Eric Sun: Understanding brain aging at spatial and single-cell resolution with machine learning

Eric D. Sun illuminates the revolutionary intersection of machine learning and aging biology, which promises to transform our understanding of brain aging at an unprecedented single-cell resolution. Emerging from Stanford University's Biomedical Data Science program, Eric Sun is set to establish his independent laboratory at MIT's Department of Biological Engineering and the Ragon Institute in 2026. He represents the vanguard of computational scientists redefining aging research through innovative artificial intelligence approaches. His groundbreaking development of spatial aging clocks, sophisticated machine learning models capable of measuring biological age at the cellular level, has unveiled previously hidden mechanisms of brain aging, including the remarkable discovery of cell types that can dramatically influence the aging trajectory of neighboring cells in both pro-aging and pro-rejuvenating directions. This pioneering work, recently published in Nature (2025), bridges the gap between computational innovation and biological discovery, positioning Eric Sun at the forefront of a new era in aging research where machine learning not only decodes the complex biology of aging but also accelerates the discovery of targeted interventions against age-related diseases, including dementia. Through this compelling Genomic Press Interview, readers gain intimate insights into the scientific journey, philosophical perspectives, and ambitious vision of a rising star whose multidisciplinary approach promises to unlock the secrets of healthy brain aging and translate these discoveries into transformative therapeutics for humanity's most pressing age-related challenges.