Conferences Thematic Areas

AI Methods and Core Technologies

• Machine Learning and Data Mining
• Deep Learning and Neural Networks
• Generative AI and Foundation Models (including LLMs)
• Probabilistic Methods and Bayesian Learning
• Graphical Models and Complex Networks
• Transfer, Adaptive and Multi-task Learning
• Semi-supervised, Active and Cost-sensitive Learning
• Feature Engineering, Dimensionality Reduction and Representation Learning
• Signal, Image and Video Processing

Data-Centric AI and Large-Scale Systems

• Big Data Analytics and Data Mining
• Visual Analytics for Big Data
• Computational Modeling for Large-Scale Data
• Cloud, Edge and Distributed AI Systems
• Stream Data Mining and Real-Time Analytics
• Semantic Data Mining and Knowledge Extraction
• Data Engineering and Data Pipelines for AI

AI in Domain-Specific Applications

• Healthcare and Biomedical AI (medicine, computational biology, heart failure, sports & biomedical engineering)
• Engineering and Industrial AI (energy, manufacturing, transport systems)
• Environmental and Climate AI (sustainability, climate science, ecological systems)
• Agriculture and Food Systems
• Web, Communication and Social Systems (WWW, social networks, recommender systems, e-commerce, games)
• Social Sciences and Economics (law, education, learning analytics, sociology, psychology, cognitive science)
• Robotics and Autonomous Systems
• Cybersecurity and Privacy
• Arts, Culture and Creative AI

Trustworthy, Ethical and Human-Centered AI

• Explainable and Interpretable AI
• AI Ethics and Governance
• Fairness, Accountability and Transparency
• Privacy-Preserving AI
• Human-AI Interaction and Collaboration