1. Data-driven Physics-based Digital Twins 2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge 3. Dynamical Systems-Guided Learning of PDEs from Data 4. Learning First-principles Knowledge from Data 5. Actual Learning through Machine Learning 6. Iterative Cross Learning 7. Learning an Algebraic Model from Data 8. Data-driven Optimization Algorithms 9. Interpretable Machine Learning 10. Learning Science and Algorithms 11. Reinforcement Learning 12. Machine Learning: Trends, Perspectives, and Prospects 13. Artificial Intelligence: Trends, Perspectives, and Prospects 14. Artificial Intelligence Education for Chemical Engineers