I am generally interested in understanding the relationship between biological sequence, structure and function. Antibodies, as subtype of protein, play a crucial role in the life sciences such as immune system, basic research and therapeutics. Specifically, I study how the primary sequence of an antibody determines its structure and function. As graduate researcher, I have developed sequence-based deep learning models to study how the primary sequence of an antibody determines its function (specificity), and how changes in genetic information affect viral phenotypes. My previous works as the first author have been published in prestigious journals such as Immunity, Elife, etc. Since May 2022, I have been working at Genentech mainly on structure-based general protein function prediction model, targeting state-of-the-art protein function prediction. In the future, my research aims to develop a deep learning-based platform to guide rational antibody design that enables the co-generation of antibody sequences and structures while conditioning on the target epitope.