SPECIAL SESSION

Special Session Ⅰ: Artificial Intelligence and Education

Session Chair: Assoc. Prof. Lan Yan, Hainan University, China

Keywords: Integration of Artificial Intelligence and Education; AI-Based Education; Education-Oriented Artificial Intelligence Research; Intelligent Teaching Systems and Applications; Intelligent Analysis of Educational Data; Intelligent Empowerment of Personalized Learning

Information: This special topic focuses on the in-depth interdisciplinary research of artificial intelligence and education. It covers not only practical directions such as the innovative application of AI technology in educational scenarios, the development of intelligent teaching tools, and the design of personalized learning programs, but also basic research such as AI algorithm optimization, model construction, and technology adaptation oriented to educational needs. It aims to promote the organic combination of technological empowerment and educational laws, and facilitate the digital transformation and high-quality development of education.

Below is an incomplete list of potential topics to be covered in the Special Session:

AI-Driven Personalized Learning Path Planning and Practice
Design and Optimization of AI Models for Educational Purposes
Development of Intelligent Teaching Systems and Evaluation of Classroom Application Effects
Application of Educational Big Data Analysis in Improving Teaching Quality
AI Ethical Norms and Risk Prevention Based on Educational Scenarios
AI-Enabled Construction and Innovation of Lifelong Learning Systems
The Guiding Role of Educational Method Innovation in AI Technology R&D
Application of Intelligent Assessment Technology in Educational Evaluation Reform
Theory and Practice of AI-Education Integration from an Interdisciplinary Perspective
R&D of AI-Assisted Tools for Special Educational Needs

Submission Deadline: April 20, 2026

Special Session Ⅱ: Intelligent Optimization, Learning, Modeling, and Decision-Making in Complex Systems and Engineering Applications

Session Chair: Prof. Chixin Xiao, Xiangtan University, China

Keywords: Machine Learning, Reinforcement Learning, Evolutionary Computation, Multi-objective Optimization, Multi-disciplinary Optimization and Design, Probabilistic Surrogate Optimization, Stochastic Optimization, Uncertainty Modeling, Complex Systems, Intelligent Decision-Making

Information: This special session aims to bring together researchers and practitioners from artificial intelligence, optimization, and complex systems engineering to explore interdisciplinary advances in intelligent optimization, learning, and decision-making. The session welcomes theoretical, methodological, and application-oriented contributions addressing challenges in dynamic, uncertain, and large-scale environments. Topics include but are not limited to multi-agent learning, stochastic and probabilistic optimization, reinforcement learning, evolutionary computation, and risk-aware decision support for energy, transportation, manufacturing, and environmental systems.

Below is an incomplete list of potential topics to be covered in the Special Session:

AI and ML methods for stochastic and uncertainty-aware optimization
Reinforcement learning for adaptive and dynamic decision-making
Evolutionary computation and swarm intelligence in complex systems
Multi-agent learning and cooperative decision under uncertainty
Data-driven predictive modeling and probabilistic surrogate optimization
Risk-aware and robust optimization for complex environments
Digital twin and intelligent control under stochastic disturbances
Interdisciplinary applications in energy, environment, and manufacturing systems

Submission Deadline: April 20, 2026

Special Session Ⅲ: Next-Gen AI-Driven Smart Manufacturing

Session Chair: Assoc. Prof. Haixia Xu, Xiangtan University, China

Keywords: Smart Manufacturing, Industrial AI, Multi-Modal Foundation Models, Interpretable AI

Information: Smart manufacturing is the core driving force of the new industrial revolution. Currently, AI technology is transitioning from isolated applications to full-process integration, achieving large-scale deployment in quality inspection, fault diagnosis, production scheduling, and other scenarios. However, the journey toward comprehensive intelligence still faces multiple bottlenecks, making issues of interpretability, real-time performance, and robustness critical challenges demanding immediate breakthroughs. Next-generation intelligent technologies based on multi-modal foundation models demonstrate tremendous potential in smart factories, digital twins, and production process optimization by fusing visual, textual, temporal, and other multi-source data, emerging as the key direction for overcoming these bottlenecks.

This session covers the following core technologies: industrial vision quality inspection and defect analysis, multi-modal data fusion and alignment, open-vocabulary defect detection and fine-grained classification, few-shot/zero-shot learning and cross-domain generalization, interpretable AI and causal reasoning, lightweight edge deployment and real-time inference optimization, domain adaptation and knowledge injection for industrial foundation models, and human-machine collaborative intelligent systems，etc. The session will also emphasize application practices in high-precision manufacturing such as automotive, semiconductors, and precision components, exploring technical feasibility, cost-effectiveness, and large-scale promotion prospects. It aims to establish a high-level technical exchange platform for experts and practitioners from academia and industry, fostering deep integration of technological breakthroughs and industrial deployment to jointly advance the intelligent transformation of manufacturing to a new stage.

Below is an incomplete list of potential topics to be covered in the Special Session:

Industrial Vision Inspection and Foundation Model Applications
Multi-Modal Data Fusion and Alignment Mechanisms
Open-Vocabulary and Fine-Grained Defect Detection
Few-Shot Learning and Model Generalization
Interpretability and causal reasoning
Edge Intelligence and Real-Time Inference Optimization
Digital Twins and Smart Factory Modeling
Human-Machine Collaboration and Flexible Manufacturing
Industrial Knowledge Graphs and Intelligent Decision-Making
Evaluation and Standards for Intelligent Inspection Systems

Submission Deadline: April 20, 2026

Special Session Ⅳ: Algorithm Optimization and Applications Based on Machine Learning and Deep Learning

Session Chairs: Assoc. Prof. Lifeng Yin, Dalian Jiaotong University, China

Assoc. Prof. Miao Wang, Henan University of Engineering, China

Keywords: Supervised Learning; Unsupervised Learning; Reinforcement Learning; Deep Learning

Information: Algorithm optimization and applications based on machine learning and deep learning are important research directions in the field of modern artificial intelligence, aimed at enhancing model performance and computational efficiency. Optimization methods include hyperparameter tuning, feature selection, training process optimization, and model compression, all designed to improve the accuracy and responsiveness of algorithms. These optimization techniques are widely applied in areas such as natural language processing, computer vision, healthcare, and fintech, contributing to higher predictive accuracy and real-time decision-making capabilities.

Below is an incomplete list of potential topics to be covered in the Special Session:

Optimization and Applications of Supervised Learning Algorithms
Optimization and Applications of Unsupervised Learning Algorithms
Optimization and Applications of Reinforcement Learning Algorithms
Optimization and Applications Based on YOLOv8 Algorithm
Optimization and Applications Based on Graph Neural Networks
Research on the Application of Deep Learning in Multimodal Data Fusion

Submission Deadline: April 20, 2026