9th Edition · Seoul, Korea
AMDS 2026
The 9th Asian Materials Data Symposium
📅 Sep 30 – Oct 2, 2026
📍 COEX, Seoul, Korea
7+ Participating Nations
6+ Technical Sessions
32+ Invited Speakers
100+ Participants

IMPORTANT DATES

Abstract Submission Deadline July 13, 2026
Decision / Acceptance Notification July 22, 2026
Early Registration Deadline August 30, 2026
Online Pre-registration Closing September 21, 2026
Conference Sep 30 – Oct 2, 2026
COEX, Seoul

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

Kee-Sun Sohn

Sejong University, Korea

Active Learning for Battery Materials Discovery

Lingwei Ma

Lingwei Ma

University of Science and Technology Beijing (USTB), China

Introduction of National Materials Big Data Center and Materials Intelligent Technology

Yibin Xu

Yibin Xu

National Institute for Materials Science (NIMS), Japan

Building Materials Databases in the Age of AI

Shyue Ping Ong

Shyue Ping Ong

National University of Singapore

Open Datasets, Software and Models for the Materials AI Era

KEYNOTE SPEAKERS

Koji Hukushima

Koji Hukushima

University of Tokyo

AtomWork Explorer: MCMC-based Materials Exploration guided by predictive uncertainty

Xiang Yang Kong

Xiang Yang Kong

Shanghai Jiao Tong University

LLM-Orchestrated Toolchain for Materials Characterizations: a representative case of analysis on fluorinated COF membrane

Haiqing Yin

Haiqing Yin

USTB

Standardization of Materials Scientific Data and Its Application in AI-Driven Materials Design of High Entropy Alloys

Lei Shen

Lei Shen

National University of Singapore, Singapore

AI for Structure Optimization and Design of Inorganic Materials

Kwang-Ryeol Lee

Kwang-Ryeol Lee

Korea Institute of Science and Technology

Scientific Communication in the Future AI-Dominating Era

Yousung Jung

Yousung Jung

Seoul National University

Beyond Product Prediction: AI That Learns Reaction Mechanisms

Ho Won Lee

Ho Won Lee

Korea Institute of Materials Science

AI for Metallic Materials: From Deep Learning to Agentic AI

Dae Young Lim

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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