Machine Learning
Machine Learning, Computational Materials Modeling, Virginia Tech
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
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
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.