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Faculty 3 - Mathematics and Computer Science
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WG Industrial Mathematics
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Prof. Dr. Dr. h.c. Peter Maaß
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PhD Students
Hannes Albers
Janek Gödeke
Nick Heilenkötter
Meira Iske
Helge Mohn
Judith Nickel
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Research
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Research
Inverse problems and magnetic particle imaging
Deep learning and inverse problems
Deep learning and digital pathology
Deep learning and industrial applications
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Projects
Current projects
PY2DLL
AGENS
DELETO - Machine learning in correlative MR and high-throughput NanoCT.
Design-KIT - Artificial intelligence in mechanical component development
DIAMANT
D-MPI - Dynamic Inverse Problems in Magnetic Particle Imaging
Research Training Group π³ - Parameter Identification – Analysis, Algorithms, Applications
HYDAMO - Hybrid data-driven and model-based simulation of complex flow problems in the automotive industry
Inverse problems - Theories, methods and implementations
KIDOHE - AI-supported documentation for midwives
KIWi -Hybrid Parameter Identification with Invertible Networks
MALDISTAR - Study on quality assessment, standardization and reproducibility of MALDI imaging mass spectrometry data
MarDATA - Monitoring a stressed ice shelf - Machine learning algorithms to detect icequakes in 20 years of seismological records at Neumayer station, antarctica
MarDATA - Machine learning in climate modelling
MarDATA - Robust Machine Learning applied to Stratospheric Chemistry Models
ML-X-RAY - Machine learning and X-ray technology for measuring inhomogeneous cable and pipe products
MPI2 - Model-based parameter identification in Magnetic Particle Imaging
ROMSOC - Reduced Order Modelling, Simulation and Optimization of Coupled Systems
SPAplus - Small Data problems in digital pathology
TorchPhysics - A deep learning library for differential equations
Finished projects
Development of a digital staining method as a pathological-histological diagnostic tool based on the MALDI imaging technology
HYPERMATH - Hyperspectral Imaging: Mathematical Methods for Innovations in Medicine and Industry
MaDiPath - Mass Spectrometric Profiling/Grading for routine oncological digital pathology applications
MALDI AMK - 3D-MALDI-Imaging for analysis of proteomic markers and clinical drug distribution
MALDI Imaging Lab - An interdisciplinary core facility for the acquisition and analysis of imaging mass spectrometry data
SceneNet - Mobile Crowd Sourcing Video Scene Reconstruction
Spatially three-dimensionally resolved metabolic analysis for medicine
CRC 747 Micro cold forming - processes, characterisation, optimisation
CRC 1232 From coloured states to evolutionary construction materials
SPP 1324 - Adaptive Wavelet Frame Methods for Operator Equations: Sparse Grids, Vector-Valued Spaces, and Applications to Nonlinear Inverse Parabolic Problems
SPP 1480 - Thermomechanical deformation of complex components by drilling and milling processes
UNLocX - Uncertainty principles versus localization properties, function systems for efficient coding schemes
Publications
Events
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Events
2023 - KoMSO Academy
2021 - KoMSO Academy
2020 - Code Sprint
2019 - Deep Learning and Inverse Problems
2019 - ROMSOC Training Course - Introduction to Deep Learning
2017 - Inverse Problems and Imaging
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WG Industrial Mathematics
Team
PhD Students
PhD Students
© Hannes Albers, ZeTeM
Hannes Albers
Inverse Problems and Magnetic Particle Imaging
find out more: Hannes Albers
more
© Helge Mohn
Helge Mohn
Deep Learning and Inverse Problems
find out more: Helge Mohn
more
© Judith Nickel, ZeTeM
Judith Nickel
Deep Learning and Inverse Problems
find out more: Judith Nickel
more
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