Martin Schrimpf
+41 21 693 12 53
Office: BC 206
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+41 21 693 12 53
Office: BC 206
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+41 21 693 12 53
Office: BC 206
EPFL › IC › IC-SIN › SIN-ENS
Website: https://sin.epfl.ch
+41 21 693 12 53
Office: BC 206
EPFL › IC › IC-SSC › SSC-ENS
Website: https://ssc.epfl.ch
+41 21 693 12 53
Office: BC 206
EPFL › SV › SV-SSV › SSV-ENS
Website: https://sv.epfl.ch/education
Expertise
Mission
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'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
Education
PhD
| Brain and Cognitive Sciences
2017 – 2022
MIT
Directed by
Jim DiCarlo
MSc
| Software Engineering2014 – 2017 TUM & LMU & UNA
BSc
| Information Systems2011 – 2014 TUM
Research
NeuroAI
Teaching & PhD
Current Phd
Aude Maier, Badr Alkhamissy, Yingtian Tang, Abdülkadir Gökce, Melika Honarmand
Past Phd As Codirector
Courses
Brain-like computation and intelligence
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
This overview course bridges computational expertise with neuroscience fundamentals, aimed at fostering interdisciplinary communication and collaboration for engineering-based neuroscience programs.