I'm a PhD researcher in Systems and Control at Delft University of Technology currently working on the intersection of Reinforcement Learning (RL) and Model Predictive Control (MPC). My research focuses on developing novel control methodologies that combine model-based and learning-based approaches for control tasks.
Specifically, I work on using MPC as a model-based function approximation scheme for RL algorithms. This allows us to leverage prior knowledge about the system dynamics and constraints while still being able to learn and adapt from data. I'm also interested in safety-critical systems, and working on Control Barrier Functions in combination with MPC and RL. Other recent work of mine includes developing nonmyopic optimization strategies for global optimization, designing MPC-RL approaches for greenhouse climate control, and creating safe learning frameworks with the help of Gaussian Processes.
I collaborate closely with Professors Bart De Schutter and Azita Dabiri @ Delft Center for Systems and Control.
Publications
