Parameter Identification - Analysis, Algorithms, Applications

Studying Industrial Mathematics in Bremen

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The task of retrieving biological, physical, or technical parameters from measured data is as universal as the quest to determine system parameters for optimisation/controlling complex processes. Accordingly, parameter identification is at the core of multiple applications in all fields of natural sciences, engineering, life sciences, and industrial applications. The demand for tackling ever more complex models in terms of non-linearity, sensitivity, coupling of systems or for including specific expert information as side constraints, provides numerous challenges in mathematical modelling and for designing, analysing, and implementing appropriate algorithms.

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Bild  Sören Dittmer Bild  Tobias Kluth
Sören Dittmer has submitted his PhD thesis with the title "On deep learning applied to inverse problems - A chicken-and-egg problem" and Tobias Kluth has submitted his habilitation with the title "Model-based to data-driven approaches for parameter identification and image reconstruction in the applied inverse problem of magnetic particle imaging" - CONGATULATIONS!



Prof. Peter Maass Dr. Daniel Otero Baguer
Phone:   +49 421 218 63801 Phone:  +49 421 218 63816
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