2nd International Conference on Multi-scale Artificial Intelligence (MAI 2027)

The 2nd International Conference on Multi-scale Artificial Intelligence (MAI 2027) explores AI methods, models, and intelligent systems that integrate information, learning, perception, and decision-making across multiple levels of complexity and abstraction.

Key Topics

• Foundations of multi-scale artificial intelligence
  • Multi-scale machine learning and representation learning
  • Multi-scale deep learning and neural networks
  • Multi-scale optimization and learning
  • Multi-scale probabilistic modeling
  • Multi-scale reinforcement learning
  • Multi-scale federated and distributed learning
  • Multi-scale graph learning and knowledge representation
  • Multi-scale reasoning and decision-making
  • Multi-scale explainable and trustworthy AI
  • Multi-scale continual and adaptive learning
• Multi-scale perception, intelligence, and systems
  • Multi-scale computer vision and object detection
  • Multi-scale multimodal learning
  • Multi-scale natural language processing and large language models
  • Multi-scale generative AI
  • Multi-scale intelligent agents
  • Multi-scale robotics and autonomous systems
  • Multi-scale human-AI interaction
  • Multi-scale cyber-physical systems and intelligent networks
  • Multi-scale edge and distributed intelligence
• Multi-scale AI for complex systems and applications
  • Healthcare and medicine
  • Scientific discovery
  • Engineering and manufacturing
  • Smart cities and transportation
  • Energy systems
  • Earth and environmental systems
  • Internet of Things (IoT)
  • Autonomous systems
  • Finance and business
  • Education
  • Complex decision support
• Emerging frontiers of multi-scale AI
  • Trustworthy and responsible multi-scale AI
  • Privacy-preserving multi-scale AI
  • Human-AI collaboration
  • Brain-inspired multi-scale AI, neuro-AI, and cognitive AI
  • Sustainable multi-scale AI
  • Multi-scale AI governance and ethics
  • Emerging architectures for multi-scale AI
  • Cross-scale learning and reasoning
  • Multi-scale AI for foundation models and intelligent agents
  • Open-source multi-scale AI systems

Who should attend

• AI researchers
• Researchers developing machine learning methods and models
• Scientists working on scientific discovery and complex systems
• Healthcare and medical researchers
• Engineers and manufacturing researchers
• Robotics and autonomous systems researchers
• Researchers in intelligent networks and cyber-physical systems
• Developers of AI systems and applications