Hi I’m Jonas! I am a PhD student at Helmut-Schmidt University in Hamburg, Germany. My research focuses on applied Machine Learning for Cyber-Physical Systems, with a special focus on using Reinforcement Learning for solving planning problems that are too large and too messy to be modeled with conventional planning algorithms.

Apart from that, I am interested in Cognitive Science and Neuroscience. I love to draw inspiration and ideas from these domains to develop algorithmic solutions for real-life problems.

Below, you can find some information on my education, experience, and recent activity in the scientific community.

Education

		PhD Artificial Intelligence in Mechanical Engineering from 2021 Helmut-Schmidt-University, Hamburg
		MSc Information Studies - Data Science 2019 - 2020 University of Amsterdam, Amsterdam
		MSc Business Administration and Engineering 2017 - 2019 University of Bayreuth, Bayreuth
		BSc Business Administration and Engineering 2013 - 2017 University of Bayreuth, Bayreuth

Work experience

		PhD Student - Artificial Intelligence in Mechanical Engineering from 2021 Helmut-Schmidt-University, Hamburg
		Student Research Assistant - Fraunhofer IPA 2015 - 2019 University of Bayreuth, Bayreuth

Activities

Here, you can find some information on my activities in the research community. For more information about my publications, visit my publications page.

2025

• Reviewing activity IEEE Conference on Emerging Technologies and Factory Automation 2025, Porto
• Organizing Committee CAIPI’25 Workshop - AI-based Planning for Complex Real-World Applications @ ECAI 2025, Bologna: link

2024

• Reviewing activity IEEE Conference on Emerging Technologies and Factory Automation 2024, Padova.
• Program Committee ML-DE (Machine Learning meets Differential Equations) Workshop at ECAI 2024, Santiago de Compostella: link
• Program Committee HYDRA (Hybrid Models for Coupling Deductive and Inductive Reasoning) Workshop at ECAI 2024, Santiago de Compostella: link
• Program Committee ML4CPS Conference 2024, Berlin: link
• Invitee Dagstuhl Seminar 24031 - Fusing Causality, Reasoning, and Learning for Fault Management and Diagnosis: link
• Organizing Committee CAIPI’24 Workshop - Planning for Cyber-Physical Systems @ AAAI 2024, Vancouver: link

2023

• Local Committee ML4CPS Conference 2023, Hamburg: link

Teaching

Here, you can find some information on courses I tutored. For more information, have a look at the teaching page.

2025

• Labs: Image Processing

2024

• Labs: Data Science
• Labs: Programming in C & Algorithms I
• Lecture: AI Crashcourse (individual lectures of the series)

2023

• Labs: Data Science
• Labs: Programming in C & Algorithms I
• Lecture: AI Crashcourse (individual lectures of the series)

2022

• Labs: Embedded Systems
• Labs: Programming in C & Algorithms I

2021

• Labs: Embedded Systems