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