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 December 2025, I successfully completed my doctorate in engineering (Dr.-Ing.).

I am passionate about consulting organizations in automation and digitalization projects, with a strong focus on data-driven decision-making. My academic and applied work centers on data science, artificial intelligence, digitalization and automation, particularly in the context of large-scale (simulation) data. A key objective of my work has been the automated analysis of complex data sets, the identification of relevant patterns, and the transparent communication of results to diverse stakeholders.

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. I have also successfully completed projects such as the further development of an autograder and the integration of generative AI to digitize programming training.

Alongside my academic work, I have been actively involved in the Simulation Working Group (ASIM) of the German Informatics Society and regularly supervised student projects and theses in the areas of simulation, AI, machine learning, and visual analytics.

Today, I apply this combined expertise as a consultant, helping companies design, implement, and scale automation and digitalization solutions in the context of factory planning. In short, I bridge simulation, AI, machine learning, and digitalization to better understand complex systems, optimize processes, and communicate insights effectively for real-world decision-making.