Nathan co-founded Ravel and secured its Seed funding in 2019. Nathan was the VP of Technology at Driver where he led the software engineering and R&D teams to develop a cfDNA assay for the identification of somatic variants. He was a contributing computational biologist in the Data Analysis group for the ENCODE and modENCODE projects resulting in publications in Science and Nature. Nathan received his PhD from UC Berkeley in biostatistics where he developed statistical methods for the analysis of functional genomic data under Peter Bickel. As a postdoc in Anshul Kundaje’s lab at Stanford, he developed deep learning models for the analysis of DNA-protein binding events. In his free time, he enjoys spending time with his family.