Marie Stettler
Senior Data Machine Learning Engineer
Switzerland
Summary
👤
Senior🎓
Top SchoolMarie Stettler is a Senior Data Machine Learning Engineer with nine years of experience at the intersection of computer science and medicine, specializing in histopathology and multimodal cancer analytics. Trained in bioengineering and biocomputing at EPFL with a master’s thesis at the Broad Institute, she has a track record of improving image-based profiling pipelines and applying self-supervised deep learning (PyTorch) to combine histology and RNA-seq for more robust diagnostics. Her research at the Werner Siemens Imaging Center explored initialization effects on deep learning representations and practical strategies for generalizable models, work she now brings to production-focused roles at kaiko.ai. Comfortable moving between research and applied engineering, she mixes statistical rigor, hands-on imaging experience, and a practical product mindset—often uncovering performance gains from methodological choices that are easy to overlook.
9 years of coding experience
7 years of employment as a software developer
Master of Engineering - MEng Bioengineering and Biocomputing, Master of Engineering - MEng Bioengineering and Biocomputing at EPFL
French, English, German
Github Skills (36)
histopathology10
ressources10
machine-learning10
datasets10
clam10
biomedical-engineering10
weakly-supervised-learning10
efficientnet10
optimizer9
data-efficient9
resnet9
biomedical9
digital-pathology9
mobilenet8
high-resolution8
Programming languages (2)
Github contributions (5)
broadinstitute/imaging_metric_comparison
Mar 2017 - Aug 2017
Contributions:166 commits in 5 months
maduc7/Histopathology-Datasets
Jul 2022 - Feb 2023
Ressources of histopathology datasets
Contributions:12 reviews, 58 commits, 5 PRs in 6 months
datasetshistology-imageshistopathologyhistopathology-imagesmachine-learning
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