How can we transform large amounts of data into valuable insights? How important is artificial intelligence in developing innovative solutions for future challenges? At Ulm University, interdisciplinary teams are developing data-based technologies for the world of tomorrow.
In a world where billions of pieces of data are generated every day, extracting reliable knowledge from this flood of information is essential. At Ulm University, researchers from different disciplines are working together to explore how data can be collected, stored, analysed, and ultimately transformed into knowledge.
As the central service provider for Ulm University, we provide relevant information and services for our researchers – for example, on open access, high-performance computing, and library and IT services.
Prof. Steffen Wendzel
Communication and Information Centre (kiz)
With its interdisciplinary approach and excellent research at the intersection of mathematics, computer science, engineering, life sciences, and natural sciences, Ulm University is contributing significantly to the development of intelligent, data-driven technologies.
From Data to Knowledge encompasses a range of topics, including methodological and computational foundations of data science as well as applications of artificial intelligence and machine learning. In all of this research, considering ethical aspects is important to us. Data-intense up-and-coming fields such as autonomous driving, human–machine interaction, digital healthcare, and personalised medicine are also central to our research.
Supported by modern high-performance infrastructure, dedicated competence centres, and strong partnerships with industry and research institutions, Ulm University advances innovation and develops solutions to tomorrow’s challenges.
Ulm University is part of the nationwide DIFUTURE consortium, which is funded by the Federal Ministry of Research, Technology and Space (BMFTR) as part of the Medical Informatics Initiative (MII). The consortium integrates medical data from multiple sources and makes it accessible across sites. The aim is to improve the research and treatment of multiple sclerosis and Parkinson's disease.
At the Knowledge Infusion and Extraction for Explainable Medical AI (KEMAI) graduate school, PhD candidates at Ulm University are investigating ways to improve AI systems for image-based diagnostics. The aim is to increase accuracy while ensuring that physicians are able to understand and interpret decisions made by AI systems.
Since 2025, the supercomputer JUSTUS 3 has been operational at Ulm University. This high-performance computer supports more than100 research projects, primarily in battery research and quantum technologies, and surpasses its predecessor, JUSTUS 2, in both performance and energy efficiency. Advanced cooling technologies such as hot water cooling and heat recovery make it especially sustainable.
kiz provides Ulm University with information and communication technologies, and drives forward innovative research projects. These include projects in the field of high-performance and cloud computing, such as the statewide bwHPC system for high-performance computing and data management and the bwForCluster JUSTUS 2/3, a high-performance computer for chemistry and quantum research.
At the UZWR, applied and interdisciplinary questions from science and industry are addressed using advanced numerical methods. The centre supports research projects across a wide range of fields—for example, in bone healing or the analysis of flows and materials. As a platform for exchange and collaboration, the UZWR brings together researchers from all faculties, thereby strengthening data-intensive research at Ulm University.
“Our research aims to extract the maximum amount of information from measurement data in order to make automated driving efficient and safe.”
Prof. Michael Buchholz
Institute for Measurement, Control and Microtechnology
“We research robust and explainable AI so that critical decisions remain reliable and transparent.”
Prof. Timo Ropinski
Institute of Media Informatics
“If we want to turn data into knowledge, we need more than algorithms and computing power; we also need to reflect on concepts, methods, goals and values.”
Prof. Rebekka Hufendiek
Humboldt Centre
At the Competence Centre F³, we develop automated vehicles to operate safely and cooperatively in traffic. The centre brings together expertise from engineering, computer science, and psychology, and provides test vehicles, simulators, and other resources. Researchers collaborate on projects involving driver assistance systems, highly automated driving and cooperative driving functions.
Since 2008, the Competence Centre for eEducation in Medicine Baden-Württemberg has been designing digital teaching programmes for the Faculty of Medicine and developing a long-term eEducation strategy for higher education in medicine in the state. Through innovative formats such as the virtual shock room, the centre combines digital learning with practical experience, promoting digital skills and a flexible, practice-oriented medical education.
The Large-Scale Software Systems (LS3) Competence Centre unites the expertise of various institutes within the Faculty of Engineering, Computer Science and Psychology. Researchers develop complex software systems that ensure the reliability, flexibility and security of large, networked applications, from cloud computing and data-based processes to data protection and security.
Founded in 2021 by Ulm University and Ulm University of Applied Sciences, DASU connects science, business and society. It provides practical access to modern methods in digitalisation, data engineering, machine learning and artificial intelligence, thus promoting knowledge transfer. DASU provides practical support, particularly for small and medium-sized enterprises, and serves as a central point of contact for data-driven innovation.
Ulm University relies on close cooperations with universities, research institutions, and industry partners to turn innovative scientific solutions directly into practice. Within the From Data to Knowledge research focus, this approach generates practical applications that advance both science and industry.
For example, our researchers are investigating the potential of quantum computers for AI applications in cooperation with the DLR Institute for AI Security. At the Ulm AI Campus, various stakeholders pool their expertise to drive the further development of AI technologies. At the same time, we support early-career researchers in collaboration with Ulm University of Applied Sciences, through initiatives such as the Data Science and Analytics doctoral programme and the Computational Science and Engineering (CSE) degree programme.
At Ulm University, young scientists are conducting interdisciplinary research into future technologies. Through programmes such as KEMAI, KoRaTo and the Data Science and Analytics doctoral programme, they are developing new methods in explainable AI, data analysis and cooperative sensor technology.
Artificial intelligence is being used more and more in medicine. But how can we be sure that diagnoses are accurate, and that doctors understand them? Who will be made responsible in case of wrong treatments? The interdisciplinary research training group "Knowledge Infusion and Extraction for Explainable Medical AI" (KEMAI) at Ulm University addresses these questions. PhD students conduct research at the interface of computer science, medicine, and ethics. The German Research Foundation (DFG) is funding KEMAI with around six million euros for an initial period of five years.
Researchers from the DFG-funded Research Training Group “Cooperative aperture synthesis for tomographic radar imaging (KoRaTo)” are developing new methods to observe the Earth's surface more precisely and improve our understanding of climate change. For this purpose, they are building drones equipped with specialised radar sensors that operate in swarms. Unlike conventional measurement methods, these sensors work together to generate large amounts of data, which are then used to create high-resolution 3D images of the environment, even in hard-to-reach regions.
The Collaborative Doctoral Programme Data Science and Analytics investigates how artificial intelligence and machine learning methods can be used reliably, comprehensively and trustworthily. Researchers examine explainability and transparency, as well as how the behaviour of algorithms can be controlled and monitored during and before application. Applications range from automation and business analytics to life sciences and medicine.
More about the Cooperative Doctoral Programme Data Science und Analytics
According to the UNL Global Research Ranking, Ulm University is among the top three worldwide and first in Germany in the field of actuarial science and risk management. Data science and artificial intelligence are playing an increasingly important role in the analysis of risks and the development of modern computational models.