📚︎1. Data Science and Big Data Technology

Fundamentals of Data Science; 

Big data architecture; Data Mining and Knowledge Discovery; 

Data Visualization and Analysis; Data governance and ethics; 

Data Engineering and Integration; 

Multimodal Data Management; 

Time series and spatial data analysis; 

Data Engineering for Artificial Intelligence

📚︎2. Modeling and Simulation

Computational Modeling and Simulation; 

High performance and parallel simulation; 

Model validation and uncertainty quantification; 

Hybrid modeling method; 

Simulation in Engineering and Science; 

Complex system modeling; 

Physical information modeling; 

Real-time simulation and digital twin; 

Sim2Real and Transfer Learning

📚︎3. Artificial Intelligence and Intelligent Systems

Basic model and big language model; 

Agent AI and multi-agent systems; 

World model and generative simulation; 

Deep learning and neural networks; 

Generative AI; 

Explainable AI and trusted artificial intelligence; 

Reinforcement learning; 

Computer Vision and Pattern Recognition; 

Natural language processing; 

Edge AI and distributed intelligence

📚︎4. Other Related Topics

Digital twin driven by artificial intelligence; 

Artificial intelligence for modeling and simulation (AI for M& S); 

Data Science and Artificial Intelligence for Scientific 

Discovery (AI4S); Data Synthesis and Data Enhancement; 

Space intelligence and physical artificial intelligence; 

Intelligent reality and meta-universe applications; 

Composite AI system and AI orchestration; 

Artificial intelligence governance security and ethics; 

Industrial Artificial Intelligence and Intelligent Systems; 

Edge intelligent analysis