Data-Driven Design and Modeling of Biomaterials

This session invites submissions on experimental and computational research that aims to understand and design biomaterials and related processes using data-driven methods. Biomaterials are either inspired by biology or interface with biological systems. Data-driven approaches include, but are not limited to, high-throughput screening, machine learning, data mining, meta-analysis, accelerated simulation techniques, and model prediction based on data. We strongly encourage abstracts that integrate data science with classical simulation and experimental approaches for materials design and property prediction. Submissions must clearly articulate the impact of data science on the materials problem of interest to be considered.