Artificial Intelligence and Machine Learning (AI/ML) for Experimental Materials Science

Date: March 1, 2023

Time: 12:00PM - 01:30PM

You must be registered to participate!

Emerging fundamental and applied problems in modern materials science, with rapidly growing complexity and parameter spaces, require a new approach to experimentation and parameter space exploration. The February 2023 issue of MRS Bulletin highlights recent progress, emerging basic science questions, and important challenges that have arisen in the application of data science tools in experimental materials research. The talks in this webinar by authors of articles in this MRS Bulletin issue cover some of these critical and important aspects.

This webinar is presented in conjunction with the February, 2023 issue of MRS Bulletin.

Hosts:

Keith Brown, Boston University
Milad Abolhasani, Department of Chemical and Biomolecular Engineering, North Carolina State University

Speakers:

Xiaonan Wang, Tsinghua University
Mahshid Ahmadi, University of Tennessee
Marcus Noack, Lawrence Berkeley National Laboratory