ABOUT ME
I completed my Bachelor's degree in Mechatronics/Robotics and my Master's degree in Embedded Systems Engineering at UAS Technikum Wien, where I have been working as a Junior Lecturer/Researcher since March 2020. Ever since doing an internship at the Telekom Innovation Laboratories in Berlin, my interest in engineering has revolved around modern control approaches in robotics. I especially enjoy using modern algorithms in the domain of data-driven robotics to efficiently improve processes (yes, that includes the buzzwords AI and machine learning).
PUBLICATIONS
This section presents the publications of which I was the first author; all of which has been performed as part of my research at FH Technikum Wien. A full list of publications I was involved in is provided on my researchgate profile.
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Deep Reinforcement Learning for Continuous Robot Trajectory Control 2022
Continuous trajectory planning for 7DOF robots using various reinforcement learning algorithmns.
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Explainable Artificial Intelligence For Robot Arm Control 2021
Explainability examination of models performing discrete trajectory planning for 3DOF robots using policy iteration.
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Open Loop Robot Control using Deep Q-Learning 2021
Discrete trajectory planning for 3DOF robots using multi-goal reinforcement learning.
PROJECTS
This section presents projects that I am either working on in my leisure time or publicly available projects that I have been part of professionally.
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ROS Machine Learning Container
Docker-based ROS development environment combining scientific computing frameworks such as PyTorch and Scikit-Learn with ROS (Noetic or Humble) utilising various graphics hardware acceleration techniques. This workspace has been utilised for my master thesis, serves as the basis of my homelab's machine learning instances and is used as the development environment for tinysim.
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Tinysim
A lightweight time-discrete mobile robot simulator for ROS 2. It can reconstruct simulation scenes from recorded sensor data (3D or 2D maps) and simulate various sensors utilisting Open3D.
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AI Anwenden und Verstehen (in German)
Research project that aims to explain both fundamental as well as state of the art concepts from the domain of artifical intelligence to small and medium-sized businesses. Apart from presenting fundamental theory surrounding AI, our website also presents blog posts about practical AI use cases as well as a list of institutions in Austria working on AI.
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Homelab
Automatically deployed, self-hosted services including machine learning instances and cloud storage using Docker, Ansible and Nextcloud. The machine learning instances are based on my ROS Machine Learning Container.