Summary
Ryo Yamamoto is a research scientist and Member of Technical Staff on Goodfire’s life sciences team, specializing in making biological foundation models interpretable and clinically useful. With a PhD in Bioinformatics from UCLA and eight years of experience spanning computational biology and CS, he has driven transcriptomics and aging research—most recently contributing to EVEE, an interpretable pathogenicity resource for 4.2M ClinVar variants covered in TIME. He combines statistical methods for RNA-seq, single-cell/long-read integration, and genetics-guided covariate inference to turn model representations into mechanistic hypotheses for disease. Comfortable moving between lab, clinic, and production ML, he brings a rare blend of academic depth and product-oriented impact from UC Berkeley to the University of Tokyo and SF Bay Area.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Arts - BA Computer Science, Bachelor of Arts - BA Computer Science at University of California, Berkeley
University of Tokyo
Japanese, English