About

I am a postdoctoral researcher at the Institute for Data Science Foundations at TU Hamburg, working with Nihat Ay. My research spans control theory, information geometry, and optimization, with a growing focus on learning and control of dynamical systems. My current work concerns natural-gradient optimization and Wasserstein-geometric approaches to divergence and regularization.

In a parallel project, I am investigating how policy architectures affect the performance and robustness of embodied agents whose policies are learned through reinforcement learning. I draw on tools from control theory, with the longer-term goal of applying these ideas to robotic systems.

I completed my PhD at the Institute of Control Systems at TU Hamburg under the supervision of Herbert Werner. I studied distributed control of multi-vehicle systems, using integral quadratic constraints to analyze robust stability and performance, and investigating cooperative source-seeking algorithms through experiments with groups of quadrotors. My research involved moving between mathematical analysis, simulation, and experiments.

Research Interests

Information Geometry · Robust Control Theory · Optimization on Manifolds · Learning of Dynamical Systems