
Jarod Rutledge
Scientific omnivore applying AI to molecular medicine for longevity
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Joined January 2026
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Summary
Jarod Rutledge is an interdisciplinary scientist and entrepreneur with a focus on longevity, neuroscience, and AI. He leverages multi-omics and advanced imaging data, combined with AI, to develop predictive tools for drug discovery and to understand the mechanisms of aging. His work aims to bridge the gap between cutting-edge research and real-world applications in health and life extension. amaranth+3
He plays a significant role in investment and strategic leadership within the longevity and biotechnology sectors. As Director of Biotechnology and Life Sciences at Starbloom Capital, he funds pioneering projects in frontier biotechnology and AI. Concurrently, as Longevity Lead at Amaranth Foundation, he dedicates himself to solving critical challenges in longevity and AI safety research, aspiring to accelerate healthy life extension. amaranth+2
His academic background includes a Ph.D. in Genetics from Stanford University, where his research focused on developing novel methods to measure aging using proteomics. He furthered his expertise as a Bridging Excellence Junior Fellow at EMBL and Stanford, applying computer vision and AI to image cell sorting for functional genomics and cell biology. His work in these areas has been published in high-impact journals like Nature. stanford+4
Jarod has an entrepreneurial drive, evidenced by his role as an Academic Co-Founder of Teal Omics, a company commercializing his research on organ aging signatures. He also serves as a board observer or director for several biotechnology companies including Cognito Therapeutics, LIfT BioSciences, MagIC Lifescience, Bexorg, Inc., and Cyclarity Therapeutics, indicating his involvement in guiding and supporting emerging ventures in the life sciences. nature+3
Work
Education
Writing
Organ aging signatures in the plasma proteome track health and disease
December 1, 2023A research paper co-authored by Jarod Rutledge that utilized machine learning models and human blood plasma proteins to measure organ-specific aging differences in living individuals, providing a method to predict diseases and aging effects.
Measuring biological age using omics data
January 1, 2022A review article co-authored by Jarod Rutledge discussing methods to measure biological age using omics data.
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