
phd student @berkeley_ai! research in ai for autonomous scientific discovery and to advance genetics one day i will start tweeting more
Berkeley, California
Joined February 2019
- Tweets21
- Following825
- Followers85
- Likes5.4K
Marçal Comajoan Cara retweeted
If interested in applying our algorithms yourself, use our fast, user-friendly package snputils!
snputils.org/
(biorxiv.org/content/10.64898…)
Also see our recent 2026 papers,
Gnomix (most accurate local ancestry inference on the market!)
nature.com/articles/s41467-0…
Adamixture (fastest unsupervised genetic clustering!)
academic.oup.com/bioinformat…
ARGformer (PCA/umap for args!)
academic.oup.com/bioinformat…
ARGMix (graph transformers now allowing ancient local ancestry inference!)
biorxiv.org/content/10.64898…
And our github for more techniques!
github.com/ai-sandbox
Marçal Comajoan Cara retweeted
My group's paper out on the cover of Science!
Native Hawaiians are most closely related to the Rapanui of distant Easter Island 😮
Proud of it my students, the two co-first authors Cole Shanks & former MS student @edwardhuangc, and 3rd author @chrisoutho.
science.org/eprint/4HAYG3KTP…
Marçal Comajoan Cara retweeted
ARGformer is out in Bioinformatics!
doi.org/10.1093/bioinformati…
Just as PCA produces a low-dimensional representation of population structure from genotypes, ARGformer can do this now for ARGs...a representation that comes now directly from inferred genealogical topologies & at a haplotype level across each individual's genome.
We do this by turning local genealogical paths into tokens & learning dense embeddings, similar to language embeddings, to visualize, cluster & query.
Code
github.com/AI-sandbox/ARGfor…
Team
@d_bonet, Cole Shanks, @marcal_cc, @jordiatjhu
Marçal Comajoan Cara retweeted
Replying to @d_bonet
@d_bonet and @marcal_cc representing the lab at the #KDD2026 conference in Korea @kdd_news, presenting their iLTM paper!
We just presented iLTM, our Integrated Large Tabular Model with @marcal_cc at #KDD2026 in Jeju! 🇰🇷 @kdd_news
More info on iLTM on the thread below👇🏼
Marçal Comajoan Cara retweeted
We just presented iLTM, our Integrated Large Tabular Model with @marcal_cc at #KDD2026 in Jeju! 🇰🇷 @kdd_news
More info on iLTM on the thread below👇🏼
Excited to share our preprint on iLTM: an Integrated Large Tabular Model!
arxiv: arxiv.org/abs/2511.15941
No single technique consistently excels across all tabular tasks. iLTM addresses this by integrating distinct paradigms in a single architecture:
- Gradient Boosted Decision Trees (GBDT)-based embeddings
- Robust preprocessing with random feature projections
- A meta-trained hypernetwork
- Retrieval augmentation with Soft Nearest Neighbors
@d_bonet @marcal_cc @alexGioannidis
(1/N)
Marçal Comajoan Cara retweeted
Some data isn't fit for LLMs, especially many biomedical datasets & anything using spreadsheets.
Large Tabular Models (LTMs) are the way to go!
Our new LTM (iLTM accepted
#KDD2026) is now literally in the dictionary! Thanks @MerriamWebster!
merriam-webster.com/dictiona…
Marçal Comajoan Cara retweeted
Replying to @d_bonet
@d_bonet is presenting ARGformer tonight at #PEQG26!
We released ARGformer this winter bc ARGs are huge & hard to use. It turns local genealogical paths into tokens & learns dense embeddings, similar to language embeddings, to visualize, cluster & query.
biorxiv.org/content/10.64898…
Marçal Comajoan Cara retweeted
Working on AI for cancer? Sorry, I can't help you.
Working on AI for Alzheimer's Disease? Sorry, I'm becoming a bit dumb when it comes to the AI part of it.
Why don't everyone stop trying to do AI for Science & Tech? We can do it all gradually. You just have to be patient.
Marçal Comajoan Cara retweeted
People have been insufficiently harsh in pushing back on this morally bankrupt opinion.
We should be doing everything we can to automate cancer research faster.
The point is to save lives, not to create make-work for scientists.
I was at an event on AI for science yesterday, a panel discussion here at NeurIPS. The panelists discussed how they plan to replace humans at all levels in the scientific process. So I stood up and protested that what they are doing is evil. Look around you, I said. The room is filled with researchers of various kinds, most of them young. They are here because they love research and want to contribute to advancing human knowledge. If you take the human out of the loop, meaning that humans no longer have any role in scientific research, you're depriving them of the activity they love and a key source of meaning in their lives. And we all want to do something meaningful. Why, I asked, do you want to take the opportunity to contribute to science away from us?
