Inverse problems constitute an essential framework for approaching a large variety of issues in technical and medical domains. They are used to determine the underlying causes and structures on the basis of measurements or results. Examples include imaging techniques, where measurement data is used to produce an image of the inside of the body or the inside of a bridge pier. The challenge here is that most inverse problems have the vulnerability that even small perturbations in the data can trigger high oscillations in the solution. A research team at the Department of Mathematics, led by Elena Resmerita, is seeking to develop new and faster mathematical methods to find stable solutions to these problems.

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