AIEI 2026 invites original research papers, case studies, conceptual frameworks, and policy discussions that examine the integration of Artificial Intelligence with Emotional Intelligence across multiple domains. This multi-disciplinary conference seeks contributions from computer science, psychology, neuroscience, education, healthcare, business, and ethics to advance understanding and applications of emotionally intelligent AI. The conference aims to highlight how emotion-aware AI systems can transform human interactions, improve decision-making, and support inclusive growth while also addressing concerns around privacy, fairness, and cultural adaptation.
1. Emotional Intelligence in Artificial Intelligence
—Affective Computing
—Sentiment Analysis
—Emotion Recognition from Facial Expressions, Voice, and Physiological Signals
—Multimodal Emotion Detection
—Emotion-Aware Conversational Agents
—Neural Networks for Emotion Classification
—Cross-Cultural Emotion Recognition
—Emotion Dataset Development and Annotation
—Emotion Dynamics in Real-Time Interactions
—Probabilistic Modeling of Emotional States
—Deep Reinforcement Learning for Emotion-Aware Systems
—Cognitive Computing for Empathy Simulation
—Explainable Emotional AI
—Ethics of Automated Emotion Recognition
2. Emotional AI in Healthcare and Wellbeing
—AI-Powered Virtual Therapists
—Chatbots for Mental Health Support
—Emotion-Sensitive Robotics in Eldercare
—Stress and Anxiety Detection with Wearable Devices
—AI for Monitoring Patient Emotional States
—Emotion-Aware Doctor-Patient Interaction Tools
—Adaptive AI in Personalized Healthcare
—Predictive Analytics for Mental Health Disorders
—Digital Biomarkers for Emotional Health
—Privacy-Preserving Emotional Health Data
—Empathy in AI-Assisted Counseling
—AI in Wellness Coaching
—Gamification for Emotional Resilience Training
—Digital Twins for Emotional Health Modeling
3. Emotional AI in Education and Human Capital Development
—Emotion-Aware Tutoring Systems
—Adaptive Learning with Emotional Feedback
—Personalized Education Pathways using Emotional Data
—AI for Early Detection of Student Disengagement
—Sentiment Analytics in Learning Management Systems
—AI-Supported Teacher Training in Emotional Pedagogy
—Micro-Credentials and Skills Recognition via Emotional Data
—Emotion-Aware Educational Chatbots
—Gamified Learning with Emotional Feedback
—Emotion Recognition in Remote Classrooms
—Emotion-Aware AR/VR Learning Environments
—AI-Powered Student Wellbeing Monitoring
—Emotion-Centered Learning Analytics
—Competency-Based Emotional Skills Assessment
4. Organizational Intelligence and Workforce Analytics
—AI in Emotion-Aware Recruitment
—Predictive Analytics for Employee Retention using Emotional Data
—Emotion Recognition for Team Collaboration
—Leadership Development through Emotional AI Tools
—Employee Sentiment Monitoring with NLP
—AI-Enhanced Performance Measurement
—Emotional Wellbeing Analytics in Hybrid Work Environments
—AI-Driven Career Path Mapping with Emotional Insights
—Ethical Use of Emotion Recognition in HR
—Workplace Culture Analytics
—Reskilling with Emotion-Aware Learning Platforms
—Diversity, Equity, and Inclusion through Emotional Analytics
—Emotion-Sensitive Robotic Process Automation in Workflows
5. Emotional AI in Business, Marketing, and Consumer Analytics
—Emotion-Driven Customer Segmentation
—AI in Neuromarketing and Consumer Emotion Tracking
—Predictive Analytics for Customer Sentiment
—Emotion-Aware Chatbots for Customer Service
—Real-Time Emotion Analytics in Retail
—Generative AI for Emotionally Engaging Advertisements
—Personalization Engines with Emotional Context
—AR/VR Marketing with Emotional Feedback
—Programmatic Advertising with Emotion Recognition
—AI in Brand Trust and Loyalty Analytics
—Cross-Cultural Emotion Analytics for Global Marketing
—Customer Journey Mapping with Emotional Signals
—Gamification for Emotion-Driven Consumer Engagement
6. Governance, Ethics, and Responsible Emotional AI
—Algorithmic Empathy and Its Limits
—Ethical Frameworks for Emotion Recognition in AI
—Emotional Data Governance and Privacy Protection
—Regulatory Frameworks for Affective Computing
—Cross-Border Emotional Data Flow and Jurisdiction
—Bias and Fairness in Emotion Recognition
—Transparency and Explainability in Emotion-Aware AI
—AI in Electoral Systems and Civic Emotion Analysis
—Ethical Surveillance with Emotional AI
—Societal Risks of Emotionally Manipulative AI
—Global Cooperation for Ethical Emotional AI
—Cultural Adaptation of Emotional AI in Governance
7. Innovation, Entrepreneurship, and Emerging Applications
—Startups in Emotional AI and Affective Computing
—Venture Capital Trends in Emotion-Tech
—AI-Driven Prototyping of Emotion-Aware Devices
—Emotion-Aware Gaming and AR/VR Experiences
—Emotion-Sensitive Virtual Assistants in Smart Homes
—Emotion Analytics in Entertainment and Media
—Experimental Labs for Emotion-Aware Human-Robot Interaction
—AI for Emotion-Aware Creative Arts
—Market Forecasting for Emotion-Driven Products
—Emotion-Aware Personal Finance Apps
—Emotion-Aware Fitness and Lifestyle Platforms
—Commercialization of Emotional AI in Consumer Electronics
8. Society, Culture, and Inclusive Growth with Emotional AI
—AI for Emotional Wellbeing in Rural and Underserved Communities
—Emotion Recognition Across Languages and Dialects
—Emotional AI for Persons with Disabilities
—Inclusive Design of Emotion-Aware Interfaces
—Gender and Diversity in Emotion Recognition Systems
—Community-Based Innovation in Emotional AI
—Emotion-Aware Social Robotics in Public Spaces
—Emotional AI for Crisis Response and Disaster Management
—Emotion-Aware Platforms for Civic Engagement
—Emotional AI in Digital Literacy Campaigns
—Cultural Narratives and Emotion-Aware Storytelling Technologies