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Seminar | Energy and Global Security

Artificial Intelligence for Material and Process Design

EGS Summer Seminar

Abstract: Modeling properties and evolution of complex systems requires a comprehensive evaluation of uncertainty and model quality using experimental, theoretical and computational methods that operate at vastly different length and time scales. In parallel, with the volume and rate of data generation continuously increasing, human analysis becomes more difficult, if not impossible. Fortunately, recent advances in artificial intelligence (AI) have significantly improved R&D methodologies by emphasizing the role of the human-machine partnership.
 
Marius Stan discusses the development of intelligent software” that includes elements of AI such as machine learning, active learning, immersive visualization and augmented reality, coupled with reduce-order modeling and Bayesian analysis. He illustrates the value of the approach using examples of machine learning modeling of material properties and real-time optimization of manufacturing processes.

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