DQAText: Assessing Data Quality Aspects of Texts (part of TMF - Standards and tools for data monitoring in observational health studies) is a DFG funded project that deals with developing automated quality checks for heath related data in the form of free texts. 

GNN4GC: The research in solving graph-related problems on the power grid started in the GAIN project and is now done within the project GNN4GC.
 

GraphPCBS:aims to use Graph Neural Networks to automatically optimize the schematic design of printed circuit boards.

ARDUOUS: Annotation of useR Data for UbiquitOUs Systems is a workshop series and spin-off of various collaboration works.

TextToHBM: A Generalised Approach to Learning Models of Human Behaviour for Activity Recognition from Textual Instructions is a project funded by the German Research Foundation (Deutsche Forschungsgemeinschaft).

Healthy Ageing: As the elderly population increases, automatically supporting their life is becoming a priority in the research community. To be able to provide such support, however, the focus of measuring ageing and health should shift from the current symptom-based approaches to personalised situation-aware approaches.

Super Learning Algorithms: The project focuses on the development and application of super learning algorithms for forecasting economic time series in high dimensions. It addresses challenges in current economic time series forecasting: vast number and heterogeneous predictors, non-linear predictive relationships, etc.

BehavE: Behaviour Understanding through Situation Models for Situation-aware AssistancE is a project funded by the German Research Foundation (Deutsche Forschungsgemeinschaft).

WETSCAPES2.0: WETSCAPES2.0 (sinks, links and legacies of novel ecosystems in rewetted fen landscapes) is the DFG Transregio Collaborative Research Centre 410, which deals with exploring the effects of rewetting fen landscapes and will provide a functional understanding of these new wetscapes, and address the spatio-temporal implications of peatland rewetting at landscape level and beyond. The Institute of Data Science is co-lead in the subproject Z3: Research Data Management. 

WikiBioM: This project introduces a sophisticated AI system for the agricultural sector based on a hybrid approach of symbolic ontologies and fine-tuned Large Language Models. By bridging expert knowledge with generative AI, WikiBioM provides not only real-time information but also transparent, reasoned answers (explainability), offering critical decision support for agricultural management.