Kevin Mader
Machine Learning Engineer at Apple
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolKevin Mader is a Machine Learning Engineer at Apple with a PhD in Electrical Engineering from ETH Zurich and over a decade of experience at the intersection of image processing, biomechanics, and computational imaging. He builds high-throughput, reproducible ML systems for wellness, health, and digital therapeutics, combining research rigor from academic roles and lecturing with product-focused engineering at companies like Magic Leap and his own startup 4Quant. His work spans medical imaging, spatial and visual computing, and biomedical sensing algorithms, with hands-on expertise in Python, high-performance computing, and large-scale data pipelines. Kevin also contributes to open-source projects—improving image-based testing in the widely used matplotlib library and tuning graph neural network examples in Spektral—demonstrating attention to robust evaluation and practical model optimization. Based in Zurich, he leverages a rare mix of academic depth and production experience to translate advanced imaging and ML research into deployed features that enhance user well-being.
12 years of coding experience
18 years of employment as a software developer
PhD, Electrical Engineering, Image Processing and Biomechanics, PhD, Electrical Engineering, Image Processing and Biomechanics at Eidgenössische Technische Hochschule ZürichBS, Electrical Engineering, BS, Electrical Engineering at Boston University
German
Stackoverflow
1,339reputation
253kreached
28answers
3questions
colors
top-5%
python
top-5%
Github Skills (21)
data-visualizations10
python10
machine-learning-models10
matplotlib10
testing10
data-visualisation10
keras10
deeplearning-ai10
deep-learning10
tensorflow10
data-visualization10
graph-neural-network10
colors9
model-optimization9
numpy8
Programming languages (19)
Github contributions (5)
danielegrattarola/spektral
Dec 2019 - Dec 2019
Graph Neural Networks with Keras and Tensorflow 2.
Role in this project:
ML Engineer
ML EngineerContributions:18 commits, 4 PRs, 4 comments in 1 day
Contributions summary:Kevin primarily focused on modifying the example scripts related to graph signal classification using MNIST data. Their commits addressed the target dimension in the model, adjusting it to match the expected output. They also made adjustments to training parameters, specifically decreasing the number of epochs and changing to early stopping to prevent overfitting. This indicates the user was actively involved in fine-tuning and optimizing the model training process within the Spektral framework.
pythondeep-learninggraph-deep-learningneural-graphneural-networks
matplotlib/matplotlib
Aug 2019 - Oct 2019
matplotlib: plotting with Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:9 commits, 1 PR, 14 comments in 1 month
Contributions summary:Kevin's contributions primarily focused on enhancing the test suite for the matplotlib library, specifically targeting image rendering functionalities. They added a new test case to verify the correct display of 10x10x1 images and refined existing tests by implementing figure comparisons. Furthermore, the user introduced failure cases and refactored tests using `check_figures_equal` to improve the robustness and reliability of the image-based testing procedures. Additional changes included updating comments and removing whitespace.
pythondata-sciencegtkdata-visualizationplotting
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