Jean-Rémi KING

About me

I am a CNRS researcher at École Normale Supérieure currently detached to Meta AI , where I lead the Brain & AI team . This team aims to identify the brain and computational bases of human intelligence, with a focus on language. For this, we develop deep learning algorithms to decode and model brain activity recorded with MEG , EEG , electrophysiology and fMRI . Some of our latest studies: ❮ Previous study Next study ❯ Visual summaries of some of our latest studies: Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI, arXiv 2025 👇 By Careil , Benchetrit and

saved by

• Laerdon Kim
• Lena Araujo

related reading

• Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
• Verbalizable Representations Form a Global Workspace in Language Modelstransformer-circuits.pub
• AI to Interpret Your Mindjonathanxu.com
• Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priorsmedarc-ai.github.io
• Toward accessible, real-time brain decoding: Introducing ENIGMA | Alljoined Blogalljoined.com
• Semantic reconstruction of continuous language from non-invasive brain recordings | Nature Neurosciencenature.com
• [2305.18274] Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priorsarxiv.org
• Alljoined | We’re Hiringalljoined.com
• MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Datamedarc-ai.github.io
• GitHub - nkmjm/mental_img_recon: Mental image reconstruction from human brain activity · GitHubgithub.com
• Fact Finding: Attempting to Reverse-Engineer Factual Recall on the Neuron Level (Post 1) — AI Alignment Forumalignmentforum.org
• [2506.06898] NSD-Imagery: A benchmark dataset for extending fMRI vision decoding methods to mental imageryarxiv.org