Zhengji joined the NERSC Division after working for three years as a postdoc in the Computational Research Division's Scientific Computing Group. In SCG she developed two new methods for computational nanoscience: the linear scaling 3D fragment (LS3DF) method for large-scale electronic structure calculations, and a new motif-based Hessian matrix method to estimate a preconditioner for nanostructures, which speeds up the convergence of atomic relaxation by at least a factor of four. Zhengji received her Ph.D. in computational physics from New York University for developing the reduced density matrix (RDM) method for electronic structure calculations, a highly accurate alternative to wavefunction-based computational chemistry methods.
Research Paper
Parallel Applications
Performance Analysis and Optimization
Performance Tools