Special Sessions

Special Session Ⅰ: AI for Education: Integrating Technological Innovation and Learning Sciences

Session Chair: Assoc. Prof. Fan Zou, Sichuan Normal University, China

Keywords: Generative AI, Intelligent Tutoring Systems / AI Agent, Human-Computer Interaction, Learning Sciences, Learning Analytics, Knowledge Modelling

Information: This special session focuses on the theory, technology, and practice of Artificial Intelligence (AI) in education, aiming to bring together scholars from fields such as computer science and educational technology. We seek to explore how emerging technologies, represented by Generative AI, can be deeply integrated with learning sciences to transform education. The session will highlight, but is not limited to, technological innovations like Generative AI and AI Agents, and their applications in personalized learning, intelligent tutoring, human-AI collaboration, educational content creation, and learning analytics. We encourage submissions based on interdisciplinary theory, system implementation, applied practice, and empirical research to jointly explore the opportunities and challenges of AI in education and to advance the synergy between educational technology and learning sciences.

Topics:

1. Generative AI Models & Algorithms

• Exploring Generative AI models for education, including the fine-tuning and optimization of Large Language Models (LLMs) and the construction and evaluation of large pedagogical models. Research on how multimodal AI processes educational data such as text, images, and speech, and the algorithmic design of cross-modal interaction.

2. AI System Design and Human-AI Collaboration

• Designing and building Interactive systems for education, such as intelligent tutoring systems, adaptive learning platforms, educational games and AI Agent architectures.

• Exploring collaboration models between humans and AI in education, and the impact of Human-Computer Interaction (HCI) design on learning experiences.

3. Empirical Research & Learning Sciences Evaluation

• Conduct quantitative, qualitative, and mixed-methods studies on AI applications in education, including but not limited to empirical research, meta-analyses, and systematic reviews.

• Grounded in learning sciences theory and leveraging data science and learning analytics, deeply explore and evaluate the impacts and experiences of AI technologies on learners, teachers, instructional processes, and learning outcomes.

4. Ethics, Privacy & Security

• Ethics and Fairness of AI in Education: Discussing ethical, security, and fairness issues brought by AI technology in education, such as algorithmic bias of Generative AI and data privacy protection.

Submission Deadline: September 25, 2025

Special Session Ⅱ: Medical Information Processing and Analysis

Session Chair: Prof. Ying Tan, Southwest Minzu University, China

Keywords: Medical Big Data Mining, AI-Assisted Diagnosis, Biomedical Informatics, Health Information Management Systems, Clinical Decision Support Systems

Information: This session explores cutting-edge technologies in medical information processing and analysis, including healthcare big data mining, AI-driven clinical decision-making, bioinformatics algorithm innovation, and health information system optimization. It aims to foster interdisciplinary research to advance intelligent transformation in precision medicine, smart hospitals, and public health management.

Topics:

• Intelligent Medical Image Analysis and Processing

• EHR Natural Language Processing and Knowledge Graph Construction

• Multimodal Biomedical Data Fusion and Mining

• Genomics/Proteomics Data Analysis

• AI Ethics and Privacy Protection in Healthcare

• Clinical Predictive Modeling and Decision Support Systems

• Public Health Big Data for Epidemiological Research

Special Session Ⅲ: AI Methodologies and Applications in Pattern Recognition and Machine Learning

Session Chair: Prof. Shuyi Li, Beijing University of Technology, China

Keywords: Advanced AI, Pattern Recognition Technologies, Machine Learning Algorithms, Deep Learning Applications, Intelligent Systems, AI Generated Content

Information: With the booming advancement of artificial intelligence technologies, innovative research work in pattern recognition and machine vision has ushered in a broad application prospect. This session aims to dissecting the latest AI research achievements in pattern recognition, machine learning, deep learning, AI Generated Content, etc. Furthermore, this session will explore how they optimize object detection, image recognition, natural language processing, biometric recognition, smart manufacturing, smart cities, generated content, and other scenarios. 

Topics:

• Advanced machine intelligence methods and applications

• Advanced pattern recognition methods and applications

• Deep-learning-based methods and applications

• Biometric recognition algorithms and applications

• Multi-view/-modal learning and fusion

• Data mining and analysis

• Advanced models in computer vision, such as object tracking and detection, AIGC, NLP

Submission Deadline: September 30, 2025

Special Session Ⅳ: Evolutionary Algorithms and Their Applications

Session Chair: Assoc. Prof. Shoufei Han, Anhui University of Science and Technology, China

Keywords: Evolutionary Algorithms, Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Multi-Objective Optimization, Engineering Optimization, Combinatorial Optimization

Information: As a class of intelligent optimization algorithms inspired by biological evolution and natural selection, evolutionary algorithms have shown remarkable advantages in solving complex optimization problems with high dimensionality, non-linearity, and multi-modality. With the continuous expansion of application fields, from traditional engineering design to emerging areas such as artificial intelligence and big data analysis, evolutionary algorithms have become an important technical support. This session is dedicated to presenting the latest research progress in evolutionary algorithms, including improvements in algorithm frameworks, innovations in optimization strategies, and breakthroughs in theoretical foundations. Additionally, it will focus on exploring how evolutionary algorithms play a role in engineering optimization, combinatorial optimization, multi-objective decision-making, intelligent scheduling, and other practical scenarios, thereby promoting the exchange and integration of theory and application in this field.

Topics:

• Improved algorithms and theoretical research of evolutionary algorithms

• Genetic algorithms and their application in complex optimization problems

• Particle swarm optimization and its extended applications

• Differential evolution algorithms and engineering practice

• Multi-objective evolutionary algorithms and decision support

• Evolutionary algorithms in combinatorial optimization (such as scheduling, routing)

• Application of evolutionary algorithms in engineering design and intelligent manufacturing

Submission Deadline: September 30, 2025

Special Session Ⅴ: 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.

Topics:

• 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: September 30, 2025