Formulated a new machine learning (ML) inter-atomic force fields-based workflow using moment tensors and density functional theory (DFT) to discover stable non-volatile memory cells.
RAMP Computational Material Science Intern
Western Digital
Designed novel phase-change memory alloy interfaces using ML force fields that showed enhanced stability for over 10 ns.
Education
PhD Computational Modeling and Simulation
University of Pittsburgh
Thesis on Molecular Modeling with Atomistic Machine Learning Methods. Supervised by Prof Karl Johnson.