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Event Registration Deadline:               23.02.2025
Abstract Submission Deadline:           23.02.2025
Oral contribution confirmation:         12.03.2025

Addressing global challenges such as climate change, the demand for sustainable materials, and technological advancements require the development of rapid and reliable methods for creating novel materials. Recent breakthroughs in machine learning (ML) had significant impact on industry and academia, including materials science. ML has already been applied to structure generation, material property prediction, synthesis design, information extraction from literature, and more. Still further improvements are needed in terms of better synthesizability of predicted materials, lower training time and data requirements, and better exploitability.

The Machine Learning for Materials Discovery (ML4MD) workshop will address these needs through its focus on the discovery of novel materials through generative ML tools, human-in-the-loop approaches, ML synthesizability and retrosynthesis prediction, and uncertainty aware ML models and out-of-domain predictions.

The ML4MD workshop will bring together young researchers, academic and industrial experts in AI and materials science to exchange knowledge and discuss recent progress, key challenges, and future directions of materials discovery.