Applied Artificial Intelligence

Contact

Group Lead

Prof. Dr.-Ing. Daniel Sonntag

Office

Office hours by appointment

Address

Stiftungsprofessur Künstliche Intelligenz
Marie-Curie Str. 1
D-26129 Oldenburg

See also

Applied Artificial Intelligence

The “Applied AI” research group, which is part of the Interactive Machine Learning research department at the German Research Center for Artificial Intelligence (DFKI), focuses on applying and adapting artificial intelligence methods to, for example, industrial and medical applications. Sustainability is also a major topic in Oldenburg.

Research-relevant application aspects primarily concern the use of learning systems and intelligent user interfaces. Key areas of focus include multimodal input and output and multisensor applications involving environmental and state recognition, sensor data processing, and issues of real-time performance and interactivity when learning from very large or very small datasets, as well as reliability aspects (including trust in AI and explainable AI).

Regardless of specific subject areas, the overarching research goal is to develop guidelines for the practical application of artificial intelligence. In addition, basic research is conducted in the interdisciplinary field of human–machine interaction in combination with machine learning.

Student AI transfer projects are especially important to us. You can find a selection here: iml.dfki.de. For Bachelor's or Master's theses, please contact or .

News

Best Student Paper Award at the BUIS Days 2025

Hannes Kath, Thiago S. Gouvêa and Daniel Sonntag received the Best Student Paper Award at the 14th BUIS Days 2025 - the VLBA Symposium in Oldenburg from 5 to 6 June 2025 - for their contribution "A Look Under the Hood of the Xprize Rainforest Competition System" was honoured.

The conference, which took place at ecos work spaces and focussed on the use of operational environmental information systems in smart and sustainable infrastructures, brought together over 60 participants and 32 accepted papers. Supported by the Centre for Digital Innovation Lower Saxony (ZDIN) and the Oldenburgisch-Ostfriesischer Wasserverband (OOWV), the event honoured outstanding work in three Best Award categories.

The winning paper highlights the Xprize Rainforest competition system and presents innovative tools such as YAPAT for annotating extensive bioacoustic data sets. With the help of methods such as active learning, transfer learning and audio separation, the researchers contribute to the efficient identification of species and the monitoring of biodiversity.

Hannes Kath, Thiago S. Gouvêa and Daniel Sonntag were awarded the Best Student Paper Award at the 14th BUIS Days 2025 - the VLBA Symposium in Oldenburg from 5 to 6 June 2025 - for their contribution "A Look Under the Hood of the Xprize Rainforest Competition System" was honoured.

The conference, which took place at ecos work spaces and focussed on the use of operational environmental information systems in smart and sustainable infrastructures, brought together over 60 participants and 32 accepted papers. Supported by the Centre for Digital Innovation Lower Saxony (ZDIN) and the Oldenburgisch-Ostfriesischer Wasserverband (OOWV), the event honoured outstanding work in three Best Award categories.

The winning paper highlights the Xprize Rainforest competition system and presents innovative tools such as YAPAT for annotating extensive bioacoustic data sets. With the help of methods such as active learning, transfer learning and audio separation, the researchers contribute to the efficient identification of species and the monitoring of biodiversity.

(Changed: 11 Feb 2026)  Kurz-URL:Shortlink: https://uol.de/p79699n11904en
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