Machine Learning And Computational Biology Intern
CurrentConducted preclinical data analysis of lead antibody drug candidates and developed models to predict their biochemical propertiesResponsible for:Developing an XGBoost Model to rank the hydrophobicity of antibody-drug conjugates in a data-limited setting that outperformed existing modelsDesigning a novel and validated pipeline to generate nanobody lead candidates using generative protein language modelsCreating software to automate SMILES string generation for drug-conjugated peptide linkers