The STAT group is comprised of leading researchers with expertise in statistics, mathematics and computer science. Together, we are collaborating on cutting-edge research projects that are pushing the boundaries towards a deeper theoretical understanding of machine learning, thereby paving the way for the development of safer, more efficient, and more reliable machine learning systems.
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.
Note that the following list is by no means complete but gives an impression of our current research areas.
- Artificial intelligence for medical imaging (Jelmer Wolterink, Christoph Brune)
- Computational neuroscience and dynamical systems (Hil Meijer)
- Ensemble methods for cluster analysis (Hanyuan Hang)
- Pure exploration (Wouter Koolen)
- Robust methods for time series analysis (Annika Betken)
- Scientific machine learning with uncertainty quantification (Mengwu Guo)
- Theoretical understanding of deep learning (Johannes Schmidt-Hieber, Sophie Langer)
- Variational and geometric methods in inverse problems and machine learning (Marcello Carioni, Josè Iglesias, Christoph Brune)