I am a Research Assistant Professor in the Department of Physics at HKUST. As a computational scientist, my research focuses on developing and applying computational methods (e.g., machine learning and molecular dynamics simulations) to understand and predict the behavior and properties of matter at atomic scales, with an emphasis on ice nucleation, aqueous carbon reactions, and hydrocarbon formation. Through my doctoral and postdoctoral work, I have uncovered non-classical nucleation pathways, elucidated reaction kinetics using advanced modeling techniques, and explored the roles of intermolecular interactions in self-assembly. Leveraging machine learning techniques and ab initio molecular dynamics, I am currently investigating the physical properties of nanoconfined water, reaction kinetics of deep Earth hydrocarbons, and the electronic and transport characteristics of two-dimensional materials. My multidisciplinary research aims to advance our fundamental understanding of matter at the atomic scale with potential applications across various scientific and engineering domains.