Academic and professional background, key areas of expertise, and research interests

Post-doc Researcher

PhD in Biomedical signal processing (EEG and FMRI analysis with tensor decompositions) in Marie Curie Consortium in NKUA and University of Edinburgh.

Masters in Electrical and Computer Engineering (AUTH) and Biomedical Engineering (KUL).

What is your role within the AI-PROGNOSIS project, and how do your expertise and skills contribute to achieving its objectives?

Co-leading WP3, member of research team of tasks 3-1 and 3-6.

The background in signal processing and previous experience in European projects helps into facilitating this tasks.

Previous experience with wearables mainly in the field of seizure detection.

What future opportunities do you see for your field in similar healthcare projects?

AI in Healthcare is flourishing , I believe in most of the fields in healthcare AI solutions will become part of the everyday clinical routine.

What do you see as the long-term potential of the AI-PROGNOSIS project in advancing AI-driven healthcare solutions?

The long-term potential is to help clinicians and partners to gain confidence and trust to AI-driven solutions. Furthermore, the need of good and big data for such solutions will become evident and will help towards improvement and sharing of datasets.

How do you see digital tools, such as apps, wearables, or other technologies, transforming healthcare in projects like AI-PROGNOSIS? What specific benefits do you anticipate for patients or healthcare providers?

The main benefit is the continuous monitoring of the health of the patients, a doctor that can monitor you 24/24. The increased amount of patients (aging population) and finite resources in healthcare domain dictates the need of solutions such as those designed within AI-PROGNOSIS.