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About this Abstract
Meeting	MS&T24: Materials Science & Technology
Symposium	Frontiers of Machine Learning on Materials Discovery
Presentation Title	Accelerating Electron Microscopy and Experimentation through Acceptance of ML/AI
Author(s)	Matt Olszta
On-Site Speaker (Planned)	Matt Olszta
Abstract Scope	Artificial intelligence and machine learning are now becoming commonplace amongst materials science research and innovation. Digital twins drive the scientific landscape to be able to both quickly understand inputs and rapidly predict system behaviors with low latency. How have these new apparent game changing paradigms made large impacts within our sphere? How can we learn and adapt these tools to further our research? In the realm of electron microscopy, the keen human observationalist has been the AI/ML since day one. We are constantly utilizing the science of microscopy instead of letting it become a simple tool. The microscopy and materials science community can greatly benefit from adopting AI/ML in our workflows to accelerate our research. Here I will discuss how we are integrating AI/ML to do better microscopy and in turn more meticulous and rigorous science through various use cases ranging from laser welding to automated electron microscopy.

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