The English papers accepted by our previous DDCLS conferences had been included in the IEEE Xplore, and indexed by EI Compendex or ISTP database. The DDCLS'27 covers both theory and applications in all the areas of data driven control and learning systems. The topics of interest include, but are not limited to:

• Data-driven control theory, approaches, and applications 
• Model-free adaptive control theory and applications 
• Active disturbance rejection control and applications 
• Data-driven fault diagnosis, health maintenance and performance evaluation 
• Iterative learning identification, iterative learning control (repetitive control) 
• Data-driven modeling, optimization, scheduling, decision and simulation 
• Statistical learning, data mining and practical applications in automation field 
• Neural networks, fuzzy systems control methods in data driven manner 
• Reinforcement learning control, ADP based learning control and learning based control 
• Robustness of data-driven control 
• Relationships between data-driven and model-based control methods 
• Applications of data-driven methods in industrial processes 
• Data-driven modeling, control, and optimization for complex systems
• Data-driven control for practical complex processes 
• Technologies and applications of complex big-data systems
• Big data in industrial processes, and applications in modeling and control 
• Complex systems and artificial intelligence