Research interests
• Data-based control of nonlinear systems
• Active learning in the Koopman framework
• Robot learning
Research projects
• ALeSCo: Active learning for systems and control https://www.alesco.uni-hannover.de (DFG; project number 35860958)
• Data-based control for snake robots
Short CV
I studied computational engineering and mathematics at the Technical University of Darmstadt and University of Stuttgart and hold a master’s degree in computational engineering. During my studies, I focused on robot learning and wrote my master’s thesis on ”Task-space exploration in robot reinforcement learning” [1] under the supervision of Jan Peters. Prior to joining the OBC group, I was a research intern at Davide Scaramuzza’s Lab at the University of Zurich, where I worked on differentiable simulation for learning quadrotor control [2] (video: https://www.youtube.com/watch?v=LdgvGCLB9do).
In my free time, I like to sing and play music and am a member of several ensembles. You can check out a barbershop performancehttps://www.youtube.com/watch?v=cWfiQGmPo5M) or ask me about the next concert dates if you are interested.
References
[1] J. Heeg, “Task space exploration in robot reinforcement learning.” [Online].
Available: https: //www.ias.informatik.tu-darmstadt.de/uploads/Team/DavideTateo/thesis johannes heeg.pdf
[2] J. Heeg, Y. Song, and D. Scaramuzza, “Learning Quadrotor Control from Visual Features Using Differentiable Simulation,” in 2025 IEEE International Conference on Robotics and Automation (ICRA), pp. 4033–4039. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/11128641
