Regular biography
Martin Schrimpf is a Tenure Track Assistant Professor in the Department of Computer Science at École Polytechnique Fédérale de Lausanne. His research focuses on computational understanding of neural mechanisms underlying natural intelligence in vision and language, bridging Deep Learning, Neuroscience, and Cognitive Science. He is affiliated with the NeuroAI Lab and has expertise in NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, and startups. His work includes founding startups and advising emerging ventures in neurotech and biotech. Martin completed his PhD at MIT and holds degrees in computer science from TUM, LMU, and UNA.
Scholar-generated biography
Martin Schrimpf is a researcher at EPFL with expertise in NeuroAI, Computational Neuroscience, Deep Learning, Vision, and Language. His work focuses on understanding the neural mechanisms underlying human intelligence through integrative modeling, predictive processing, and benchmarking artificial neural networks against brain responses. Schrimpf explores how deep learning models can mimic brain-like object recognition and language processing, emphasizing the alignment between models and human neural activity. His research also investigates the robustness of neural networks, the role of recurrent computations in visual pattern completion, and the development of platforms for multi-modal physical simulation. His contributions span both theoretical and applied aspects of AI and neuroscience.