Am 23.07.2025 findet an der Universität Stuttgart ein Industrie-Symposium zu Data & AI mit dem Schwerpunktthema AI Governance statt. Das Programm umfasst Impulvorträge sowie Berichte zu Best Practices verschiedener Unternehmen und bietet umfassend Gelegenheit zur Diskussion und zum Erfahrungsaustausch.
Continue reading →We are excited to announce the second edition of the Industry Summit on Data Product-Oriented Architectures (POA), taking place on September 18–19, 2025, at the Universität Stuttgart, Germany. More details are available here.
Continue reading →Attention students! LowCoding democratizes software development and enables non-technical people to develop innovative software solutions. A user-friendly frontend, visual interfaces and ready-made modules help with programming. Bosch uses the LowCoding platform “OutSystems” to accelerate software development. Take part in an exclusive event with Bosch, where you will get to know the functions and benefits of…
Continue reading →Dear students, we are happy to announce the next IBM on campus event on data and AI. Generative AI based on large language models is inherently data-driven; but how can we build and maintain real-work applications when the underlying data changes? Re-training models is slow and expensive. We’re going to explore faster alternatives based on…
Continue reading →Workshop Complex Data Environments
Continue reading →As the range of data platforms is rapidly evolving, the goal of this research project is to investigate and prototype upcoming architectures and technologies and to assess their applicability and potentials for industrial enterprises.
Continue reading →Tim Waizenegger: Kubernetes Operator Pattern. Theory and Best Practices Florian Fritz: “Enterprise DevOps” in IBM Cloud Hyper Protect Services Pradeep Parameshwaran: Fully Homomorphic Encryption
Continue reading →IoT-Anwendungen können durch Domänenexperten mithilfe von Entwicklungsumgebungen modellgetrieben entwickelt werden. Beim Betrieb derartiger IoT-Anwendungen können Fehlerfälle auftreten, die nicht durch existierende Monitoringsysteme erkannt werden, z.B. falsch gemessene Sensorwerte. Ziel dieses Projektes ist es, derartige Fehlerfälle mittels Datenvalidierung schon bei der modellgetriebenen Anwendungsentwicklung zu berücksichtigen und so aktiv zu einer verbesserten Fehlertoleranz beizutragen.
Continue reading →This project deals with data characteristics that often occur in industrial use cases. Therefore, it investigates how a targeted data preparation can be used to address such data characteristics. If several of these data characteristics are present in combination, purely data-driven methods are usually not able to address them sufficiently. Therefore, it will be explored how existing domain knowledge of the industry partner can be used in a targeted way to enable more meaningful analysis results. This will then be investigated and evaluated on the basis of real use cases of the industry partner.
Continue reading →Das Ziel des Forschungsprojekts ist es, Datenzustände in einer Blockchain mithilfe von Ad-Hoc-Anfragen effizient zugreifbar zu machen und dabei gleichzeitig die Datenunversehrtheit (d. h. die ursprüngliche Originalität) von gelesenen Daten sicherzustellen. Daher werden im Rahmen dieses Forschungsprojekts effiziente Anfragekonzepte für Blockchain-Datenhistorien entwickelt.
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