We have contributed to the session “A Tutorial on Nonlinear Model Predictive Control: What Advances Are On the Horizon?” at the American Control Conference, Atlanta, 2022. The corresponding paper will be published in the conference proceedings and can be found, e.g., here.
I am happy to share that our work on connecting predictive safety filters and control barrier functions “Predictive control barrier functions: Enhanced safety mechanisms for learning-based control” will be published in the IEEE Transactions on Automatic Control in May 2023.
Our paper Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers has been accepted for the 4th Annual Learning for Dynamics & Control Conference at Stanford and was selected for oral presentation.
My doctoral thesis has been published, which I successfully defended in September 2021.
Spotlight talk at IROS 2021 Workshop on Safe Real-World Robot Autonomy: Summarizes some of the more recent work on predictive safety filters.
A predictive safety filter for a miniature racing application and its combination with imitation learning to safely learn an expert policy: Preprint
I’m currently working at Bosch Central Research on the safe control of uncertain dynamical systems. Before, I was a postdoctoral researcher in the intelligent control systems group at IDSC ETH. My research interests are in Safe Learning Control, Model Predictive Control, and Model-based Reinforcement Learning; see also my Google Scholar profile.
For a detailed CV, see my LinkedIn profile.