Artificial Intelligence / Data Science

Artificial Intelligence / Data Science has been identified as a new scientific competence field for the Science Master Plan. Learning systems are becoming the driver of digitization in business and society everywhere today. They permeate all areas of the working world and everyday life. Robots, assistance and software systems are already working on complex problems. In Dortmund, scientists are researching both technical improvements and algorithms to improve production processes, for example, and the interface between humans and machines.

Source: FH Dortmund/Volker Wiciok

The following institutions are active in this field:

TU Dortmund University

Dortmund has a long-standing reputation for Data Science since it was the first university in Germany to establish a degree program in statistics. The Dortmund Data Science Center (DoDSc) bundles methods from statistics, computer science and mathematics in interaction with the sciences of physics, chemistry and chemical biology as well as with journalism. This provides an umbrella within the TU Dortmund University for interdisciplinary exchange on research, teaching and transfer. This provides an excellent framework for cooperation with other universities and institutes.

Artificial intelligence (AI) also has a long tradition at the TU Dortmund University. A corresponding chair was established as early as 1991. Even then, machine learning was recognized here as the key discipline of AI. The startup RapidMiner was born there and the system of the same name is continuously in the leading quadrant of the Gartner Group.

Meanwhile, capacity in AI has been built: Professorships on Pattern Recognition (Prof. Dr. Gernot A. Fink), Data Mining (Prof. Dr. Erich Schubert), Data Science and Data Engineering (Prof. Dr. Emmanuel Müller), and Smart City Science (JProf. Dr. Thomas Liebig) will soon be complemented by an endowed professorship on machine learning in industrial applications, established by KION Group AG, a provider of forklift trucks, warehouse technology and related services, and supply chain solutions. In the Faculty of Statistics, the professorships on Statistical Methods for Big Data (Prof. Dr. Andreas Groll) and the professorship on Statistics in Industrial Applications (Prof. Dr. Markus Pauly) endowed by Deutsche Post AG were filled in 2019. Appointment procedures are currently underway for the professorships of Artificial Intelligence (successor Prof. Dr. Katharina Morik) and Computational Statistics (successor Prof. Dr. Claus Weihs).

In the Collaborative Research Center (SFB) 876 “Availability of Information through Analysis under Resource Constraints” brings together Big Data, machine learning and embedded systems. This innovative connection opens up possibilities for real-time processes, such as in firefighting or autonomous sensor-actuator systems. The basic orientation yields reliable statements on the quality of learned models with respect to model quality and resource consumption.

Competence Center Machine Learning Rhine-Ruhr (ML2R)

With the acquisition of the ML2R, the research area of artificial intelligence/machine learning has been strengthened and gained great supra-regional visibility. The center, which is funded by the German Federal Ministry of Education and Research (BMBF), is one of six nationwide centers for cutting-edge research and transfer in the field of artificial intelligence. Cooperation partners are the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS in Sankt Augustin, the University of Bonn and the Fraunhofer Institute for Material Flow and Logistics IML in Dortmund. Prof. Dr. Katharina Morik, head of the Chair of Artificial Intelligence at TU Dortmund University, also coordinates all six centers. This is why the Federal Minister of Education and Research, Anja Karliczek, has already visited TU Dortmund University twice.

Fachhochschule Dortmund - University of Applied Sciences and Arts

At Fachhochschule Dortmund – University of Applied Sciences and Arts, too, the subject area of AI represents an important focus in research and teaching. Here, AI methods and applications are considered both from the perspective of the methodological-theoretical fundamentals and from the perspective of application in the most diverse subject areas. Accordingly, the topic of AI is also taken up at various departments.

At the Department of Computer Science, AI is represented by Prof. Dr. Sebastian Bab, Prof. Dr. Britta Böckmann, Prof. Dr. Christoph Friedrich and Prof. Dr. Sabine Sachweh. Prof. Dr. Bab (Chair of Applied Logics and Artificial Intelligence) is especially dedicated to classical, symbolic AI and its relation to logic up to the topics of machine learning and natural language processing. Prof. Dr. Böckmann and Prof. Dr. Friedrich are dedicated to the application of AI and machine learning methods in the field of (bio)medical informatics, among others in the DFG-funded research training group WisPerMed. Prof. Dr. Sachweh at the Institute for the Digitization of Work and Living Environments (IDiAL) also considers ethical aspects of the application of AI in particular.

At the Department of Information Technology, AI is represented in the profile focus Intelligent Information and Communication Systems and at the Institute of Communication Technology by Prof. Dr. Ingo Kunold (Communication Technology and Digital Signal Processing) and Prof. Dr. Hendrik Wöhrle (Intelligent Autonomous Sensor and Actuator Systems). AI methods and technologies are considered in particular in the context of communication technology and the Internet of Things with the areas of Smart Systems, Smart Energy and Smart Homes/-Buildings and Cities. Another focus is the use and application of real-time AI technologies on embedded systems and the development of efficient hardware for machine learning. Prof. Dr. Jörg Thiem and Prof. Dr. Andreas Becker deal with the use of AI in robotics and automotive. Another research area is the application of AI in the field of biomedical engineering, which is represented by Prof. Dr. Sebastian Zaunseder and Natalie Mrachacz-Kersting.

