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Martin Schrimpf

Expertise

NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]

Mission

Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to human behavior in their outputs.  Please see the NeuroAI Lab website for details on the lab, publications, applying, and more.

Startups: I am excited about translating cutting-edge research into real-world applications. In the past I founded a startup for the digitization of documents (exit), worked at Promonde in Dubai on digital navigation, co-founded Integreat (now used in 1/6th of cities in Germany to help newcomers), and worked at MetaMind on deep learning in natural language processing (now part of Salesforce). The lake Geneva region is a fantastic emerging place for startups especially in the neurotech and biotech space. Early-stage funding and access to talent here are unparalleled. I am currently advising Dandelion and Neurosoft.
Martin completed his PhD at the MIT Brain and Cognitive Sciences department advised by Jim DiCarlo with collaborations with Ev Fedorenko and Josh Tenenbaum, following Bachelor's and Master's degrees in computer science at TUM, LMU, and UNA. His previous work includes research in human-like vision at Harvard with Gabriel Kreiman, natural language processing reinforcement learning at Salesforce with Richard Socher, as well as several other projects in industry. Martin also co-founded two startups. Among others, his work has been recognized in the news at Science magazine, MIT News, and Scientific American.

Martin's work has been published at top journals including PNAS, Neuron, and Nature Human Behavior as well as leading machine learning venues such as NeurIPS and ICLR where his papers are routinely selected for Oral and Spotlight presentations (<1% acceptance rate). He has received numerous awards and honors for his research, including the Schmidt Foundation AI2050 Fellowship, Neuro-Irv and Helga Cooper Open Science Prize, the McGovern fellowship, the Walle Nauta Award for Continuing Dedication in Teaching, the Takeda Fellowship in AI+Health, the German Federal scholarship, and the MIT Singleton and Shoemaker fellowships. With his startup Integreat, he was a finalist in the Google.org Impact Challenge and won the TUM Social Impact Award, and the Council of Europe's Youth Award.

[Full CV]

Curriculum vitae

=> CV

Education

PhD

| Brain and Cognitive Sciences

2017 – 2022 MIT
Directed by Jim DiCarlo

MSc

| Software Engineering

2014 – 2017 TUM & LMU & UNA

BSc

| Information Systems

2011 – 2014 TUM

Research

NeuroAI

Please see the NeuroAI Lab website for details on the lab, publications, applying, and more.

Teaching & PhD

Current Phd

Aude Maier, Badr Alkhamissy, Yingtian Tang, Abdülkadir Gökce, Melika Honarmand

Past Phd As Codirector

Ben Lönnqvist

Courses

Brain-like computation and intelligence

NX-414

Recent advances in machine learning have contributed to the emergence of powerful models of animal perception and behavior. In this course we will compare the behavior and underlying mechanisms in these models as well as brains.

Neuroscience foundations for engineers

BIOENG-310

This overview course bridges computational expertise with neuroscience fundamentals, aimed at fostering interdisciplinary communication and collaboration for engineering-based neuroscience programs.