Machine learning for material property prediction

Project Status

In progress

Project Description:

Density Functional Theory based methods for calculating material properties from first principles require large computation facilities and significant computation time. This project aims to develop novel machine learning models and workflows in order to better predict material properties in a fraction of the computation the time that current techniques require.

Student Research Computing Facilitator Profile

Graduate student studying physics with further background in computer science, machine learning, and high performance computing. (Michael Butler, UMaine Orono)

Project Owner

Liping Yu

Project Institution

University of Maine Orono

Anchor Institution

University of Maine

Project Address

105 Bennett Hall
Orono, ME 04469