planning, progress tracking, and outcome evaluation using AI
- Adaptive and personalized intervention strategies based on user state and feedback
- Clinical validation, real-world deployment, and regulatory challenges
Contact
For any inquiries, please contact:
- Xiangmeng Wang (Primary Contact): xiangmengpoly.wang@polyu.edu.hk
- Haoyang Li: haoyang-comp.li@polyu.edu.hk