Excited to be in Rio for #ICLR2026 🇧🇷
I'll be presenting our work, Mixture of Cognitive Reasoners (aka MiCRo), on Friday at Pavilion 3, 10:30 AM (#1610). Come say hi :D
Happy to chat about NeuroAI, representational & cultural alignment, and/or test-time learning 🧠
My lab is hiring a software engineer to support our #NeuroAI research: careers.epfl.ch/job/Lausanne.... Please consider applying if you want to build out the infrastructure enabling models of the human brain & mind (e.g., www.Brain-Score.org). We will start screening applications this week 🧠🤖
I will be at #ICRL2026 in Rio to present our work on model-guided microstimulation.
Poster session: Thursday, 23 April, 10.30am - 1pm at pavilion 3, poster nr. 1620
Initial BlueSkyPrint here: tinyurl.com/modelguidedmicrostim
🧠 When you watch a movie, your brain blends sight, sound, and speech into a single experience.
Should models of the brain blend them too, or keep the senses separate until the very end?
We built MIRAGE to find out. It sets a new SOTA for predicting whole-brain fMRI from movies. 🧵
🚀 The Re-Align Challenge is now LIVE!
We’re inviting you to explore what properties of vision models and data lead to convergences and divergences in representational alignment.
🔗 Get started: huggingface.co/spaces/repre...
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🎉 Re-Align is back for its 4th edition at ICLR 2026!
📣 We invite submissions on representational alignment, spanning ML, Neuroscience, CogSci, and related fields.
📝 Tracks: Short (≤5p), Long (≤10p), Challenge (blog)
⏰ Deadline: Feb 5, 2026 for papers
🔗 representational-alignment.github.io/2026/
Looking forward to presenting at the #AAAI #NeuroAI workshop; including 3 projects that were just accepted to ICLR! arxiv.org/abs/2509.24597, arxiv.org/abs/2510.03684, arxiv.org/abs/2506.13331 🧪🧠🤖
Martin Schrimpf
One week left to apply to the EPFL computer science PhD program www.epfl.ch/education/ph.... It's an amazing environment to do impactful research 🧪 (with unparalleled compute)! My NeuroAI group is hiring 🧠🤖. Consider this review service by our fantastic PhD students: www.linkedin.com/posts/spnesh...
Two simple ideas for building improved brain encoding models: 1. learn to use representations from all model layers via a gating mechanism + 2. start from natively multimodal features for multimodal predictions. State of the art performance; see mirage-brain.epfl.ch for details #NeuroAI 🧠🤖🧪
DNN models of the brain are getting bigger. Are we replacing one complicated system in vivo with another in silico?
In new work, we seek the *smallest* DNN models of visual cortex, balancing prediction with parsimony.
It turns out these compact models are surprisingly small!
rdcu.be/e5H8G
