MTS @Boltz_bio; Ex. Staff RE @instadeepai; PhD @UCLmedphys; MSc CSML @uclcs; MEng @Polytechnique; BioInformatics.

Joined February 2012
5 Photos and videos
Yunguan Fu 🧬 retweeted
Announcing GPT-Rosalind, our frontier model for life science research. This model is a step towards one of our most important goals — accelerating science and improving human outcomes. Excited to work with many amazing partners on deploying and improving this model.
Apr 16
Introducing GPT-Rosalind, our frontier reasoning model built to support research across biology, drug discovery, and translational medicine.
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Yunguan Fu 🧬 retweeted
Observed T-cell Receptor Space: Now 1.9M non-redundant paired TCR sequences ( 5 studies, up from 1.6M) opig.stats.ox.ac.uk/webapps/… Thera-SAbDab: 1133 entries ( 58 therapeutics) opig.stats.ox.ac.uk/webapps/… TAP: Guidelines now based on 851 Phase-II therapeutics opig.stats.ox.ac.uk/webapps/…

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Yunguan Fu 🧬 retweeted
4 Feb 2025
We've just rolled out a HUGE DeepPCB update! 🫡 Better AI Routing quality & differential pair support 💪 Support up to 2,200 pins and 1,000 components for AI Placement 👁️ New rendering with improved interactivity: select components, check net-classes, net priorities, and more 🌚 Dark mode ➕ Edit, add & delete diffy P's (differential pairs) in routing 💤 Improved Zuken support 🎨 Better constraint coloring for AI Placement Ready to take your PCB design to the next level? Jump into DeepPCB now to experience AI Place & Route like never before at deeppcb.ai🚀
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Yunguan Fu 🧬 retweeted
Nucleotide Transformer is a series of genomics foundation models of different parameter sizes and training datasets which can be applied to various downstream tasks by fine-tuning. @instadeepai nature.com/articles/s41592-0…
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Yunguan Fu 🧬 retweeted
Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with @jeremyWohlwend, @pas_saro and an amazing team at MIT and Genesis Therapeutics. A thread!
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Yunguan Fu 🧬 retweeted
24 Oct 2024
🚀 We’re proud to announce Kyber, our near-exascale supercomputer, built to drive the next generation of AI research! Powered by NVIDIA H100 GPUs and delivering ~0.5 exaFLOPs in FP16 performance, Kyber increases our computational capabilities tenfold. Read about how we're pushing the boundaries of AI innovation bit.ly/3AeUjth #AI #DeepLearning
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Yunguan Fu 🧬 retweeted
12 Oct 2024
Ai Day last week was a blast! I had a great time presenting alongside many colleagues from @instadeepai and @BioNTech_Group, some of our ongoing Bio AI initiatives. We made several announcements, introducing Kyber, our new supercomputing cluster (more on this soon), as well as BFN, our new paradigm for generative AI, with competitive results on protein and antibody generation. During Ai Day we also delivered two live demos of Laila, our new AI agent, including one from BioNTech's TechLab in Mainz, Germany! To our knowledge, this was one of the first demos of its kind featuring a GPT-4 level AI agent acting in the Lab, interacting with scientists and technicians and helping them enhance their productivity! Ai Day was a significant moment for all of us, and it was exciting to see both the event and Laila featured by several publications including @FT (shorturl.at/hwy4c). Curious to see it in action? Check out the recording of the Laila in the Lab demo below, worth watching and don't miss the end! 😉
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Yunguan Fu 🧬 retweeted
8 Sep 2024
We’re honored to partner with Young African AI Research and @JeffDean to launch this Fellowship! #Indaba2024 #InstaDeep
The 2024 Young African AI Research Fellowship launched yesterday at #Indaba2024, initiated at #Indaba2023 with generous sponsorship from @JeffDean. Inspired by the @instadeepai movie "Cape to Carthage- An African AI Journey," the program nurtures emerging AI talent in Africa 1/3
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Yunguan Fu 🧬 retweeted
2 Sep 2024
Exciting hackathon coming and for a good cause! 🐍 💉#DLI2024
2 Sep 2024
Ready to decode the wild? 🌍Senegal's snake venom present a real health challenge, but we're tackling this complexity head-on with our Snakes and Sequences Hackathon🐍. We invite Deep Learning Indaba attendees to participate in the challenge taking place from today until Friday, September 6th. While the real reward is contributing to groundbreaking research, there are also exciting prizes up for grabs!🏆🎉 Want to know more about @DeepIndaba programme? Check out all the details here: lnkd.in/dgqmCNK5 #deeplearningindaba #AI #MachineLearning #Africa;#hackathon #dli2024
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Yunguan Fu 🧬 retweeted
15 Jul 2024
🌱 As scientists wrestled with the mysteries of plant genomics, our #AI problem solvers had a daring question, "Can AI make a difference?" @Nature covered how our #research and AI #genomics teams teamed up to search for an answer, with AgroNT – our new #LLM. 📚Read more→ go.nature.com/3xWopR7 🤗 Access our LLM #open-source on : huggingface.co/InstaDeepAI/a…
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Yunguan Fu 🧬 retweeted
Sending a very large public thank you to @BennyChain and colleagues for the beautiful tidytcells Python library. I wish this had been around a few years ago. Testing it out on a feature and will soon be replacing a lot of code. pypi.org/project/tidytcells/ frontiersin.org/journals/imm…
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Thanks for organizing such an inspiring event! Great to connect with the immunology community and explore deep learning applications. The code of our work FrameDiPT for #TCR can be found at github.com/instadeepai/Frame…!
19 Jun 2024
Great turnout at the Hinxton Immunogenomics Day, organised by Wanseon Lee @WanseonL , @AniaLorenc and our own Lisa Dratva, around all things #TCR #MHC! @sangerinstitute @LoKretschmer @ioansarr @SCICambridge sites.google.com/view/hinxto…
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Yunguan Fu 🧬 retweeted
🚨Call for reviewers! Please consider serving as a reviewer for @MICCAI_Society - #ASMUS workshop 🔊🏥 and apply here: forms.gle/taPTjt2qbwANC7Pk8 More info: ASMUS ‘24 (miccai-ultrasound.github.io) * Submissions until June 24 * Reviews due July 10
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The slide is available at github.com/mathpluscode/ImgX…. Thanks @mertrory, @STsaftaris, @AlanQWang for the great questions and organisation!
Honoured to be invited! 💟I will present "A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models" melba-journal.org/papers/202… (code at github.com/mathpluscode/ImgX…). Looking forward to discuss more about generative models at the panel discussion!
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Yunguan Fu 🧬 retweeted
Replying to @liza_p_semenova
@liza_p_semenova A huuuuge thank you from everyone at @AiMSza for this wonderful course 🌊🇿🇦📈 and the amazing tutorials you also created for @DeepIndaba 🇬🇭! PS. Please come back 🙏 elizavetasemenova.github.io/…

