PeopleofSuperintelligence

Researcher

Martin Schrimpf

Martin Schrimpf is a NeuroAI researcher whose neural network models of vision and language aim to match the brain's representations and human behavior. After computer science degrees at TUM, LMU and UNA, he completed a PhD at MIT under Jim DiCarlo, where he started the Brain-Score platform in 2017 and led work on the CORnet-S network. From 2022 to 2023 he was a research scientist at the MIT Quest for Intelligence, and in 2023 he started the NeuroAI Lab at EPFL. In 2024, he coauthored a Nature Human Behaviour study on driving the human language network with a GPT-based model and the TopoLM paper, and in 2025 he was named a Schmidt Sciences AI2050 Early Career Fellow. He is a tenure-track assistant professor at EPFL, where he heads the NeuroAI Lab.

Badges

Timeline

  1. 2011–2020

    Computer science and Integreat

    He studies information systems at TUM from 2011 to 2014 and software engineering at TUM, LMU and UNA from 2014 to 2017. His master thesis in 2016 is at Harvard Medical School with Gabriel Kreiman, and in 2017 he works on deep learning at MetaMind/Salesforce with Richard Socher. From 2015 to 2020, he is co-founder and CTO of Integreat, a startup now used in one sixth of German cities to help newcomers.

  2. 2017–2022

    A PhD and Brain-Score at MIT

    He completes a PhD in the Brain and Cognitive Sciences department at MIT, advised by Jim DiCarlo, with collaborations with Ev Fedorenko and Josh Tenenbaum. In 2017, while still a graduate student, he starts Brain-Score, an open-source platform that tests AI models against human neural and behavioral data. By 2020, he leads with Jonas Kubilius the DiCarlo-lab work on Brain-Score and on CORnet-S, a shallow recurrent network with four areas analogous to V1, V2, V4 and IT.

  3. 2021

    Language models fit the brain

    In 2021, he publishes "The neural architecture of language: Integrative modeling converges on predictive processing" in PNAS. The study finds that the most powerful transformer models predict nearly 100% of explainable variance in neural responses to sentences, evidence that predictive processing shapes language comprehension in the human brain.

  4. 2022–2023

    Research scientist at MIT Quest

    From 2022 to 2023, he is a research scientist at the MIT Quest for Intelligence. His doctoral work with James DiCarlo studies the neural mechanisms underlying object recognition.

  5. 2023

    Founding the EPFL NeuroAI Lab

    In 2023, he moves back to Europe to start the NeuroAI Lab at EPFL, joining the Neuro-X institute as a tenure-track assistant professor. The lab works jointly between the School of Life Sciences and the School of Computer and Communication Sciences.

  6. 2024

    Language network and TopoLM

    In January 2024, he coauthors a Nature Human Behaviour study in which a GPT-based encoding model picks sentences that strongly drive or suppress activity in the human language network of new individuals. In October 2024, he coauthors TopoLM, a transformer language model with a two-dimensional spatial layout of units that cluster like areas of the brain's language system.

  7. 2024–2025

    SPARK grant and AI2050 fellowship

    In 2024, he is awarded a Swiss National Science Foundation SPARK grant for a project on scaling laws for neural network models of the primate visual ventral stream. In 2025, he is named a Schmidt Sciences AI2050 Early Career Fellow, with 500,000 USD for a three-year project to build digital twins of the human brain.

  8. As of October 2026

    Leading the NeuroAI Lab

    He is a tenure-track assistant professor at EPFL with appointments in the School of Life Sciences and the School of Computer and Communication Sciences, and he heads the NeuroAI Lab. His research builds artificial neural network models that match the brain's neural representations and align with human behavior. He is also Chief Scientific Fellow at Dandelion, an advisor to Neurosoft and an ELLIS Scholar in the ELLIS Unit Lausanne.

Career

  1. Since 2023EPFLTenure-track Assistant Professor, Founder
  2. NowDandelionChief Scientific Fellow
  3. NowEuropean Laboratory for Learning and Intelligent SystemsScholar
  4. 2022–2023Massachusetts Institute of TechnologyResearch Scientist
  5. 2017MetaMind/Salesforce
  6. 2015–2020IntegreatCo-founder and CTO

Education

  1. 2022Massachusetts Institute of TechnologyPhD
  2. 2017Technical University of MunichMaster's study in software engineering
  3. 2017LMU MunichMaster's study in software engineering
  4. 2017National University of AsunciónMaster's study in software engineering
  5. 2016Harvard UniversityMaster's thesis
  6. 2014Technical University of MunichInformation Systems study

From the biography.

  1. Google has the highest combined h-index among AI organizationsIncludes European Laboratory for Learning and Intelligent Systems. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes EPFL. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  3. The United States employs an estimated 48% of people shaping AIIncludes EPFL. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  4. 44% of AI career moves go from one university to anotherIncludes European Laboratory for Learning and Intelligent Systems. We estimate how 26,439 AI career moves link universities, companies, labs, nonprofits and government research centers, with decade counts, net flows and the top paths.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Martin Schrimpf yet. Send us a free-licensed photo.

  1. EPFL - Martin Schrimpf | Online People Directory people.epfl.ch. Checked 21 October 2026.
  2. Martin Schrimpf mschrimpf.com. Checked 21 October 2026.
  3. How AI Models Are Helping to Understand — and Control — the Brain | Quanta Magazine quantamagazine.org. Checked 21 October 2026.
  4. Tidying up deep neural networks - MIT McGovern Institute mcgovern.mit.edu. Checked 21 October 2026.
  5. The neural architecture of language: Integrative modeling converges on predictive processing - PMC pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  6. Martin Schrimpf | The MIT Siegel Family Quest for Intelligence sqi.mit.edu. Checked 21 October 2026.
  7. "We're building an in-silico replica of the brain" - EPFL actu.epfl.ch. Checked 21 October 2026.
  8. EPFL NeuroAI Lab - EPFL epfl.ch. Checked 21 October 2026.
  9. Driving and suppressing the human language network using large language models | Nature Human Behaviour nature.com. Checked 21 October 2026.
  10. [2410.11516] TopoLM: brain-like spatio-functional organization in a topographic language model arxiv.org. Checked 21 October 2026.
  11. Martin Schrimpf receives prestigious SNSF SPARK grant - EPFL actu.epfl.ch. Checked 21 October 2026.
  12. EPFL Professors named Schmidt Sciences AI2050 Fellows - EPFL actu.epfl.ch. Checked 21 October 2026.
  13. Martin Schrimpf - AI2050 ai2050.schmidtsciences.org. Checked 21 October 2026.
  14. Martin Schrimpf | European Laboratory for Learning and Intelligent Systems ellis.eu. Checked 21 October 2026.