
Linnea Evanson, PhD
43 posts

Linnea Evanson, PhD
@EvansonLinnea
Postdoc | Former PhD Student @ École Normale Supérieure | Former Research Scientist Intern @ Meta AI | Studying how AI and our brains learn language!



💫 Introducing NeuralSet: a simple, fast, scalable Python package for Neuro-AI 📦 pip install neuralset 📄 kingjr.github.io/files/neuralse… 🔍 facebookresearch.github.io/neuroai/neural… Supports 🧠 fMRI, EEG, MEG, ECoG, spike… preprocessing 💬 text 🔊 audio ▶️ video 🏞️ image… embeddings 🧵 Details👇



🧠 the Digital Brain Project is now live: $5M total · up to $500k per selected team Let's open-source the modeling of the human brain brain activity! ➡️Apply on: digitalbrainproject.org




Our Brain and AI team will be at #ccn2025 this week: 3 highlights: 1. 🏆1st place for the Algonauts competition: x.com/stephanedascol… 2. 🗣️Keynote:2025.ccneuro.org/k-and-t-langua… 3. 🚀Tutorial: Scale your decoding pipeline in the notebook: docs.google.com/document/d/1is…

We’re very pleased to release our latest study ‘Emergence of Language in the Developing Brain’ Paper: tinyurl.com/5h49xpjv Blog: tinyurl.com/mrtdk8p2 The first systematic investigation of how the neural representations of language evolve as the brain develops. A collaboration between @AIatMeta and @FondARothschild, with @JeanRemiKing. Thread 👇

We’re very pleased to release our latest study ‘Emergence of Language in the Developing Brain’ Paper: tinyurl.com/5h49xpjv Blog: tinyurl.com/mrtdk8p2 The first systematic investigation of how the neural representations of language evolve as the brain develops. A collaboration between @AIatMeta and @FondARothschild, with @JeanRemiKing. Thread 👇

Announcing the newest releases from Meta FAIR. We’re releasing new groundbreaking models, benchmarks, and datasets that will transform the way researchers approach molecular property prediction, language processing, and neuroscience. 1️⃣ Open Molecules 2025 (OMol25): A dataset for molecular discovery with simulations of large atomic systems. 2️⃣ Universal Model for Atoms: A machine learning interatomic potential for modeling atom interactions across a wide range of materials and molecules. 3️⃣ Adjoint Sampling: A scalable algorithm for training generative models based on scalar rewards. 4️⃣ FAIR and the Rothschild Foundation Hospital partnered on a large-scale study that reveals striking parallels between language development in humans and LLMs. Read more ➡️ go.fb.me/q5l4cz

