I’m an Alvarez Postdoctoral Fellow at Lawrence Berkeley National Laboratory. I received my PhD in Applied Math from the Program of Applied and Computational Mathematics at Princeton University, where I was advised by Roberto Car and Weinan E. You can find the complete list of my publications at Google Scholar, and my Curriculum Vitae here.
Research Summary
The central goal of my work is to consistently bridge physical models at different scales. This is similar to drawing “the bull” at different stages of abstraction.
See here for details.
Open-Source Statement
I advocate data and code sharing for all research works supported by non-profit grants and funding. I try my best to upload code, data, models, and even post-processing scripts to Github or permanent repos like Zenodo after the conclusion of a project. It is the responsibility of our generation to reduce statements like “** available upon reasonable requests” in publications.
Software Development
QEpsilon: Python package designed to minimize the effort required to build data-driven quantum master equation of an open quantum system and to perform time evolution of the master equation.
OpenFerro: Python package designed to minimize the effort required to build on-lattice Hamiltonian models, and to perform molecular dynamics (MD) and Landau-Lifshitz-Gilbert simulations.
AIGLETools: Python package designed to minimize the effort required to build ab initio generalized Langevin equation (AIGLE) & ab initio Langevin equation (AILE) models for multi-dimensional time series data.