MIA Research

The MIA group has diverse expertise in mathematical and computational research for data science in imaging and artificial intelligence.
Our research features close synergies with medical imaging, inverse problems, functional analysis, geometric methods, scientific computing, numerical PDEs, dynamical systems, and neuroscience, and finds a wide spectrum of applications in physical sciences, engineering simulations, and precision medicine.

Data-driven science allows discovering hidden parameters or functions in dynamical systems from observed data by solving (ill-posed) inverse problems. Next, tools from uncertainty quantification, image analysis, optimal transport and dynamical systems yield further insight.

We aim to combine data-driven science with our intense research in dynamical systems, scientific computing, and mathematical systems theory. This approach offers new opportunities to obtain more accurate data-driven models in, for instance, neuroscience but also presents important mathematical challenges, such as understanding the mathematical properties of these new models and techniques and deriving and analysing accurate and efficient numerical discretisations for these novel approaches.

Note that the following list is by no means complete but gives an impression of our current research areas.