My research focuses on developing structure-based computational strategies for antibody design. Computational approaches can overcome the time-consuming, costly, and imprecise nature of traditional experimental techniques, which often yield antibodies with suboptimal functionality and developability. Past methods fall short of matching the affinity and specificity of clinically-approved antibodies. My work aims to develop machine learning methods that design epitope-specific antibodies with improved binding properties.