Dominik Baumann

Postdoctoral Researcher



Phone: +49 241 80 92053

I am a postdoctoral researcher at the DSME at RWTH Aachen. My research focuses on enabling provably stable and resource-efficient control of (typically wireless) cyber-physical systems. For this, I use both tools from control theory and machine learning and integrate them with communication systems. Further, I am interested in understanding how autonomous systems can automatically infer causal structure.

Before joining DSME, I studied electrical engineering at TU Dresden where I graduated in 2016. I then started as a joint PhD student with the Max Planck Institute for Intelligent Systems and KTH Stockholm and defended my thesis in 2020.

Talks and Poster Presentations

  • Poster: "Distributed and event-based wireless control of cyber-physical systems," PhD School on Cyber-Physical Systems, Lucca, Italy, Jun. 2017.
  • Talk: "Distributed and event-based wireless control of cyber-physical systems," Seminar at KTH Royal Institute of Technology, Stockholm, Sweden, Aug. 2017.
  • Poster: "Learning to save communication," Max Planck ETH Workshop on Learning Control, Zürich, Switzerland, Feb. 2018.
  • Talk: "Fast and resource-efficient control of wireless cyber-physical systems," Reglermöte (Swedish Control Conference), Stochkolm, Sweden, Jun. 2018.
  • Poster: "Deep reinforcement learning for resource-aware control," Bosch Conference on Artificial Intelligence, Renningen, Germany, Nov. 2018.
  • Talk: "Feedback control goes wireless," GMA Meeting, Günzburg, Germany, Mar. 2019.
  • Talk: "Fast and resource-efficient control of wireless cyber-physical systems," GMA Meeting, Anif, Austria, Sep. 2019.
  • Poster: "Feedback control goes wireless," Digitalize in Stockholm, Stockholm, Sweden, Nov. 2019.
  • Talk: "Feedback control and causal identification for cyber-physical systems," Seminar at Uppsala University, Uppsala, Sweden, Dec. 2019.
  • Talk: "Control-guided communication: Efficient resource arbitration and allocation in multi-hop wireless control systems," IEEE Conference on Decision and Control, Nice, France, Dec. 2019.
  • Talk: "Wireless control of cyber-physical systems," Seminar at ETH Zurich, Zurich, Switzerland, Jan. 2021.
  • Talk: "Wireless control of cyber-physical systems," GMA Meeting, Günzburg, Germany (virtual), Mar. 2021.
  • Talk: "Causality in learning-based control," Research Seminar on Artificial Intelligence, RWTH Aachen University, Aachen, Germany, Sep. 2021.


  • Best paper award at the ACM/IEEE International Conference on Cyber-Physical Systems 2019.
  • Best demo award at the ACM/IEEE International Conference on Information Processing in Sensor Networks 2019.
  • 2019 Future Award of the Ewald Marquardt foundation.

Supervised Student Projects

  • Oleksandr Zlatov, "Deep reinforcement learning for resource-aware control", University of Tübingen.
  • José Mario Mastrangelo, "Predictive triggering for multi-agent systems", ETH Zürich.
  • Niklas Funk, "Learning event-triggered control - Leveraging hierarchical reinforcement learning algorithms to obtain resource-aware controllers", ETH Zürich.
  • Erik Hörmann, "Causality for learning control", Sapienza University of Rome.
  • Hannah Markgraf, "Toward safety guarantees for deep neural network controllers: Stability analysis of reinforcement learning policies", RWTH Aachen (main supervisor: Emma Pabich).
  • Bhavya Sukhija, "Globally optimal safe robot learning", ETH Zürich (co-supervisor: Matteo Turchetta).
  • Yannick Streicher, "Learning dynamics equations of a novel rotational inverted pendulum", University of Tübingen.

Academic Community Services