Neuro-inspired Theory, Modeling and Applications


Our theoretical research is concerned with understanding and analytically describing various aspects of neural network dynamics. On the modeling side, we are mainly interested in functional networks (i.e., networks that do something that we consider useful), for which we take inspiration from both biology and AI research. An essential aspect of model functionality concerns robustness, since one of our goals is the embedding of functional networks in neuromorphic substrates and their application to real-world problems.

Our Research Interests


The Human Brain Project Podcast - Info
Mihai A. Petrovici
talks about his research on intelligence, his experience of growing up in a family of physicists, and what he does for fun outside of work.

eLife Article: how natural-gradient descent enable efficient synaptic plasticity!


"Natural-gradient learning for spiking neurons".
See Publication

Our group leader speaks his mind!


Read the Interview that Mihai A. Petrovici gave on Science and Politics to Uniaktuell - the online magazine of the University of Bern.

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