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The University of Piraeus was founded in 1938 under the title of the “School for Industrial Studies”, by the Industrialists and Tradesmen Association, while in 1989 it was renamed to "University of Piraeus" with several academic departments. Since 2020, ten departments are run by the University of Piraeus, focusing on various academic topics that range from economics, financial management and business administration to industrial management, maritime studies and informatics and digital systems. The Department of Digital Systems covers the areas of services, data management and analytics, network management as well as the security of digital systems. The department’s research staff consists of 25 faculty members, 21 postdoctoral researchers and 87 PhD candidates, whose collective expertise covers many key areas in distributed systems and services. The University of Piraeus Research Center (UPRC) facilitates the research activities of university members in different programmes and initiatives. In this context, UPRC has been actively involved and coordinated a number of European and National R&D projects, as well as projects developed in collaboration with enterprises (both international and national). UPRC participates in STAR with the team members of the Data & Cloud Research Group ( The group members research on AI, data management and analytics, focusing on machine and deep learning algorithms for various application domains (including health, retail, transportation and agriculture), as well as techniques for data modelling (through flexible schemas), data quality assessment and incremental analytics.

Role in the project
UPRC team members will lead the research in STAR with respect to explainable AI (XAI) exploring different XAI techniques for Deep Neural Networks (DNNs), while also researching and implementing the concept of simulated reality (SR) in order to enable AI systems to operate in dynamic, unstructured and mostly unpredictable environments. Furthermore, UPRC will focus on defining the vision and specifications for safe and human centric AI in manufacturing by coordinating the project efforts on the requirements and state of the art analysis on eliciting, collecting and analysing requirements regarding safe, secure and human centered AI in manufacturing environments.