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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 Bulletinhighlighted 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.
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