CM@B Speaker Series

Anubhav Jain: Software Tools, Crystal Descriptors, and Applications of Machine Learning Applied to Materials Design

Time: 4pm Tuesday, October 16, 2018

290 Hearst Memorial Mining Building

Today, it is easier than ever to apply the tools of high-throughput computation and machine learning to materials design problems. That’s why we’re especially pleased to have Anubhav Jain, one of the pioneers in this field, talk about how materials scientists can apply these powerful tools in their research. Many believe that the Jain group’s work on developing novel descriptors for crystal structure will have important applications in materials data mining problems. Furthermore, their recent activities in text mining millions of materials science journal abstracts to extract information about materials and their properties is a completely new approach to computational materials research and is one of the hottest areas in computational materials today.

In his talk, Anubhav will also describe his group’s work in developing open-source software frameworks like atomate to generate and analyze large computational data sets at supercomputing centers, which has lead to major advances in the field of high-throughput computational materials science over the last 5 years. Attendees will also get a great introduction to matminer, which is a software package that can be used to rapidly prototype, refine, and deploy machine learning models (elastic modulus, phonons, and general structure-property relationships).