Harmonizing physical and deep learning modeling: A computationally efficient and interpretable approach for property prediction

Building a quantitative composition-microstructure-property relationship of dual-phase steels via multimodal data mining

On the use of transfer modeling to design new steels with excellent rotating bending fatigue resistance even in the case of very small calibration datasets

High-throughput map design of creep life in low-alloy steels by integrating machine learning with a genetic algorithm

Revolutionizing car body manufacturing using a unified steel metallurgy concept

From creep-life prediction to ultra-creep-resistant steel design: An uncertainty-informed machine learning approach