Andrés J. García

Machine learning for biomaterials design

This Review surveys machine learning methods, including surrogate modelling, generative design and active learning loops, for predicting and optimizing properties across metals, polymers, hydrogels, ceramics and biological biomaterials, and outlines key datasets, challenges, and future autonomous discovery pipelines.