1. Machine learning amorphous solidsWe extracted new features from a coarse-grained amorphous system and applied support vector machine (SVM), convolutional neural network(CNN), PCA and t-SNE for classification, dimension reduction and regression.2. Shear response of amorphous solidsWe performed computer modeling of Molecular Dynamics (MD) simulations on amorphous system to study the shear response in different conditions. We connected the structure with mechanical properties.3.… Show more 1. Machine learning amorphous solidsWe extracted new features from a coarse-grained amorphous system and applied support vector machine (SVM), convolutional neural network(CNN), PCA and t-SNE for classification, dimension reduction and regression.2. Shear response of amorphous solidsWe performed computer modeling of Molecular Dynamics (MD) simulations on amorphous system to study the shear response in different conditions. We connected the structure with mechanical properties.3. management and maintenance of the clustersMaintain the self-built computing cluster of the laboratory and manage the submited jobs for computer simulation based on the LSF job scheduling system. Show less

Computational investigation of sheared amorphous systems using discrete element method (DEM):1. Numerical experiment using Fortran, Python, LAMMPS for Molecular Dynamics (MD) simulations2. Developed codes to study the Hessian Matrix of a jammed system3. Using machine learning methods to identify defects in bulk metallic glass

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