Interactive visual metamorphosis investigates a new way for interactive data exploration: Instead of looking at multiple static views in parallel, users will smoothly travel between dynamically changing views. During this traveling, users will accumulate the insight necessary to comprehensively understand the data. Visual and conceptual gaps between non-trivial visualization views are narrowed by employing smooth display transitions that transform one visual representation into another one. Through the visual part of the metamorphosis, it will be easier for users to transfer insights from one visual representation to another. The interaction part will allow user to control and steer the metamorphosis.
[German Resarch Fondation (DFG), 2024 - 2026]
CombiDiag is a Marie-Curie Doctoral Network funded by the European Union. The mission of CombiDiag is to develop an AI-based diagnostic protocol for early-stage Alzheimer's disease using peripheral biomarkers. The project also aims to train a new generation of interdisciplinary experts. Alzheimer's is a major global challenge, and CombiDiag seeks to address it by studying minimally invasive biomarkers from bodily fluids and digital markers from speech and other sources. The project involves collaboration between academic and non-academic institutions across the globe.
[European Union, 2023 - 2027]
Das Projekt KI-Med-Kollaborationsplattform (KiMeKo) setzt sich das Ziel, bestehende Kompetenzen aus mehreren KI-Med-Initiativen in fünf Teilprojekten zu bündeln. Durch diese thematische Fokussierung und den Einsatz standardisierter Methoden und Werkzeuge soll die Entwicklung von KI-basierten Medizinprodukten signifikant beschleunigt und unterstützt werden. Diese Plattform dient als Grundlage für eine dynamische Zusammenarbeit zwischen Forschenden, Medizinern und Unternehmen, um zukunftsweisende und disruptive Innovationen in der gesundheitlichen Versorgung voranzutreiben.
[Federal Ministry of Research, Technology and Space (BMWTR),
2024 - 2027]
Das Flagship Projekt OTC-DaTA des Ocean Technology Campus Rostock-Zukunftsclusters (https://www.oceantechnologycampus.com) entwickelt das grundlegende Framework des Digital Twins für das Management maritimer Missionen.
Ziel von URO-VAC ist die Entwicklung von hybriden neuro-symbolischen Datenanalysestrategien, die eine energie- und bandbreiteneffiziente (Echtzeit-) Analyse von multimodalen Meeresdaten ermöglichen. Insbesondere zielen wir darauf ab, Strategien zu entwickeln, die es erlauben, Vorwissen über algebraische Eigenschaften von Daten in Modelle des tiefen Lernens (deep learning) zu integrieren.
[Federal Ministry of Research, Technology and Space (BMFTR),
2024 - 2027]
The Center for Artificial Intelligence brings together practice and academia by first providing information and advice to interested SMEs. Through individual consultations, we examine the specific, unique context of each company.
[Mecklenburg-Western Pomerania Ministry for Economic Affairs, Infrastructure, Tourism and Labour,
2024 - 2030]
Development of methods to support the development, calibration and validation of cognitive agent-based simulation models with a lack of real data. Within the case study, different application areas (e.g. economics, epidemiology
& sociology) are examined.
[German Research Foundation (DFG), 2025 - 2027]
Multimodal generative AI for turning natural-language interaction with complex software systems into machine-processable instructions. (Show2Instruct)
This project develops a generative AI technology basis for human-machine interfaces. The goal is not only natural-language operation of software and machines through large language models, but also the ability to include visually recognized objects from the local system context in prompts.
[Federal Ministry of Research, Technology and Space (BMFTR),
2025 - 2028]
Cell and gene therapies are considered key elements of modern medicine. They offer new treatment options for severe and previously incurable diseases such as cancer or autoimmune disorders. By individually utilizing customized cells, diseases are expected not only to be alleviated but even permanently cured in the future. A central component of the interdisciplinary collaborative project is the use of Artificial Intelligence (AI) to create digital twins of complex dynamic systems to optimize manufacturing processes, enhance quality, and bring new therapeutic approaches to patients more quickly.
[Land MV / Europäische Union, 2025 - 2028]
Subproject within research consortium AI-ANIMAL WELFARE "WP6: Technologies for animal welfare detection"
The primary objective of the project is to establish the technological infrastructure for non-invasive monitoring of animal welfare. To achieve this, the work will integrate and refine existing tools while introducing novel methodologies to ensure objective data collections. A key focus is the implementation of AI-driven automation, designed to streamline operational workflows for staff while simultaneously elevating standards of animal care.
[Federal State MV / European Union, 2025 - 2029]
ADAPT-AI addresses a key challenge in data-driven applications: machine learning models often do not transfer well to new environments, resulting in substantial manual effort for data annotation. The project develops methods for efficiently adapting time-series models to new domains, such as different sensor configurations or operating environments.
[Federal Ministry for Economic Affairs and Climate Action (BMWK), 2025 - 2029]
Subproject within research consortium ADAPTI-M "WP3: Intelligent NPI-Strategy-Generation and Optimization"
Subroject within research consortium BehAIve "WP2: Hybrid Neurosymbolic and Neuroprobabilistic Models for the Analysis of Dynamic Systems"
The joint project develops innovative solutions and support systems for older people in their home environment.The aim is to improve quality of life while reducing the burden on nursing staff.
Subproject led by Prof. Dr.-Ing. Thomas Kirste, focuses on providing the system component for activity and situation recognition, developing scenario-specific parameterization for this component, and continuously refining and adapting it based on the results of the system evaluation.
[State Development Institute of Mecklenburg-Western Pomerania,
2026 - 2029]
