Andreas Hauptmann
Associate Professor
Finland
Summary
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Senior🎓
Top SchoolAndreas Hauptmann is an applied mathematician and Associate Professor at the University of Oulu with eight years of research-focused experience bridging inverse problems and medical imaging. He develops mathematically grounded imaging methods—particularly electrical impedance tomography and multimodal sound-and-light approaches—to translate theory into devices that address clinical needs. His roles as Academy Research Fellow on the AI-SOL project and Honorary Associate Professor at UCL reflect an active cross-institutional research portfolio and industry-facing ambition. Trained with a PhD in Applied Mathematics (University of Helsinki) and an M.Sc. from TUM, he combines deep computational expertise with clinical collaboration as a docent in the Faculty of Medicine. Beyond algorithms, he focuses on practical impact: optimizing imaging workflows for stroke classification and other time-critical diagnostics. Colleagues value his ability to turn rigorous analysis into usable tools that improve healthcare outcomes.
8 years of coding experience
6 years of employment as a software developer
Master of Science (M.Sc.), Computational and Applied Mathematics, Master of Science (M.Sc.), Computational and Applied Mathematics at Technical University MunichDocent, Faculty of Medicine, Docent, Faculty of Medicine at University of OuluDoctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at University of Helsinki
English, German, FinnishGithub contributions (5)
asHauptmann/DeepDbar
Feb 2018 - Jul 2019
Contributions:8 commits, 6 pushes, 1 branch in 1 year 4 months
asHauptmann/3DPAT_DGD
Jan 2018 - Mar 2020
Contributions:6 commits, 5 pushes, 1 branch in 2 years 2 months
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