IMPORTANT DATES
TOPICS
We welcome submissions across the following technical sessions:
Materials Data and Standards
Schema, metadata, and ontology construction for heterogeneous data integration, as well as policies for national materials data repositories.
AI and Material Informatics
Machine learning applications for property prediction, inverse design, and process optimization.
Inorganic Materials
Structural and functional ceramics, semiconductors, glasses, oxides, and other advanced inorganic systems.
Organic Materials
Advanced polymers, soft matter, biomaterials, elastomers, and diverse functional organic compounds.
Metallic Materials
Ferrous and non-ferrous metals, high-performance alloys, intermetallics, and advanced metallurgical systems.
Textile Materials
Natural and synthetic fibers, smart and functional textiles, technical fabrics, and advanced dyeing and finishing materials.
PLENARY SPEAKERS
Kee-Sun Sohn
Sejong University, Korea
Active Learning for Battery Materials Discovery
Lingwei Ma
University of Science and Technology Beijing (USTB), China
Introduction of National Materials Big Data Center and Materials Intelligent Technology
Yibin Xu
National Institute for Materials Science (NIMS), Japan
Building Materials Databases in the Age of AI
Shyue Ping Ong
National University of Singapore
Open Datasets, Software and Models for the Materials AI Era
KEYNOTE SPEAKERS
Koji Hukushima
University of Tokyo
AtomWork Explorer: MCMC-based Materials Exploration guided by predictive uncertainty
Xiang Yang Kong
Shanghai Jiao Tong University
LLM-Orchestrated Toolchain for Materials Characterizations: a representative case of analysis on fluorinated COF membrane
Haiqing Yin
USTB
Standardization of Materials Scientific Data and Its Application in AI-Driven Materials Design of High Entropy Alloys
Lei Shen
National University of Singapore, Singapore
AI for Structure Optimization and Design of Inorganic Materials
Kwang-Ryeol Lee
Korea Institute of Science and Technology
Scientific Communication in the Future AI-Dominating Era
Yousung Jung
Seoul National University
Beyond Product Prediction: AI That Learns Reaction Mechanisms
Ho Won Lee
Korea Institute of Materials Science
AI for Metallic Materials: From Deep Learning to Agentic AI
Dae Young Lim
Korea Institute of Industrial Technology
Future Outlook for the Textile Industry Through the History of High-Performance Fibers
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