My question changed the course of the panel, and set the tone for the rest of the discussion. Afterwards, a number of attendees came up to me, either to thank me for putting what they felt into words, or to ask if I really meant what I said. So I thought I would return to the question here.
One of the panelists asked whether I would really prefer the joy of doing science to finding a cure for cancer and enabling immortality. I answered that we will eventually cure cancer and at some point probably be able to choose immortality. Science is already making great progress with humans at the helm. We'll get fusion power and space travel some day as well. Maybe cutting humans out of the loop could speed up this process, but I don't think it would be worth it. I think it is of crucial importance that we humans are in charge of our own progress. Expanding humanity's collective knowledge is, I think, the most meaningful thing we can do. If humans could not usefully contribute to science anymore, this would be a disaster. So, no. I do not think it worth it to find a cure for cancer faster if that means we can never do science again.
Many of those who came up to talk to me last night, those who asked me whether I was being serious or just trolling, thought that the premise was absurd. Of course there would always be room for humans in science. There will always be tasks only humans can do, insight only humans have, and so on. Therefore, we should welcome AI. Research is hard, and we need all the help we can get. I responded that I hoped they were right. That is, I truly hope there will always be parts of the research process which humans will be essential for. But what I was arguing against was not what we might call "weak science automation", where humans stay in the loop in important roles, but "strong science automation", where humans are redundant.
Others thought it was immature to argue about this, because full science automation is not on the horizon. Again, I hope they are right. But I see no harm in discussing it now. And I certainly don't think we need research on science automation to go any further.
Yet others remarked that this was a pointless argument. Science automation is coming whether we want it or not, and we'd better get used to it. The train is coming, and we can get on it or stand in its way. I think that is a remarkably cowardly argument. It is up to us as a society to decide how we use the technology we develop. It's not a train, it's a truck, and we'd better grab the steering wheel.
One of the panelists made a chess analogy, arguing that lots of people play chess even though computers are now much better than humans at chess. So we might engage in science as a kind of hobby, even though the real science is done by computers. We would be playing around far from the frontier, perhaps filling in the blanks that AI systems don't care about. That was, to put it mildly, not a satisfying answer. While I love games, I certainly do not consider game-playing as meaningful as advancing human knowledge. Thanks, but no thanks.
Overall, though, it was striking that most of those I talked to thanked me for raising the point, as I articulated worries that they already had. One of them remarked that if you work on automating science and are not even a little bit worried about the end goal, you are a psychopath. I would add that another possibility is that you don't really believe in what you are doing.
Some might ask why I make this argument about science and not, for example, about visual art, music, or game design. That's because yesterday's event was about AI for science. But I think the same argument applies to all domains of human creative and intellectual expression. Making human intellectual or creative work redundant is something we should avoid when we can, and we should absolutely avoid it if there are no equally meaningful new roles for humans to transition into.
You could further argue that working on cutting humans out of meaningful creative work such as scientific research is incredibly egoistic. You get the intellectual satisfaction of inventing new AI methods, but the next generation don't get a chance to contribute. Why do you want to rob your children (academic and biological) of the chance to engage in the most meaningful activity in the world?
So what do I believe in, given that I am an AI researcher who actively works on the kind of AI methods used for automating science? I believe that AI tools that help us be more productive and creative are great, but that AI tools that replace us are bad. I love science, and I am afraid of a future where we are pushed back into the dark ages because we can no longer contribute to science. Human agency, including in creative processes, is vital and must be safeguarded at almost any cost.
I don't exactly know how to steer AI development and AI usage so that we get new tools but are not replaced. But I know that it is of paramount importance.
Marçal Comajoan Cara retweeted
Excited to share our preprint on iLTM: an Integrated Large Tabular Model!
arxiv: arxiv.org/abs/2511.15941
No single technique consistently excels across all tabular tasks. iLTM addresses this by integrating distinct paradigms in a single architecture:
- Gradient Boosted Decision Trees (GBDT)-based embeddings
- Robust preprocessing with random feature projections
- A meta-trained hypernetwork
- Retrieval augmentation with Soft Nearest Neighbors
@d_bonet @marcal_cc @alexGioannidis
(1/N)
Marçal Comajoan Cara retweeted
Replying to @marcal_cc
@marcal_cc
I think this idea is the future of AGI.
I want to apply t to LLMs and image generator latent space. Do you think its possible?
github.com/salcc/QuantumTran…















