Artificial Intelligence and Machine Learning for Materials: Panel at IMAT 2024
Source abstract
Abstract
Abstract This article describes highlights from a panel held at IMAT 2024. Representatives from industry, government, and academia discussed the potential that artificial intelligence and machine learning offer the materials science and manufacturing communities. David Furrer, Pratt & Whitney, moderated the panel. The panelists were Seth Kimble, ASM International; Joshua Stuckner, NASA Glenn Research Center; James E. Saal, Citrine Informatics; and S. Mohadeseh Taheri-Mousavi, Carnegie Mellon University. Each panelist provided their perspective on how AI and ML are impacting current and future materials design and manufacturing processes.
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Research context
OpenAlex topics: Machine Learning in Materials Science · Electron and X-Ray Spectroscopy Techniques
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