General research interests:

• Optimal large scale control systems
• Machine learning
• Modeling and simulation of high-impact, low-probability (HILP) events

Research project:

Classical power grids are turning to more complex and networked cyberphysical systems (CPS). In this context, we investigate how to minimize the number of controller and measurement devices required for fulfilling a known set of operational requirements. Identifying such critical elements is of paramount importance in order to enhance the resilience of complex CPSs to high-impact, low-probability (HILP) events, e.g. natural catastrophes or cyber attacks.

In our research we exploit tools from optimal control theory and convex optimization such like (mixed-integer) linear programming, semidefinite programming, and dynamic programming.

This project is funded by the German Ministry of Education and Research (German: BMBF) and is done in cooperation with Siemens AG and Entega AG. See AlgoRes for more details.

• 2018 – 2022: PhD student at EINS
• 2016 – 2018: M.Sc. Electrical Engineering and Information Technology at TU-Darmstadt
• 2010 – 2015: B.Sc. Electronic Engineering at National University of Colombia in cooperation with TU-Darmstadt