1. Data Science & Big Data

• Data mining and knowledge discovery

• Big data processing, storage, and analytics

• Data modeling, integration, and visualization

• Streaming, spatiotemporal, and web data analysis

• Data governance, privacy, and security

• Cloud/edge/distributed data systems

2. Machine Learning & Deep Learning

• Supervised, unsupervised, and reinforcement learning

• Deep neural networks, representation learning

• Foundation models and generative AI

• Transfer, multimodal, and graph learning

• Explainable, trustworthy, and federated learning

• AutoML and optimization for ML

3. Advanced Algorithms & Optimization

• Evolutionary computation and swarm intelligence

• Combinatorial and numerical optimization

• Quantum and quantum-inspired algorithms

• Parallel, distributed, and randomized algorithms

• Algorithmic game theory and resource scheduling

4. Intelligent Computing & Autonomous Systems

• Intelligent agents and multi-agent systems

• Robotics, autonomous vehicles, smart machinery

• Intelligent control and decision-making

• Edge intelligence and embedded AI

• Smart manufacturing and cyber-physical systems

5. AI Applications & Emerging Technologies

• AI for healthcare, finance, and bioinformatics

• Smart city and urban computing

• Learning analytics and educational intelligence

• Environmental and sustainable AI

• Security, forensics, and surveillance

• NLP, speech technologies, computer vision

• Digital twins, AR/VR, and metaverse technologies

6. Interdisciplinary & Future Directions

• Ethical and responsible AI

• Human–AI collaboration

• AI governance and global standards

• Benchmarking, reproducibility, and evaluation