The main goal of the Huang Lab is to develop new chemical theories to propel the advancements of AI for science, particularly in studying biomolecular dynamics. Research areas include elucidation of functional conformational changes in gene transcription, elucidation of molecular recognition and self-assembly, development of machine learning and Generalized Master Equation model for biomolecular dynamics, development of Integral Equation theories for solvation, and development of deep learning methods to predict protein-ligand and protein-RNA interactions.