Yves Bernaerts
Postdoctoral Researcher at Champalimaud Foundation
Cascais, Portugal
Summary
👤
Senior🎓
Top SchoolYves Bernaerts is a computational neural scientist and Postdoctoral Researcher with eight years of experience bridging computational neuroscience research and practical instruction in physiological methods. Based at Cascais and holding a PhD (Magna cum laude) from the University of Tübingen, he has produced rigorous work in Berenslab and continues research at the Champalimaud Foundation. He combines deep quantitative skills from physics, biophysics and computational modeling with hands-on teaching as a certified Wim Hof Method instructor, applying breathwork and cold exposure insights to human physiology and mindset. Yves’s background in project management and interdisciplinary training enables him to translate complex neural models into testable experiments and real-world practices.
8 years of coding experience
Bachelor's degree, Physics, Bachelor's degree, Physics at KU LeuvenMaster’s Degree, Biophysics, Biochemistry and Biotechnology, Master’s Degree, Biophysics, Biochemistry and Biotechnology at University of LeuvenDoctor of Philosophy - PhD, Computational Neuroscience, Magna cum laude, Doctor of Philosophy - PhD, Computational Neuroscience, Magna cum laude at University of Tübingen
Dutch, English, German, French, Latin, Portuguese
Github Skills (28)
gene-expression10
bottleneck10
predict9
sparse9
parameter-estimation9
bayesian-inference9
electrophysiology8
glow8
pytorch8
simulation8
computational-neuroscience8
neurons7
variational-autoencoder7
machine-learning7
neuroscience7
Programming languages (2)
Github contributions (5)
berenslab/hh_sbi
Mar 2023 - Mar 2025
Contributions:5 PRs, 62 pushes in 2 years 1 month
berenslab/sBNN
Feb 2020 - Jan 2022
A sparse bottleneck neural network to predict electrophysiological properties of neurons from their gene expression.
Contributions:388 commits, 1 PR, 286 pushes in 1 year 11 months
neurosciencegene-expressionpropertiessparsepredict
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