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.
News
Sept 2024 Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why
Apr 2024 Our paper ``Deuteration removes quantum dipolar defects from KDP crystals’’ appears on Arxiv! (link). State-of-the-art path-integral MD simulation brings new stories of materials that have been intensively studied but never fully understood.
Mar 2024 Our paper ``Ab Initio generalized Langevin equation’’ is published by PNAS (link).
Mar 2024 I give a talk on ab initio generalized langevin equation (AIGLE) in 2024 APS March Meeting at Minneapolis.
Open-Source Statement
I advocate data&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 do so and reduce statements like “** available upon reasonable requests” in publications.
Software Development
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.