(Including but not limited to the following topics)
Track 1: Artificial Intelligence Natural Language Processing
Fuzzy logic
Computer vision and image understanding
Signal and image processing
Speech and natural language processing
Computational learning theory
Information retrieval and fusion
Hybrid intelligent systems
Intelligent system architectures
Theories and algorithms
Machine learning/reinforcement learning
VLSI and computer architecture
Database systems
Multimedia databases and information retrieval
Programming languages and software systems
Computer networks and distributed systems
Track 2: Data science
Data mining, data analysis, data visualization, data application Natural Language Processing
Data privacy protection
Model fitting and data analysis
Predictive models and economic research
Data processing and storage
Data analysis and mining
Data visualization and reporting
Data privacy and ethics
Data systems and architectures
Spatial-temporal data analysis
Data-driven decision-making
Data quality management
Data integration and interoperability
Data management strategies
Cloud computing and big data
Biological data science
Data-driven innovation
Ethics and transparency in data science
Specific industry data applications
Environmental data science
Data science platforms and tools
Track 3: Edge computing
Collaboration between edge computing and cloud computing
Network protocols for edge computing
Fault management of edge devices
Load balancing in edge computing
Dynamic scheduling of edge computing services
Data caching in edge computing
Edge intelligence and machine learning
Edge AI in edge computing
Edge network slicing
Internet of Things supported by edge computing
Data stream processing
Application development in edge computing environment
Resource scheduling algorithms
Network performance optimization in edge computing
Delay optimization in edge computing ......