In the Department of Electrical Engineering, the teaching area of Prof. Dr. Kai Luppa is software development, energy automation and network management. Here, among other things, work is done on the topics of data analysis and AI for future control systems in the energy industry. Efficient microelectronic systems for AI and sensor data analysis using machine learning methods are developed by Prof. Dr. Michael Karagounis. In addition to the technical aspects of AI, societal impacts are also playing an increasingly important role. In this regard, Prof. Dr. Claudia Streblow-Poser at the Department of Applied Social Sciences is dealing with the effects of AI on social work and the related ethical issues.

Fraunhofer Institute for Material Flow and Logistics IML

Fraunhofer IML conducts research on AI topics in a number of projects funded by the German federal and state governments. These include the BMBF-funded competence center “Machine Learning Rhine-Ruhr” (ML2R, see above) and the research project “ai arena” for the establishment of a practice-oriented AI laboratory for interdisciplinary and collaborative research on machine learning for robot swarms, the BMVI-funded project on the Silicon Economy, which aims to establish an infrastructure for AI-driven autonomous systems and processes of tomorrow’s logistics, the BMWi-funded Mittelstand 4. 0 competence center “Digital in NRW”, which transfers AI know-how to SMEs by means of AI trainers, and the logistics and IT performance center funded by the MKW NRW, which connects Dortmund AI researchers in its “Machine Learning Research Clan” in a cross-institutional and purpose-oriented manner. Fraunhofer IML cooperates intensively with local research partners in the fields of AI / data science and logistics (TU Dortmund University, chairs of the faculties of mechanical engineering, computer science, statistics, electrical engineering and information technology; IfADo; Max Planck Institute for Security and Privacy) as well as international institutions (e.g. TNO, TKI DINALOG, Georgia Tech Atlanta).

AI research at Fraunhofer IML is also broadly positioned in the area of industrial contract research – from research and training of autonomous systems in general (e.g. by means of reinforcement learning) and the development of autonomous transport robots such as LoadRunner® in particular, to diverse tasks in the area of computer vision (e.g. for counting or (quality) control). This includes, for example, the counting or (quality) measurement of logistical objects, resources, or documents, the development of AI-based assistance systems for the optimization of supply chains (e.g., for the creation of demand forecasts), and topics related to the planning and operation of logistical networks (e.g., route analyses or forecasts of arrival times).

Federal Institute for Occupational Safety and Health (BAuA)

At BAuA, AI is considered both as a tool for designing safe and healthy work, but also as a component to be safeguarded in products and work systems. For example, text analysis AI is being developed to detect potentially hazardous products. In another project, the impact of AI use in cyber-physical systems on risk analysis processes is being investigated together with corresponding adaptation options.

City of Dortmund / Master Plan Digital Education

With the Master Plan Digital Education, the city of Dortmund is also taking a look at the topic of AI, e.g. in relation to vocational training, but also for the general school sector. Imparting knowledge about AI at an early stage and promoting interest among learners form the basis for producing more talent for Dortmund as a business and technology location in the future. In educational institutions, AI becomes a means and an object of learning. This is supported by the Media Competence Framework NRW, which is mandatory for schools to apply.

City of Dortmund / Institute for Fire and Rescue Technology (IFR)

One field of application is offered by research at the IFR of the City of Dortmund. Here, new technologies and concepts for fire protection, rescue services and civil protection and disaster management are tested. One example of this is the research project led by the IFR with a focus on establishing a German Rescue Robotics Center (A-DRZ), which is funded by the BMBF. In a so-called “Living Lab”, end users (= non-police authorities and organizations with security tasks, BOS), research and industry jointly test the developed systems for their operational suitability. AI is seen and researched here as an important factor for supporting process flows in logistics, situational awareness, mission support, as well as for automating robot operations and for training.

Max Planck Institute "Cybersecurity and Safety"

The Max Planck Institute “Cybersecurity and Safety” is jointly supported by the Ruhr University Bochum and the TU Dortmund University. Synergies with the study of trustworthy AI, machine learning as well as occupational safety (BAuA) are long-term.

In November 2020, the 4th Dortmund Science Conference was held digitally for the first time. The guiding theme of the conference was Artificial Intelligence.

Transfer and networking

The research field of artificial intelligence is interwoven with several other scientific research and competence fields in an interdisciplinary manner. For example, there is a long-standing, fruitful collaboration with the scientific competence field of logistics. There is also great potential in the combination with other fields, especially biotechnology, which will be used even more systematically in the future.

In addition, the Dortmund environment is the ideal place for the interaction of industry and innovation. The research and training side is completed by companies such as Wilo and by institutes such as the Leibniz Institute for Analytical Sciences – ISAS – e.V., the Leibniz Institute for Labor Research at the TU Dortmund University (IfADo) and the Social Research Center Dortmund (sfs).

Initially, the cooperation in the scientific competence field of AI / Data Science is to be expanded and consolidated, structures of cooperation are to be defined, common topics and further actors are to be identified.

For the first joint projects, the participants have agreed on the following main topics, which will be worked on in sub-working groups:

  • Machine learning in education, training and further education
  • Real-time AI
  • Trustworthy AI and security

    Participating organizations