Matthias Hüser
Senior Data Scientist
Basel, Basel-City, Switzerland
Summary
👤
Senior🎓
Top SchoolMatthias Hüser is a Senior Data Scientist with a decade of experience at the intersection of machine learning, optimization and biomedical informatics, currently applying his expertise at TriNetX. He holds a Dr. sc. from ETH Zürich and a strong engineering foundation from Imperial College London, combining academic rigor with production-focused skills in software performance, SIMD/x86 vectorization, parallel computing and GPU acceleration. His domain experience spans intensive care, neuro-ICU and oncology, where he builds ML and statistical solutions informed by operations research and biomedical signal processing. Notably, he blends deep systems-level performance engineering with clinical data science—an unusual mix that lets him optimize models not just for accuracy but for throughput and deployment efficiency. Based in Basel, he has moved seamlessly from PhD research to industry programs like Novartis’ AI4Life, demonstrating an ability to translate advanced methods into real-world healthcare impact.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering (BEng), Computing, 1st class honours, Bachelor of Engineering (BEng), Computing, 1st class honours at Imperial College LondonDoctor of Sciences (Dr. sc. ETH Zürich), D-INFK, Doctor of Sciences (Dr. sc. ETH Zürich), D-INFK at ETH ZürichMaster of Science (MSc), Computer Science, GPA: 5.52/6.00, Master of Science (MSc), Computer Science, GPA: 5.52/6.00 at ETH ZurichGerman Abitur, Special subjects: German Mathematics Chemistry Geography, Average grade: 1.0, German Abitur, Special subjects: German Mathematics Chemistry Geography, Average grade: 1.0 at German School Tokyo Yokohama
English, German, French
Github Skills (32)
scheme9
python8
clustering8
unsupervised-learning8
pandas8
data-science7
netbsd7
data-structure7
data-analysis7
data-structures7
holoviz6
openbsd6
holoviews6
freebsd6
plotly5
Programming languages (4)
Github contributions (5)
ratschlab/dpsom
Oct 2019 - Aug 2020
Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'
Contributions:4 commits, 3 pushes, 2 comments in 10 months
clusteringunsupervised-learning
ratschlab/AKI-EWS
Jan 2024 - Jul 2024
Contributions:1 push, 1 branch in 5 months
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