Arnaud Dhaene
Specialist, Data Science
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolArnaud Dhaene is a Specialist in Data Science based in Zurich with eight years of experience at the intersection of life sciences, AI consulting and software engineering. He holds a Master of Life Sciences Engineering from EPFL and completed graduate work at Stanford, blending rigorous biological training with advanced data science methods. At QuantumBlack, AI by McKinsey, he applies production-focused ML and analytics to industry problems while drawing on prior computational research in academia. A strong programmer and analytic thinker, he navigates complex pipelines from experimental data to deployable models. He brings a multidisciplinary perspective that helps translate domain-specific life-science questions into scalable AI solutions. Notably, his background bridges hands-on software delivery and research-grade computational biology—enabling pragmatic yet scientifically grounded outcomes.
8 years of coding experience
Certificat du Baccalauréat Général, Certificat du Baccalauréat Général at Collège international Marie de FranceMaster of Life Sciences Engineering (120 ECTS), Master of Life Sciences Engineering (120 ECTS) at EPFL (École polytechnique fédérale de Lausanne)Master Thesis, Master Thesis at Stanford University
Spanish, English, French, Dutch
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (80)
tensorboard10
controlling9
circles9
developer-tools9
data-visualization9
pyside9
python9
metadata9
fabric9
deep-learning9
streamlit9
pytorch9
imaging9
machine-learning9
medical-image-processing9
Programming languages (5)
Github contributions (5)
arnauddhaene/nidmd
Mar 2020 - Jun 2020
Interactive Dashboard for the visualisation of fMRI time-series Dynamic Mode Decomposition.
Contributions:95 commits, 4 PRs, 57 pushes in 2 months
decompositionvisualisationfmridashboardtime-series
arnauddhaene/tagroi
Mar 2022 - Mar 2022
Segmentation model for tagged cardiac MR images.
Contributions:1 review, 21 commits, 3 PRs in 19 days
cardiacdeep-learningcomputer-visiontaggedsegmentation
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