This spring I had a chance to teach a 3-week course on "Bayesian Modelling & Probabilistic Programming with Numpyro" for the "AI for Science" MSc at the African Institute for Mathematical Sciences (@AIMSacza), SA🇿🇦. Lecture notes (some to be finalised): elizavetasemenova.github.io/…
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Yunguan Fu 🧬 retweeted
🔊 We have just updated our Patent and Literature Antibody Database (PLAbDab) and Therapeutic Antibody Profiler (TAP) web application. New PLAbDab: opig.stats.ox.ac.uk/webapps/… New TAP: opig.stats.ox.ac.uk/webapps/… Descriptions of updates to follow... (1/4)

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Yunguan Fu 🧬 retweeted
🚨 Upcoming MELBA Symposium on Generative Models (June 11) Applying diffusion models for medical imaging❓ 📢 Spotlight on talk #4 - @mathpluscode 1⃣ recycling approach for image segmentation with diffusion models; 2⃣ experiments on various medical imaging modalities (US, CT, MR)
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Thanks for sharing! ❤️ In AI, managers often engage in technical discussions. They might see themselves as contributing members, but their suggestions can be perceived as orders. We need to clarify discussions vs decisions and encourage open dialogue and idea challenges.
I loved this podcast with @elonmusk. He’s just about right. I especially liked his comment about micromanagement. I too have been told this, but I feel micromanagement is often confused with paying attention to engineering detail. In AI and tech, VPs should be able to sit with engineers and work with them. That’s when the real magic happens. I’m skeptic of “managers-by-slides”. I also love the approach of setting meaningful goals and committing to them with a growth mindset which accepts mistakes as part of the learning process. open.spotify.com/episode/5hg…
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Yunguan Fu 🧬 retweeted
(1/2) The webserver and GitHub for AntiFold, our antibody inverse folding model developed by @magnushoie and @AlissaHummer, have now been released! Webserver: opig.stats.ox.ac.uk/webapps/… GitHub: github.com/oxpig/AntiFold

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Yunguan Fu 🧬 retweeted
In this new Review, Smita Nair and co-authors discuss cancer mRNA vaccines, including their advantages and advances made in clinical trials using both cell-based and nanoparticle-based delivery methods, as well as future opportunities for optimization: nature.com/articles/s41571-0…
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