Short CV
Argyro Mavrogiorgou is a Postdoctoral Researcher at the University of Piraeus, Greece (Department of Digital Systems). She received her BSc in Digital Systems in 2013 and MSc in Network-Oriented Systems in 2015, both from the Department of Digital Systems at the University of Piraeus. Since 2019, she holds a PhD from the University of Piraeus (Department of Digital Systems) in the fields of Devices and Data Integration, focusing on Internet of Things heterogeneous devices’ accessibility and management towards the successful data ingestion and integration. Her general research interests rely on the fields of data management across the complete data lifecycle, and hybrid infrastructures including cloud/edge computing environments, Internet of Things, and cyber-physical systems. In this context, she has participated in several relevant EU and National funded projects (e.g. PolicyCLOUD, InteropEHRate, CrowdHEALTH), leading research for addressing issues related to data integration and analysis, as well as data cleaning and reliability, while she has also contributed in the aforementioned fields through multiple International Conference and International Journal publications. Regarding her Academic expertise, she has collaborated as an Academic Associate with the University of West Attica, Greece (Department of Industrial Design and Production Engineering, and Department of Electrical and Electronics Engineering), the National and Kapodistrian University of Athens, Greece (Faculty of Nursing), the National Technical University of Athens, Greece (School of Electrical and Computer Engineering), and the University of Piraeus, Greece (Department of Digital Systems).
Personal Research Topics
Mechanisms for IoT Devices’ Integration
Interoperable plug’n’play mechanisms for both connecting to different IoT platforms and facilitating the automatic recognition, interaction and access to all the underlying heterogeneous IoT devices (of both known and unknown nature).
Data Cleaning Techniques
Techniques for cleaning raw data in real-time deriving from both streaming and non-streaming data sources.
Data and Data Sources Reliability Techniques
Techniques for automatically managing heterogeneous IoT data sources, estimating their levels of reliability, and finally collecting data only from the reliable and relevant ones to each connected platform.
Big Data Management Ecosystems
Tools and techniques for automatically collecting, transforming, storing, processing, and analyzing structured, semi-structured and un-structured Big Data, exploiting diverse ecosystems.
