Camilo Ruiz
@_camiloruiz
PhD @Stanford with @jure | AI for Biology | Previously @MIT, @Gates_Cambridge, @Cambridge_Uni
Can deep learning work on small data with far more features than samples? We present PLATO: a method that achieves the state-of-the-art on such datasets by using prior domain information! neurips.cc/virtual/2022/p… 🧵 Published in #NeurIPS2023 with @ren_hongyu @kexinhuang5 @jure
Sir Demis sharing at the Google IO stage: - AI Co-scientist - our OG @GoogleDeepMind Gemini agents for accelerating scientific discovery and helping finding cures for complex diseases (acute myeloid leukemia, liver fibrosis and counting) - AMIE - our research AI doctor system…
Happy to share that our work on POPPER — an AI agent for autonomous scientific hypothesis validation — has been accepted to #ICML2025! I’ll be presenting during the poster session this Thursday at 4:30pm — come say hi if you’re around! ⬇️
🧪 Introducing POPPER: an AI agent that automates hypothesis validation by sequentially designing and executing falsification experiments with statistical rigor. 🔥POPPER matched PhD-level scientists on complex bio hypothesis validation - while reducing time by 10-fold! 🧵👇
🧬 Excited to open-source Biomni! With just a few lines of code, you can now automate biomedical research with AI agent! We are releasing Biomni A1 (agent) + E1 (env) with 150 specialized tools, 59 databases, and 105 software. E1 is our first attempt at curating the bio-agent…
🚀 Excited to open-source our general-purpose biomedical AI agent Biomni. Biomni A1 (agent) + E1 (env) with 150 specialized tools, 59 databases, and 105 software! With just a few lines of code, you can now automate complex biomedical research with AI agent! E1 only scratches…
Excited to share Biomni's @ProjectBiomni first blog post with Anthropic AI @AnthropicAI ! More use cases coming soon. Try it free at biomni.stanford.edu anthropic.com/customers/biom…
🤝Excited to announce @ProjectBiomni × @AnthropicAI! AI agents are set to transform how biologists do everyday research. Thanks to this partnership, the platform is now free for scientists worldwide: biomni.stanford.edu Learn more: anthropic.com/customers/biom…
Very interesting to see RL+open source LLM > frontier lab LLM on specialized genomic reasoning task great demonstration of a recipe to build expert-level bio reasoning model! Congrats @YuanhaoQ and the team!
🤔 How do you train an AI model to think and reason like a biology expert? We found the answer: let it learn from real expert discussions! Checkout our recent work on a breakthrough approach to improve LLM scientific reasoning - by learning directly from 10+ years of genomics…
Excited to announce MIRIAD — a large-scale dataset of 5,821,948 medical question-answer pairs, each rephrased from passages in the medical literature. Great collab with @QueyJ, @salmanabdullah_, @samarthrawal, @cyrilzakka, @SophieOstmeier, Maximilian Purk, @edreisMD, @EricTopol &…
📢 Introducing Biomni - the first general-purpose biomedical AI agent. Biomni is built on the first unified environment for biomedical agent with 150 tools, 59 databases, and 106 software packages and a generalist agent design with retrieval, planning, and code as action. This…
I will be giving a talk at NAACL AI & Scientific Discovery Workshop tomorrow morning about our recent line of work on automating research with AI agent! Come say hi if you are around! ai-and-scientific-discovery.github.io
Check out our perspective on Multimodal foundation models in molecular cell biology now out in @Nature ! Thanks @BoWang87 @HOATIANCUI1 @fabian_theis @Alejandro__TL @JulioSaezRod @simocristea @genophoria @mo_lotfollahi
🚀 Our perspective is out in @Nature! We present a roadmap for Multimodal Foundation Models (MFMs) — large AI models pretrained across multi-omics and multi-timepoint data — to serve as the computational backbone for building virtual cells. Read the full paper in Nature:…
One direction I'm excited to see more work on in the future is CoT monitoring as a potential scalable oversight method. In our work, we found that we could monitor a strong reasoning model (same class as o1 or o3-mini) with a weaker model (gpt-4o).
Excited to share what my team has been working on at OpenAI!
Detecting misbehavior in frontier reasoning models Chain-of-thought (CoT) reasoning models “think” in natural language understandable by humans. Monitoring their “thinking” has allowed us to detect misbehavior such as subverting tests in coding tasks, deceiving users, or giving…
At Arc we are building AI models of cell state from the ground up, rethinking every step, from data generation to biologically relevant evaluation Today we launch scBaseCamp, the largest public repository of single cell RNAseq data, uniformly processed from raw sequencing reads.
1/6 🚀 Introducing Sky-T1-32B-Preview, our fully open-source reasoning model that matches o1-preview on popular reasoning and coding benchmarks — trained under $450! 📊Blog: novasky-ai.github.io/posts/sky-t1/ 🏋️♀️Model weights: huggingface.co/NovaSky-AI/Sky…
After 7 yrs of training w multiple wearables and user reported data, we can now use probabilistic models to predict blood sugar WITHOUT sensors. JanuaryAI received the CES award: ces.tech/ces-innovation…
1/ Thrilled to share an advancement in gene therapy from my PhD in @NatureComms! We've developed a new approach to reduce immune responses while maintaining efficiency—paving the way for safer, more effective therapies. Big thanks to @zhangf & @mircoscopy! bit.ly/redicas9
Evo has been published in @Science! A true privilege to work with such an amazing team! So many exciting new experimental results in this emerging field of Generative Genomics, including AI generated and *validated* CRISPR-Cas systems and transposons
A new Science study presents “Evo”—a machine learning model capable of decoding and designing DNA, RNA, and protein sequences, from molecular to genome scale, with unparalleled accuracy. Evo’s ability to predict, generate, and engineer entire genomic sequences could change the…
Honored to have my thesis work recognized by the 2024 Sammy Kuo Award in Neuroscience!
The graduate paper of the year goes to @UcheMedoh of the @abu_remaileh lab for his @ScienceMagazine paper on "The Batten disease gene product CLN5 is the lysosomal bis(monoacylglycero)phosphate synthase."
Unlock the Power of Synthetic Data in Computer/Machine Vision 🔐 🚀 With AI vision blowing up in manufacturing and robotics, you have many options for vision system hardware and software 📸 Nevertheless, researchers agree that the data you use to train these systems is actually…