Dr. Kejun (Albert) Ying
Kejun (Albert) Ying, Ph.D. is an F99K00 Postdoctoral Fellow at Stanford University in the Wyss-Coray Lab and the University of Washington’s Institute for Protein Design in the Baker Lab, with over 6 years of experience in aging biology and computational research.
He currently serves as Cofounder of Avinasi Labs and is a Core Member of the Biomarkers of Aging Consortium. His groundbreaking contributions include developing the first causal inference-based aging clock, featured on the cover of Nature Aging in 2024, creating ClockBase — a platform that integrates over two million biological age data samples, and developing MethylGPT, recognized by Eric Topol in Science as one of the most promising large biomedical models.
In January 2025, Albert joined Tony Wyss-Coray’s lab at Stanford University and David Baker’s lab at the Institute for Protein Design as an F99K00 Postdoctoral Fellow, merging aging biology with protein design to tackle neurodegeneration. His research focuses on developing de novo disaggregases to combat protein aggregation in neurons and building advanced aging clocks and foundation models for proteomic data.
In 2024, he received a perfect Impact Score of 10 for his NIH F99/K00 application, one of the highest honors in competitive research funding. His postdoctoral work is uniquely co-mentored by Dr. Tony Wyss-Coray, known for discovering how circulatory blood factors modulate brain function, and Dr. David Baker, who won the 2024 Nobel Prize in Chemistry for computational protein design. Read Aging biomarkers and the measurement of health and risk – PubMed.
Albert developed MethylGPT, a transformer-based foundation model trained on 226,555 human methylation profiles spanning diverse tissue types from 5,281 datasets, processing 7.6 billion training tokens. The model demonstrates robust methylation value prediction, with a Pearson correlation of 0.929, and maintains stable performance even with up to 70% missing data. When fine-tuned for mortality and disease prediction across 60 major conditions using 18,859 samples from Generation Scotland, MethylGPT achieved robust predictive performance, demonstrating significant potential for clinical applications.
His ClockBase platform features biological age estimates based on multiple aging clock models applied to more than 2,000 DNA methylation datasets and nearly 200,000 samples. The platform has facilitated the discovery of novel anti-aging drug candidates, including zebularine, which reduces biological age estimates across all tested aging clock models. Read ClockBase: a comprehensive platform for biological age profiling in human and mouse and MethylGPT: a foundation model for the DNA methylome – PMC.
At Harvard, working with Dr. Vadim Gladyshev, Albert performed an epigenome-wide Mendelian Randomization on 20,509 CpG sites causal to eight aging-related characteristics. He created three models: CausAge, a general clock predicting biological age based on causal DNA factors, and DamAge and AdaptAge, which include only damaging or protective changes. Testing on 4,651 individuals from the Framingham Heart Study and the Normative Aging Study showed that DamAge correlated with adverse outcomes, including mortality, while AdaptAge correlated with longevity. Read Looking to rewind the aging clock and Causality-enriched epigenetic age uncouples damage and adaptation.
As Cofounder of Avinasi Labs since January 2025, Albert leads a platform fostering collaboration and data sharing to overcome fragmented data and funding barriers in longevity science. The company focuses on building the AI-Native Chain for Longevity, pioneering novel approaches to global data collection and clinical trials through decentralized protocols across pop-up cities.
He co-leads the Biomarkers of Aging Challenge, an open competition leveraging DNA methylation datasets from 500 individuals aged 18 to 99 to develop novel models predicting chronological age, mortality, and multi-morbidity. The challenge has driven significant advances in biomarker accuracy compared to existing models through advanced machine learning techniques and biological knowledge integration. Read An Open Competition for Biomarkers of Aging.
Albert earned his Ph.D. in Biological Sciences in Public Health from Harvard Medical School in 2025, with his dissertation titled On the Quantification of Aging under the supervision of Dr. Vadim Gladyshev. His dissertation advisory committee included Dr. Brendan Manning, Dr. David Sinclair, and Dr. Shamil Sunyaev. He earned his Master’s degree in Computational Science and Engineering from the Harvard John A. Paulson School of Engineering and Applied Sciences in 2024.
He earned his Bachelor’s degree in Life Science from Sun Yat-sen University in 2019, graduating from the Yan-Sen Honor School Program, representing the top 0.5% of students. During his undergraduate years, he conducted research at multiple prestigious institutions, including UC Berkeley, the Buck Institute for Research on Aging, and the University of Washington. Watch On the Quantification of Aging | Kejun (Albert) Ying | Harvard PhD Defense Seminar.
Albert has published extensively in high-impact journals, with his work featured in Nature Aging. Nature Reviews Genetics, Nature Medicine, Nature Communications, and Nature Metabolism. His publication on centenarian loss-of-function mutations revealed longevity genes through depletion analysis of germline mutations.
He has presented at major conferences, including the Keystone Symposia, the Global Congress on Aesthetic and Anti-Aging, and the Aging Research and Drug Discovery conference. In 2023, he received the Best Poster Award at the Inaugural Biomarker of Aging Symposium, and in 2022, he won the Best Poster Award at the Gordon Research Conference on Systems Aging. Read Biological science student answers top questions on ageing.
As President of Harvard’s Interdisciplinary Discussion on Disease and Health from February 2024 to May 2025, Albert created a platform for graduate students to engage in cross-disciplinary discussions on disease-related topics. The organization brought together students from medicine, public health, biological sciences, and engineering to share research and foster collaboration across domains. He has mentored numerous students, including Ali Doga Yucel, Siyuan Li, Hanna Liu, Donghyun Lee, and Yikun Zhang, and has served as an instructor for the Harvard Public Health Symposium for Young Generation.
Born in Fuzhou, China, Albert was initially drawn to physics and the exploration of the universe, inspired by scientists like Albert Einstein. His interest shifted to biological sciences after contemplating mortality, leading him to think, “Maybe people don’t have to die if they don’t want to”.
He appreciates his hometown’s scenic mountains, delectable food, and rich tea-drinking culture. Albert continues to advocate for public awareness of aging research, believing it’s never too early to start thinking about the aging process. Read MethylGPT: a foundation model for the DNA methylome and ClockBase: a comprehensive platform for biological age profiling.
Visit his Homepage, LinkedIn profile, Google Scholar page, and Stanford Profile. Follow him on Facebook, GitHub, ResearchGate, and X.