Co-Founder & CTO @k_dense_ai | Ph.D. in Bioengineering. Previously @biostateai, @matterworks_bio, @MIT, @GeorgiaTech.

Palo Alto, CA
Joined December 2020
Timothy Kassis retweeted
Today, we’re announcing an open call for guest investigators in life sciences. Over 8–12 weeks, guest investigators will work directly with my team and other Anthropic researchers to produce analyses and tools for their work. We’ll run our models and harnesses, at no cost to them. We’ll work together to open-source the resulting data, artifacts, and code, and write preprints about what we find. We want humans to remain at the center of scientific discovery, deciding what questions to pursue, and how to pursue them. Those decisions are not ours to make alone. This open call is part of our ongoing efforts at Anthropic to support researchers and accelerate scientific discovery. I’m looking for principal investigators and their research groups at academic institutions, nonprofits, or government labs, working in causal human biology, structural and computational molecular biology, medicinal chemistry, drug discovery, and clinical science. Applications are open for about 14 days: anthropic.com/news/open-call…
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Timothy Kassis retweeted
We're significantly expanding access to Gemini for scientists via antigravity - sign up now! Top of mind question for scientists on data retention - please turn off telemetry if you'd like. docs.google.com/forms/d/e/1F…
Excited to launch Gemini 4 Argon, designed to help with hardest coding and knowledge work tasks with its frontier capabilities.. For developers and enterprises, it’s available in the paid tier of the Gemini API and the Gemini platform, for Ultra subscribers in Google Antigravity, and Ultra and Pro subscribers in the Gemini app and Search. Read more: blog.google/innovation-and-a…
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Timothy Kassis retweeted
Bridging in silico research with real-world lab work. At K-Dense, we’re excited about our partnership with Litmus Science, giving AI agents the power to generate experimental plans and have them executed in professional labs. This is a major step toward end-to-end automated science. Learn more about this innovation in our recent conversation with Logan Lawler on #ReshapingWorkflows: reshaping-workflows.simpleca…
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Timothy Kassis retweeted
Same cells, same genes, same FDR cutoff: 8,554 hits or 6,186, depending only on whether the test counts a cell or a donor as the replicate. We re-tested Kang 2018 with K-Dense Web. The biology holds; 2,632 cell-level-only effects don't. Full write-up below 👇
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Timothy Kassis retweeted
Watched Jon Stewart's Daily Show segment on AI this morning and couldn't stop thinking about his question: what does the public actually get out of all this? So I wrote this (with AI's help, of course). If AI wants our trust, it should cure something. k-dense.ai/blog/ai-should-cu…
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Timothy Kassis retweeted
In today’s research landscape, scientific data comes from everywhere and in every possible format. At K-Dense, we built Scientific Agent Skills, our open-source library, to help AI agents access, aggregate, and harmonize disparate research sources for seamless discovery. Proud to share more about this innovation in a recent conversation between @TimothyKassis and Dell's Logan Lawler on #ReshapingWorkflows reshaping-workflows.simpleca…
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Timothy Kassis retweeted
K-Dense BYOK is your free open-source AI co-scientist running on your computer. Claude Science but much more powerful and customizable.
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Timothy Kassis retweeted
New in K-Dense BYOK: /prove-verify Parallel investigators attack an open question, adversarial verifiers check every draft, and a ledger tracks what's verified and what's ruled out, round by round. And set a verifier model so a different model checks the work. github.com/K-Dense-AI/k-dens…
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Timothy Kassis retweeted
Excited to share our most recent paper from @k_dense_ai lead by @ambrueckner describing K-Dense BYOK. A free AI co-scientist that runs on your desktop. We released this 7 months ago and now it is packed with features focused around scientistic workflows based on conversations with scientist from academia, government and industry. 🧵 arxiv.org/abs/2610.00074
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Timothy Kassis retweeted
Our paper on K-Dense BYOK is live on arXiv! In our evaluation, K-Dense BYOK outperformed the scientific harnesses we tested on scientific quality and research execution. It also maintains full research provenance through a hash-chained lab notebook, so every result traces back to an auditable record. arxiv.org/abs/2610.00074
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Timothy Kassis retweeted
Today we're open-sourcing LabMCP: connectors that let AI assistants run your lab instruments. Balances, stirrers, pumps, spectrometers, potentiostats and more. 32 connectors, 411 tools, with safety limits and a full command log.
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Timothy Kassis retweeted
I've been noodling with CompBioBench for the last couple of weeks and am impressed that our Gemini 3.8 run landed so high. The power of a good harness! 🦾
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Timothy Kassis retweeted
Reporting checklists have existed for years. Checking a paper against them is still slow, so it rarely happens. Today we're releasing Rigor Scan: a free reporting check for papers, built on Jev by @typesafeai. Drop in a PDF, get results in seconds. k-dense.ai/tools/rigor-scan
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Timothy Kassis retweeted
I'm excited to announce CASMI 2026, the blind challenge hosted by @enveda on Kaggle to address one of the grandest challenges in life science: can you tell the structure of a small molecule from its mass spectrum? kaggle.com/competitions/enve…
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Timothy Kassis retweeted
Thank you to all for sharing and using our scientific-agent-skills repo, which hit 40k stars this weekend!
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Timothy Kassis retweeted
Introducing K-Bench 01. A new private benchmark composed of 178 end-to-end scientific tasks. Read the pre-print: arxiv.org/abs/2608.21601
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Timothy Kassis retweeted
Today, we're excited to share early progress on using Gemini to accelerate scientific discovery in the real-world. We present an extension of Co-Scientist which we use to collaborate with scientists across materials science, biology, and computer science.
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Timothy Kassis retweeted
Introducing BioSecBench-Function, a verifiable benchmark for testing whether AI agents can infer the functional properties of viruses, bacteria, and toxins from data. Opus 5 with Claude Code leads in endpoint pass rate (50.4%), while Grok 4.6 with Grok Build leads in overall pass rate (44%) when refusals are counted as failures. The benchmark contains 111 deterministic evaluations spanning viral, bacterial, and toxin systems. It covers five primary threat axes: transmissibility, immune escape, virulence or toxicity, drug resistance, and persistence or fitness. Each evaluation is grounded in a published study or dataset and reviewed by domain experts. Tasks draw on deep mutational scanning, Tite-Seq, surface plasmon resonance, X-ray crystallography, free-energy calculations, and related assays. Agents receive the relevant data and produce structured answers graded against study-derived ground truth.
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