Jonas Genath

My name is Jonas Genath and I obtained my master’s degree in industrial engineering from the Technical University of Ilmenau in 2019. Since the beginning of 2020, I have been working as a research assistant in two departments: “Information Technology in Production and Logistics” led by Prof. Steffen Straßburger and “Information and Knowledge Management” led by Prof. Dirk Stelzer at the Technical University of Ilmenau. In October 2025, I will successfully complete my doctorate in engineering. My research focuses on data farming, data mining, machine learning, and visual analytics in the context of large simulation data and AI. A central concern is to automatically analyze simulation results, identify relevant patterns, and present them in an understandable way.

Here are a few highlights from my data science journey. In December 2021, I presented my concept for automating knowledge discovery in simulation data at the Winter Simulation Conference. The aim was to enable less experienced users to use these methods – from experiment design and meta-learning to rule-based visualizations. Another project, published in the journal Simulation Notes Europe in 2022, presented an integrated software solution called “4farm”, which we developed in cooperation with SimPlan AG. This solution supports users in evaluating and conducting (in the cloud) large-scale simulation studies and visualizing the results. Most recently, in December 2023, I published the conference paper “How Not to Visualize Your Simulation Output Data”. In it, we highlight common mistakes in the presentation of large simulation data sets and provide clear recommendations for better visualizations fore the community.

Parallel to my research, I am involved in the Simulation Working Group (ASIM) of the German Informatics Society. I also regularly supervise students in project and thesis work, most of which deals with simulation, AI (and ML in general), and visual analytics.

In short, I combine simulation, AI, ML, and visual analysis to better understand complex systems and communicate results effectively. My goal is to prepare scientifically sound methods in such a way that they can be used immediately in practice, whether in industry or in teaching.