Simon M. Hofmann

Simon M. Hofmann is a Doctoral Researcher at the Max Planck Institute for Human Cognitive and Brain Sciences (Leipzig), affiliated with the Department of Neurology and the International Max Planck Research School NeuroCom. His work focuses on interpretable AI methodologies for neuroscience, recurrent neural networks modeling cognitive processes, and developing ecological research paradigms using naturalistic stimuli like immersive virtual reality. He holds a Master's in Brain and Cognitive Science from the University of Amsterdam and a Bachelor's in Philosophy/Psychology from TU Berlin. Hofmann has conducted visiting research at institutions including the Fraunhofer Heinrich Hertz Institute and the Donders Institute. Beyond academia, he has served as an organizer for the CBS CoCoNUT initiative and held roles in film festivals such as Berlinale. His research emphasizes explainable AI tools like the xai4mri Python toolbox and investigates brain-heart interactions in virtual environments.

• Education:
  • 2015-2018: Research Master in Brain and Cognitive Science (University of Amsterdam)
  • 2009-2013: Bachelor in Philosophy/Psychology (TU Berlin/Humboldt University)
• Key Research Groups:
  • Methods and Development Group: Neural Data Science & Statistical Computing
  • Research Group: Mind-Body-Emotion (Dept. of Neurology)

His research interests span cognitive processes in complex environments, deep learning model interpretability, and the development of naturalistic experimental paradigms integrating multisensory stimuli. Hofmann's contributions include advancing EEG/fMRI integration techniques and studying emotional arousal through physiological signals in immersive VR settings.

Publications highlight his work on explainable AI for neuroimaging, brain-age predictions via deep learning, and decoding neural correlates of emotional experiences. He actively promotes open science practices through tool development and interdisciplinary collaboration.

Labs/Teams: Involved in the Methods and Development Group focusing on neural data science and statistical computing, with cross-group collaborations in computational neuroscience and neuroimaging.