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Visual Analytics Lab

The main purpose of the Visual Analytics Lab is to conduct basic and applied research in topics related to:

  • Seamless data visibility and analysis and learning from historic data; real-time tracking and response audio-based predictive analytics
  • Interactive visualization, voice-based interaction technologies, personalized content access multimodal interfaces dynamic dashboards, and remote information sharing adaptive intelligent systems
  • Data-driven decision support and big Data analytics to inform better, faster, and more cross-functional decision making.

Alongside, VAlab has been actively researching technologies and applications to provide solutions for the Healthcare sector with emphasis to algorithms, tools and applications for digital health interventions; intelligent medical decision support; promotion of healthy lifestyle behaviors; ageing interventions; early detection of symptoms and interventions to prevent the disease from progressing, etc. 

Also, during the last few years, the lab has been very active in the cybersecurity but also physical security domain. So, the lab focuses on research to address the security and privacy challenges of distributed assisted living platforms and related health related IoT ecosystems, AI security, 5G security, automotive security, security verification and penetration testing, cryptographic solutions and security by design approaches. Finally, our research activities include decentralized ledger architectures (blockchain); privacy-preserving and personalized data analysis among trusted ecosystems; and data sovereignty technologies and distributed digital identities. 

Call for any questions

+30 2311 257 722


+30 2311 257 732


Our main scientific directions

Our excellent team is expertized in different scientific areas.

In the laboratory, there is also active a working group in Remote Sensing, with a focus on the research and development of applications and computational processes.

Novel decision support systems that encapsulate hypothesis testing methods as well as research on innovative decision support models that are based upon simulation of real business processes and market conditions.

Self-training algorithms fully exploiting historical data with robust capabilities for detecting patterns in real-time, including technologies for predictive analytics.

The Visual Analytics Lab is affiliated with the Z-Inspection® Initiative.

Z-Inspection® is a holistic process used to evaluate the trustworthyness of AI-based technologies at different stages of the AI lifecycle. It focuses, in particular, on the identification and discussion of ethical issues and tensions through the elaboration of socio-technical scenarios. It uses the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI.

The Z-Inspection® process is distributed under the terms and conditions of the Creative Commons (Attribution-NonCommercial-ShareAlike CC BY-NC-SA) license

and it is published in IEEE Transactions on Technology and Society.

Z-Inspection® is listed in the new OECD  Catalogue of AI Tools & Metrics https://oecd.ai/en/catalogue/tools/z-inspection

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