Machine Learning
Machine Learning, Computational Materials Modeling, Virginia Tech
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Application of machine learning to understand and predict the behavior of materials, the use of algorithms and statistical models to effectively perform a simulation without using explicit theoretical physical models, relying on patterns and inference instead.
Faculty
Pinar Acar, Computational Materials Modeling, Virginia Tech
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Pinar Acar
We work on multi-scale computational methodologies to achieve a comprehensive understanding of processing, microstructure, and material properties. The main research topics are Integrated Computational Materials Engineering (ICME), multi-scale modeling, optimization, uncertainty quantification, reduced order modeling, and machine learning to study material behavior at length scales ranging from microstructure to component.
Sanket Deshmukh, Computational Materials Modeling, Virginia Tech
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Sanket Deshmukh
My research group is interested in developing, adopting, and integrating multi-scale modeling and machine-learning approaches to create new hybrid materials and bio-materials, promising for use in a number of technologically important areas, such as energy and biomedicine.