People

Predicting mechanical strength of materials through theory and simulations of defect microstructures across scales. Developing new atomistic simulation methods for long time-scale processes and applying machine learning to materials research.

Researching metallurgical processes and modeling for metal additive manufacturing (3D printing).

Interests in multiscale computational mechanics, scientific machine learning, and inverse optimization. Focuses on data-driven methods for dislocation dynamics.

Researching mechanics of materials and microstructural evolution.

Researching rare events, accelerated kinetic Monte Carlo simulations, and mechanical behaviors of polymer networks using molecular dynamics.