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Stefan Heinrich

Dr. rer. nat., Dipl.-Inform.

20092025

Research activity per year

Personal profile

Research

My research interest is located at the intersection of artificial intelligence, cognitive psychology, and computational neuroscience, where I study how representations emerge and give rise to function in biological and artificial systems. Here, I aim to understand principles underlying representation learning as a unifying framework for understanding structure, abstraction, and generalisation in cognition and in AI. In particular, I study the processes and mechanisms in the brain and in computational models that form representations through spatial and temporal composition and decomposition, as well as through multimodal integration. My goal is to uncover how such representations arise from structural and geometric symmetries, how they enable behaviour, learning, and reasoning, and how individual differences and neurodiversity shape them. As a central approach, I develop computational cognitive models in the form of artificial neural systems with plausible mechanisms and probabilistic learning dynamics, focused on tasks and phenomena in reasoning, natural language processing, cognitive development, and biosignal inference. Understanding these representational mechanisms and processes provides inductive biases for machine learning and AI systems and yields priors and markers for cognitive science in models of compositionality, disentanglement, generation, and prediction.

Publications

https://stefanheinrich.net/publications/

Employments/positions

Education and competencies

Keywords

  • Machine Learning
  • Natural Language Processing
  • Cognitive Modelling

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  • Carina Garber

    Heinrich, S. (Host)

    1 Mar 202215 Mar 2022

    Activity: Hosting a visitor typesHosting an academic visitor