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Prof. Dr. Ralph Bergmann

Contact +49 651 201 3876 (Trier)

https://www.dfki.de/bergmann
Address (Trier) Gebäude HBehringstraße 21D-54296 Trier
Prof. Dr. Ralph Bergmann

Publications

Mirko Lenz; Ralph Bergmann

In: Max Bramer; Frederic Stahl (Hrsg.). Artificial Intelligence XLI. SGAI International Conference on Artificial Intelligence (AI-2024), 44th SGAI International Conference on Artificial Intelligence, December 17-19, Cambridge, United Kingdom, Pages 189-203, Lecture Notes in Computer Science (LNCS), Vol. 15446, ISBN 978-3-031-77915-2, Springer Nature Switzerland, Cham, 2025.

To the publication

Alexander Schultheis; Benjamin Alt; Sebastian Bast; Achim Guldner; David Jilg; Darko Katic; Johannes Mundorf; Tobias Schlagenhauf; Sebastian Weber; Ralph Bergmann; Simon Bergweiler; Lars Creutz; Guido Dartmann; Lukas Malburg; Stefan Naumann; Mahdi Rezapour; Martin Ruskowski

In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Springer, 9/2024.

To the publication

Profile

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.

  • KI-AIM

    AI-based anonymization in medicine

    The use of artificial intelligence (AI) offers the opportunity to fundamentally support and revolutionize knowledge-intensive activities. In business and many scientific disciplines, the changes…

  • KIAFlex

    Interactive AI assistance for predictive and flexible control in discharge and transition management

    Ensuring optimal and continuous care for patients is a major challenge in the German healthcare system. Discharge management plays a key role in this process because it is responsible for continuity…

    KIAFlex
  • DZW

    Digital twin in water resource management

    Being able to guarantee unrestricted access to fresh drinking water is generally taken for granted. However, the appearance of clean water is deceptive - climate change and urbanization in particular…

  • myRPA

    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…

  • SPELL

    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…

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