Antoine Wehenkel
Applied Research Scientist at Apple
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolAntoine Wehenkel is an Applied Research Scientist at Apple’s Health AI team with 11 years of experience blending biophysical simulation and machine learning to enable non-invasive health monitoring. He completed a PhD (FNRS Fellowship) on deep probabilistic modelling for intractable inverse problems and spent a postdoc at Apple and ML Research developing robust simulation-based inference for misspecified simulators. His work spans theory and engineering—publishing research on distribution-robust hybrid learning and contributing practical code and teaching materials for deep learning and AI courses. At Apple he translates generative and inference advances into applied health technologies, combining domain knowledge with scalable ML. He also has hands-on full‑stack and ML engineering experience from university projects and internships at AWS and Apple, reflecting an ability to ship both prototypes and production-ready systems. Based in Zurich, he brings a rare mix of rigorous probabilistic research and pragmatic software craftsmanship to health-focused ML.
11 years of coding experience
1 year of employment as a software developer
High School, General Studies, High School, General Studies at A.R.A.P.SMaster in engineering, Artificial Intelligence, Summa Cum Laude, Master in engineering, Artificial Intelligence, Summa Cum Laude at Université de LiègeExchange Student, Computer Engineering, 5.8/6, Exchange Student, Computer Engineering, 5.8/6 at EPFL (École polytechnique fédérale de Lausanne)
English, French
Github Skills (17)
pytorch10
python10
machine-learning10
pacman10
mask-rcnn10
deep-learning10
faster-rcnn10
game-development10
mnist9
jupyter-notebook9
vggnet8
matplotlib8
dcgan7
cgan7
graphical-user-interface6
Programming languages (6)
Github contributions (5)
glouppe/info8006-introduction-to-ai
Sep 2018 - Jan 2021
Lectures for INFO8006 Introduction to Artificial Intelligence, ULiège
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:85 commits, 3 PRs, 75 pushes in 2 years 4 months
Contributions summary:Antoine contributed to both the front-end and back-end of the project. Their work included adding a bar plot notebook for visualization, modifying a Python script related to the game's core logic, and merging branches, indicating involvement in code integration. They also updated the run script for agent loading and made various changes to the game's configuration and code files, reflecting involvement in both application and interface development.
deep-learningartificialmachine-learningulinatural-language-processing
glouppe/info8010-deep-learning
Jul 2019 - Mar 2021
Lectures for INFO8010 Deep Learning, ULiège
Role in this project:ML Engineer
ML EngineerContributions:17 commits, 12 PRs, 6 pushes in 1 year 8 months
Contributions summary:Antoine contributed to deep learning tutorials, focusing on convolutional neural networks (CNNs) and logistic regression. The commits include code for building, training, and evaluating CNN models on the MNIST dataset. The contributions involve implementing and experimenting with different CNN architectures, including fine-tuning pre-trained models like VGG16. Additionally, there are exercises and examples related to GANs and using PyTorch for these tasks.
deep-learningulimachine-learningtensorflow
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