The Machine Learning Revolution in Materials Research

Description

Machine learning (ML) and artificial intelligence (AI) are quickly becoming common-place in materials research. In addition to the standard workflow of fitting a model to a large set of data in order to make predictions, the materials community is finding novel and meaningful ways to integrate AI within their work. The July, 2019 issue of the MRS Bulletin highlighted a few of these applications.  The articles in the issue show that AI/ML is delivering real-world, practical solutions to materials problems, and we need AI/ML methods and models that are more fluent in materials science.

The talks in this webinar expanded on the material presented in the MRS Bulletin issue as well as the MRS Communications Special Issue on Artificial Intelligence.   An interactive Q&A session was held with the speakers following each talk.

TALK PRESENTATIONS:

• Artificial Intelligence (AI) for Accelerating Materials Discovery
  Carla Gomes, Cornell University
  Talk begins at 11:05
     
  
• Accelerating the Search for New Materials using Machine Learning and Adaptive Design
  Prasanna V. Balachandran, University of Virginia
  Talk begins at 42:08
     
  
• Embedding Domain Knowledge for Machine Learning of Complex Material Systems
  Newell Washburn, Carnegie Mellon University
  Talk begins at 1:16:10
     
  
• Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective
  Daniel Ruscitto and Kareem Aggour, GE Global Research
  Talk begins at 1:41:35
     

Sponsored by American Elements

Host(s):

• Keith A. Brown, Boston University

Speaker(s):

• Carla Gomes, Cornell University
• Prasanna V. Balachandran, University of Virginia
• Newell Washburn, Carnegie Mellon University
• Daniel Ruscitto, GE Global Research
• Kareem Aggour, GE Global Research