Jonathan Crabbé

@JonathanICrabbe

🧬MTS @ Latent Labs 💡GenAI for Biology & Protein Design 🎓PhD in ML @ University of Cambridge ⚙️ Ex-RS Intern @ Apple MLR & Microsoft Research

London, England

jonathancrabbe.github.io

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Jonathan Crabbé
@JonathanICrabbe
Dec 16, 2025
Super proud of the team's achievement 🚀 Shipping our second model Latent-X2 that allows users to design antibody binders on our platform. Check the below thread for more details 👇
Latent Labs
@Latent_Labs
Dec 16, 2025
5 months from Latent-X1 to Latent-X2. AI-generated antibodies with drug-like developability and low immunogenicity in human panels — zero-shot. Available now for selected partners.
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Jonathan Crabbé
@JonathanICrabbe
Jul 22, 2025
Really happy to be releasing our first model on a beautiful platform. It generates de novo binders with impressive affinity and speed. If you are curious, you can try it for yourself, more info on the thread👇
Simon Kohl
@saakohl
Jul 22, 2025
Introducing Latent-X — our all-atom frontier AI model for protein binder design. State-of-the-art lab performance, widely accessible via the Latent Labs Platform. Free tier: platform.latentlabs.com Blog: latentlabs.com/latent-x/ Technical report: tinyurl.com/latent-X
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Jonathan Crabbé
@JonathanICrabbe
Dec 22, 2023
Always a pleasure to engage with the ML community at conferences! Had an amazing time at #NeurIPS2023 and really interesting conversations with researchers from all around the world. Really worth arguing with Reviewer 2 🤩
Alan Jeffares
Jonathan Crabbé
@JonathanICrabbe
Dec 13, 2023
🚨 𝐏𝐨𝐬𝐭𝐞𝐫 #𝟓𝟑𝟕 𝐖𝐞𝐝𝐧𝐞𝐬𝐝𝐚𝐲 𝟓𝐩𝐦-𝟕𝐩𝐦 🚨 We will challenge many intuitions on training deep ensembles at #NeurIPS2023. Super excited about this awesome collaboration between @Jeffaresalan, @tennisonliu, @MihaelaVDS and myself. Come chat with us & check the 🧵
Alan Jeffares
@Jeffaresalan
Nov 22, 2023
Have we been training deep ensembles with the wrong objective? 😱 Our new #NeurIPS paper investigates why training ensembles *jointly* is almost never observed in practice and uncovers some pretty surprising behaviour… 🧵 [1/N]
Jonathan Crabbé
@JonathanICrabbe
Dec 12, 2023
🚨 Tomorrow, on Tuesday, don't miss my #NeurIPS2023 𝐏𝐨𝐬𝐭𝐞𝐫 #𝟏𝟓𝟐𝟏 on the robustness of interpretability methods @ 𝟏𝟎:𝟒𝟓-𝟏𝟐:𝟒𝟓. A great opportunity to chat about how model invariances are reflected (or not) in popular interpretability methods!
Jonathan Crabbé
@JonathanICrabbe
Nov 3, 2023
[1/n] Interpretability techniques are useful only if they are faithful to the model they explain. In a NeurIPS paper with @MihaelaVDS, we explore faithfulness through the lens of model symmetries. Are interpretability methods consistent with these symmetries? 🧵⬇️Our findings