Prof. Dr. Ralph Bergmann

  • Address (Trier)
    Gebäude F
    Behringstraße 21
    D-54296 Trier

Prof. Dr. Ralph Bergmann


Lukas Malburg, Manfred-Peter Rieder, Ronny Seiger, Patrick Klein, Ralph Bergmann

In: The 12th International Conference on Ambient Systems, Networks and Technologies (ANT) / The 4th International Conference on Emerging Data and Industry 4.0 (EDI40) / Affiliated Workshops. International Conference on Emerging Data and Industry 4.0 (EDI40-2021) March 23-26 Warsaw Poland Pages 581-588 Procedia Computer Science 184, 2021 Elsevier 2021.

To the publication
Lukas Malburg, Maximilian Hoffmann, Simon Trumm, Ralph Bergmann

In: Proceedings of the 34th International Florida Artificial Intelligence Research Society Conference. International FLAIRS Conference (FLAIRS-2021) North Miami Beach Florida United States FloridaOJ 2021.

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Short Biography

Ralph Bergmann is full professor at Trier University since 2004 and is directing a research group on business informatics with a strong focus on Artificial Intelligence. Since 2020 he is topic-field leader for experience-based learning systems (EBLS) within the Trier Branch of the German Research Center for Artificial Intelligence. He led approx. 35 projects, funded by the European Union, the German Research Foundation (DFG), the Federal Ministry of Education and Research (BMBF), the state of Rhineland-Palatinate, as well as by industrial companies. He authored more than 200 scientific papers (h-index 40), including four books and 13 edited proceedings volumes.

Over the past 30 years, Ralph Bergmann has significantly contributed to the foundations and applications of AI, including knowledge-based systems, knowledge representation and reasoning, case-based reasoning, machine learning, AI planning, and semantic technologies.

With the current focus on experience-based learning systems he aims at developing hybrid AI-systems integrating data-oriented AI methods (machine learning and case-based reasoning) with semantic technologies (ontologies and knowledge graphs) for modeling explicit knowledge. In current projects, he explores how experience-based learning systems can enable process redesign, adaptation, and flexible execution, and how process data can be analyzed with respect to resource and process diagnostics. Application fields include Industry 4.0 and other cyber-physical systems, construction, crisis management, service, medicine, cooking, and political argumentation.


Experience-based Robotic Process Automation for Knowledge-based Personal Assistants

Robotic Process Automation (RPA) enables further automation of processes across existing systems. As RPA can act like humans and thus is able to read, transfer, and enter data in graphical user…


Semantische Plattform zur intelligenten Entscheidungs- und Einsatzunterstützung in Leitstellen und Lagezentren

Artificial intelligence in the interconnected control center of the future

The SPELL project represents the idea of a semantic platform for intelligent decision-making and deployment support in…


Preliminary study for the realization of a case-oriented decision support system for treatment recommendations of skin cancer.

In the case of advanced skin cancer, treatment decisions are often based on the personal experience of the treating physician due to a lack of evidence. Significant progress can be made here with a…


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz