About me

I’m a 4th-year PhD candidate at the Institute of Control Systems, Hamburg University of Technology. My research studies data driven optimization and decision making for (partially) unknown systems using techniques from approximation theory, statistical learning and control. A central goal of my work is to develop methods with provable guarantees, including approximation bounds, as well as performance and safety certificates. I’m currently working on sparse identification of dynamical systems using kernel methods and safe decision making using multiple data sources. Main applications are in particle accelerators; in collaboration with the Deutsches Elektronen-Synchrotron (DESY) the algorithms are tested on real systems.

Student Supervision

Students interested in kernel methods, neural networks, or Bayesian optimization are welcome to email me with a brief message and an up-to-date transcript of records.