Academic output
h-index and citation counts from OpenAlex, disambiguated by institution match, not just the highest-h-index same-named result.
Aging & longevity research, ranked with receipts
Every scientist, company, and conference here is scored across five dimensions: academic output, genuine discoveries, drug discovery, funding raised, and a speculative LLM-estimated lifespan-extension impact. Every claim links to a source. Every score shows its caveats.
Why this exists
Longevity has plenty of "top people" lists. Almost none of them show their work, or agree with each other.
This portal starts from seven public directories (agingbiotech.info, the Unfiltered Longevity 100, the Who's Who in Gerontology and Biology of Ageing, and others), merges duplicate entries across sources, then runs independent research on every claim: real h-index and citation counts, specific attributed discoveries, verified drug pipeline stages, cross-checked funding figures, and a clearly-labeled speculative LLM-ensemble estimate of long-run impact.
Where we found the source directories were wrong or stale, we say so, in the open, with the correction and its source. This dataset grows and re-verifies itself over time rather than shipping once and going stale.
Methodology
We don't collapse five very different kinds of evidence into one silent number. Each dimension is shown side by side; you can sort by whichever matters to you. Full methodology write-up is linked in Sources below.
h-index and citation counts from OpenAlex, disambiguated by institution match, not just the highest-h-index same-named result.
Specific, citable findings mapped to a 100-area taxonomy. A tag without a cited discovery doesn't count.
Real pipeline stage, cross-checked against company sites, ClinicalTrials.gov, and press coverage, not just "affiliated with a biotech."
Total raised and market cap, independently verified and dated. Several source-directory figures turned out to be materially stale.
A frontier-model estimate of projected lifespan-extension impact, shown with its range and explicitly marked as speculative, never as measured fact.
Every figure links to where it came from. Where we corrected a source directory, the correction and its evidence are shown, not hidden.
The explorer
Switch between scientists, companies, and conferences. Every row expands into its full evidence drawer: score breakdown, source links, and any corrections we made to the original directory listing.
Reading this responsibly
Someone with no listed drug-discovery output may simply be a theorist or basic-science researcher, that's an honest "not applicable," not a low score.
Some Tier 1 names are on multiple lists because they're prominent communicators or investors, not because they're the most scientifically productive. We tag career type explicitly rather than force everyone into a "researcher" mold.
It's one (or a few) models' speculative extrapolation, shown with range and caveat. Treat it as a conversation starter, not a forecast.
h-index and citations correlate with career length and subfield size as much as with breakthrough impact. We show recency-weighted figures where available to partially correct for this.
It re-scrapes, re-verifies, and grows over time. Corrections we've already made are shown in the open specifically so you can judge our error rate, not just our conclusions.
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Beyond the rankings
Communities, news outlets, and investor networks that don't fit neatly into scientist/company/conference but shape the field's information flow.
Where this comes from
Two of the seven originally-requested sources were excluded on principle: Expertscape's robots.txt explicitly disallows automated access to its rankings, and aging-atlas.org turned out to be an unrelated commercial directory whose terms of service prohibit automated scraping. Both are documented, not silently skipped.
Full scoring methodology, the 100-area research taxonomy, and per-entity research files (including every "researcher_notes" caveat) are available in the project repository.