Etienne Combrisson is a Senior Data Scientist and neuroscientist with a decade of experience at the intersection of neuroscience, statistics and machine learning, currently applying his expertise to 3D topology-aware cost prediction at Fabera. He has a strong academic track record as a CNRS researcher and postdoc, developing information-theoretic and network-based methods to track dynamic functional connectivity during learning and decision-making. His PhD and postdoctoral work produced practical ML tools for decoding motor representations from intracranial EEG with applications to brain–computer interfaces. Etienne is also an active open-source contributor—having improved Vispy’s 2D/3D arrow and text rendering—which reflects his habit of translating research-grade algorithms into robust, reusable code. Fluent in scientific programming and GPU-accelerated computation (including JAX), he blends theoretical rigor with pragmatic engineering to move complex neuroinformatics methods toward real-world use.
Baccalauréat, Mathématiques, Baccalauréat, Mathématiques at Lycée Jeanne-d'Arc
Mathématiques, Mathématiques at Classes Préparatoires, lycée godefroy de bouillon
Doctor of Philosophy - PhD, Intelligence artificielle et neuro-informatique, Doctor of Philosophy - PhD, Intelligence artificielle et neuro-informatique at Université Claude Bernard Lyon 1
Deep Learning, Deep Learning at Neuromatch academy
Contributions:20 commits, 6 PRs, 66 comments in 1 year 1 month
Contributions summary:Etienne significantly contributed to the Vispy library by implementing features related to arrow visuals and text rendering, specifically focusing on individual text rotation and flexible arrow head configurations. They modified the arrow head implementation to accommodate both 2D and 3D data. They also refactored the code to use modern coding practices like `as_vec4` and adjusted the size conditions of markers and the processing of colormaps.
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