Welcome to my Website!

My name is Niklas and I am pursuing a PhD degree under the supervision of Jan Peters at the Intelligent Autonomous Systems Group at TU Darmstadt.

Previously, I have obtained a Bachelor's degree in Electrical Engineering and Information Technology, as well as a Master's degree in Robotics, Systems and Control from ETH Zurich.

Research Interests

Generally speaking, I am interested in all sorts of algorithms and methods enabling and advancing Intelligent Systems. In the past years, I have especially focussed on the intersection between Machine/Reinforcement Learning and Control. Besides trying to make the ideas work in simulation, I am also particularly interested in real-world demonstrations.

Practical Experience

In the past, I have been participating in several research and applied projects.

My journey in the field of Robotics started with "Project ARC" in the last year of my Bachelor's. The goal of this project was to climb a Swiss mountain pass autonomously, using the Teach & Repeat method. (Link to video of an autonomous drive.)

After finishing the second semester of the Masters, I joined an interdisciplinary project at the intersection between Robotics and Synthetic Biology. The goal of Project "AROMA" was to build a mobile robotic platform capable of smelling.

During my Master's, I also completed a research internship at the Bosch Center for Artificial Intelligence in Renningen. At the time, I gathered first experience in working with deep reinforcement learning algorithms.

I then started my Semester Project together with Matthias Hofer in Prof. D'Andrea's group at ETH Zurich. The goal of this project was to conduct gray- and black-box model identification for the control of an articulated soft robotic arm.

At the Max-Planck Institute for Intelligent Systems, I finished off my Master studies. My thesis on "Learning Event-triggered Control from Data through Joint Optimization" was supervised by Dominik Baumann and Sebastian Trimpe.

Before starting the PhD in Darmstadt, I joined NVIDIA for a remote internship as Deep Learning Software Intern.