Research
Explore our research activities in predictive maintenance, Causal AI, Large Language Models, Knowledge Graphs, V2X architectures, and data-sovereign pipelines. Our work bridges academic inquiry and industrial application, advancing reliable, explainable, and trustworthy AI for connected mobility.
Research Projects
Ongoing and completed thesis research collaborations exploring predictive maintenance, Causal AI, time-series modeling, LLM-based reasoning, and cybersecurity in connected vehicles.
Publications
Selected peer-reviewed publications presenting our contributions to causal discovery, federated learning, V2X architectures, and demand forecasting across automotive and medical-device industries.
Open Topics
Available thesis and research topics combining Knowledge Graphs, Retrieval-Augmented Generation, prompt engineering, time-series imputation, and data sovereignty for predictive maintenance.
