# Kejun (Albert) Ying: Autonomous AI Agents, Decoding Aging

Page: https://stenobird.com/podcast/galaxy-balance-7619530/kejun-albert-ying-autonomous-ai-agents-decoding-aging
Text version: https://stenobird.com/podcast/galaxy-balance-7619530/kejun-albert-ying-autonomous-ai-agents-decoding-aging.md
Podcast: [Galaxy Balance](https://stenobird.com/podcast/galaxy-balance-7619530)
Published: 2026-02-16T21:30:00+00:00
Episode link: https://api.riverside.com/hosting-analytics/media/8ccfc9bb99a4cae9f60a8c2bcfa39aedde77535c797f665f0292227c1b816a1b/eyJlcGlzb2RlSWQiOiI4NzgzYmZiZC03MGU1LTRlYTMtOTlkNi04NjRlZmQxNTg1MzgiLCJwb2RjYXN0SWQiOiJjMGE0YjQ3Yi1iMmM5LTRjNjgtODhiNS0xYmFhM2EzNTJjODMiLCJhY2NvdW50SWQiOiI2OTBiYjRiMzM2NjY3MWFlZGQwZTZhMTEiLCJwYXRoIjoibWVkaWEvY2xpcHMvNjk4MTJiZjAzY2I0MTc3NjVkMWQ4OTAxL2Nvcnktc21pdGhzLXN0dWRpby1sTktuWC1jb21wb3Nlci0yMDI2LTItMl9fMjMtNTctNTIubXAzIn0=.mp3
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JSON: https://stenobird.com/v1/public/podcasts/galaxy-balance-7619530/episodes/kejun-albert-ying-autonomous-ai-agents-decoding-aging
Duration seconds: 3687

## Resource

In this episode of Galaxy Balance, Cory Smith sits down with Kejun (Albert) Ying, a computational biologist and aging researcher working at the intersection of AI, protein design, and longevity science. Albert's work spans designing novel proteins never seen in nature, applying large-scale AI models to millions of RNA-seq samples, and uncovering potential anti-aging effects hidden in existing drugs. Splitting his time between the Baker Lab at the University of Washington and the Vies-Carre Lab at Stanford, Albert brings a rare systems-level perspective on how computation, biology, and experimentation can converge to tackle aging as an engineering problem. The conversation explores why aging became his central focus, how AI is reshaping biological discovery, and what it might take to meaningfully extend human healthspan. 00:00 - The integrated future of AI in daily life and science 02:19 - Introduction to Albert Ying’s background and research 04:17 - Inspiration from Aubrey de Grey and shifts toward computational biology 07:37 - Challenges with longitudinal aging data 11:16 - Large-scale analysis with AI for aging interventions 14:23 - Validation and regulatory pathways for aging biomarkers 14:43 - The concept of autonomous AI agents in scientific discovery 16:23 - How foundation models learn biology and their limitations 18:07 - The impact of protein structure prediction tools like AlphaFold 22:51 - Next steps after identifying promising aging interventions 27:21 - The vision of AI operating seamlessly in background science infrastructure 31:25 - The vision and mechanics of decentralized science with Avanasi Labs 36:39 - Data privacy, security, and ethical considerations for decentralized platforms 40:03 - Rethinking aging for better data collection and understanding 4…

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