Scholar
Andreas Hauptmann
Google Scholar ID: y8nRmTYAAAAJ
Academy Research Fellow & Associate Professor, University of Oulu
Inverse Problems
Computational Imaging
Photoacoustic Tomography
Electrical Impedance Tomography
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
2,568
H-index
24
i10-index
40
Publications
20
Co-authors
19
list available
Contact
Email
andreas.hauptmann@oulu.fi
GitHub
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Publications
4 items
Learned iterative networks: An operator learning perspective
2025
Cited
0
Digital twins enable full-reference quality assessment of photoacoustic image reconstructions
2025
Cited
0
Learned enclosure method for experimental EIT data
2025
Cited
0
Learned enclosure method for experimental EIT data
2025
Cited
0
Resume (English only)
Academic Achievements
Published a survey paper on learned reconstruction methods in the IEEE Signal Processing Magazine
Elected as a member of the Young Academy of Finland
Awarded an Academy Research Fellow position focusing on accurate imaging with sound and light
Co-authored a review article on deep learning in photoacoustic tomography published in the Journal for Biomedical Optics with Ben Cox
Received a two-year project grant from the Academy of Finland for sawing optimization
Background
Computational Mathematician interested in combining Inverse Problems and data driven methods.
Co-authors
19 total
Simon ARRIDGE
University College London
Ben Cox
University College London
Co-author 3
Felix Lucka
Centrum Wiskunde & Informatica
Samuli Siltanen
Professor of Industrial Mathematics, University of Helsinki, Finland
Carola-Bibiane Schönlieb
DAMTP, University of Cambridge
Ozan Öktem
Department of Mathematics, KTH - Royal Institute of Technology
Jonas Adler
Principal Research Scientist, Google DeepMind
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