The research focuses on the mathematical foundations and applications of machine learning and data-driven optimization and control, especially on robustness (distributional robustness, adversarial robustness, generalization, causal intervention, robust optimization), and interfacing dynamical systems and learning.
Flexible Research Platform
- Data-driven Optimization and Control
- Multi-species Balance Laws
- Numerical Methods for Innovative Semiconductor Devices
- Probabilistic Methods for Dynamic Communication Networks
- Simulation of Semiconductor Devices for Quantum Technologies
- Former Groups