"Innovation requires imagining big, taking risks, and working hard together as a team."
I joined the Prescient Design team at Genentech in November 2021.
I work on developing and applying advanced machine learning methods to therapeutic protein design, with the goal of accelerating the generation of lead drugs with improved properties.
My area of focus is the development and application of machine learning methods for designing therapeutic antibodies. My research is directed at using machine learning systems to infer from data rules underlying antibody affinity, function, specificity, immunogenicity, and developability characteristics. Our team is leveraging available sequence and structure data and is applying state of the art predictive and generative machine learning models for producing candidates with in-silico optimized properties.