Research

My research interests lie at the intersection of Deep Learning, dynamical system modeling and optimization-based control. I use deep neural networks based control and reinforcement learning for control of real-world systems such as energy systems (heating networks, power systems, heat pumps, buildings, thermomanagement of EVs) and process control (coating processes). 

Teaching

Lecturer at bachelor's course on linear systems and control theory, since SS2021.

Lecturer at master's course Model predictive control for renewable energy systems SS2023

Short Bio

Lilli studied Computer Science and Applied Mathematics at University of Paderborn, University College London and EPFL Lausanne. In 2018, she obtained a PhD degree in the Scientific Computing department of the University of Heidelberg on the topic "Fast numerical methods for optimal control under uncertainty". Since then, she been working at Fraunhofer ISE in the Building Systems Technology group. Lilli joined the syscop team as a part-time postdoc in 2021.