Efficient, Interpretable Atomistic Graph Representation for Angle-Dependent Spectroscopic Prediction

Speaker: Tim Hsu, Lawrence Livermore National Laboratory

Abstract


Bio
Dr. Tsu received his PhD Carnegie Mellon University in Materials Science and Engineering in 2019. In collaboration with the National Energy Technology Laboratory, his study focused on commercially fabricated solid oxide fuel cell electrode microstructures. He stayed at CMU as a postdoctoral researcher before moving to the Lawrence Livermore National Laboratory to work on scientific machine learning for molecular dynamics and density functional theory simulations.