Longevity x AI Hackathon Winner Breakdown

What made us love the teams enough to give away $7k in prizes!

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Jul 08, 2025

This post is a follow-up to the Longevity x AI $10k Hackathon, going in depth for WHY sharing these longevity-focused biological datasets is critical, and why judges loved the teams we picked. The goal of the hackathon was to upload as many high-quality longevity-related datasets (preferably from Karl & Francesco’s curated list) to HuggingFace, a widely used AI dataset and model platform.

Check out our longevity-db HuggingFace organization for all the uploaded datasets from the Hackathon. Amazingly, some of the datasets already have ~100 downloads after being online for only few weeks! How cool! It feels great that we’re already making an impact on the field with this work.

1st Place: Longevity-genie ($4k)

This team went for quality over quantity, and the judges noticed. We loved their clean, well documented repositories (both code and data!), and importantly, these datasets also loaded with the HuggingFace datasets API! Amazingly, this team also won another hackathon in Berlin the same weekend! I’m so impressed!

Team members

skeletal-muscle-atlas

As muscle is a clear biomarker of aging, with grip strength and ease of building muscle declining with age, we need to understand what’s happening at the molecular level so we can design effective interventions to prevent muscle loss.

aging-fly-cell-atlas

Aging of a whole organism across life is a HUGELY valuable dataset! However, obtaining such a valuable dataset from humans is extremely labor-intensive and for now, we’ll settle for using the fruit fly (Drosophila) as a model. While we’re not flies, we share many similar basic mechanisms like cell division, which tends to break down with age. By making this dataset accessible to the broader AI/ML community, we can learn how aging is a systemic process that affects whole body systems, which systems are most affected, and where can we best intervene.

2nd Place: CellVPA ($2k)

CellVPA did a great job of preparing the data, having beautiful READMEs, and showing their work with their processing scripts. Thank you, CellVPA!

Team Members

human-optic-nerve-fibroblasts-snRNAseq

The eye is extremely susceptible to age-related degeneration, and its senescence can lead to glaucoma which is the leading cause of irreversible blindness. A single-cell RNA-seq dataset describing the intricate cell types of the eye is crucial to prevent eye aging.

human-muscle-aging-atlas-snRNAseq

Aging muscle is a popular dataset! This team also used the same Human Skeletal Muscle cell atlas as longevity-genie, and I think it’s great to have the dataset uploaded multiple times. This team did a nice job of giving instructions to ML engineers for how to use the data.

mouse-muscle-aging-atlas-snRNAseq

More aging muscle! This time in mouse, which means that the data is much more controlled, and researchers can really dig into the aging signal specifically, and not have as many confounding variables as in human like lifestyle choices.

3rd Place: Florian De Rop ($1k)

3rd place went to a team of one! Florian had a major push with great data processing scripts, and data that loaded on the HuggingFace API. Way to go!

terekhova2023

This dataset from blood of individuals aged 25-85 will have the easiest application towards diagnostics and biomarkers for aging. As peripheral blood mononuclear cells (PBMCs) are the easiest tissue to biopsy, this dataset will be immensely useful for researchers who want to find genes that change across age, and quantitatively measuring their difference after a longevity intervention.

riken2018

Also from blood, this dataset features samples from supercentarians (ages 110+!) and younger controls. What an amazing opportunity to learn from what are some positive biomarkers of aging for the healthy elderly! I’m really excited for what people do with this dataset.

All high-quality datasets

Here are all the HuggingFace datasets that the judges rated favorably, regardless of team. Enjoy training models on them!

A guest post by

Olga Botvinnik

Founder/CEO, Seanome. Peppy computational biologist

Seanome’s Substack

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