Forschungsinteresse

Visiting Researcher at  GraC-lab for the project EU project ‘The Delta of language’.

Alexandra Korda’s research interests lie primarily in the application of computer science in health, ranging from pre-processing and feature extraction algorithms applied in medical data to the defensive part of Artificial Intelligence. In particular, she is interested in developing new methods for feature extraction and artificial intelligence applicable not only to medical signals and images, but also to psychological batteries, pharmacological studies and medical reports.

Keywords: explainable AI, NLP, brain MRI, treatment response

Education

2002-2008 Diploma & Master, Applied Mathematics and Physical Sciences, ECE, National Technical University of Athens (Greece)

2008-2010 Master, Biomedical Engineering, ECE, National Technical University of Athens and University of Patras (Greece)

2011-2017  PhD, Oculomotor signal processing using AI and mathematical modelling, ECE, National Technical University of Athens (Greece)

Professional Experience

2009-2015 Tutor of Mathematics in private high school, Athens (Greece)

2013-2015 External Associate at MED.I.S.P. Lab, Department of Biomedical Engineering, Technological University of Athens (ARCHIMEDES; Greece)

2015-2017 Data Scientist at Ernst&Young, Athens (Greece)

2017-2018 Consultant at IRI Worldwide, Athens (Greece)

2017-2018 Postdoctoral researcher, Oculomotor signal processing using AI and mathematical modelling, ECE, National Technical University of Athens (Greece)

2018-2020 Postdoctoral Researcher, Brain sMRI for identification of psychosis using explainable AI, LVR-Clinic, Düsseldorf (Germany)

2020-present Postdoctoral Researcher, Multimodal analysis for identification of psychosis using explainable AI, University of Lübeck & University Hospital Schleswig-Holstein (ZiP) (Germany)

Best paper awards

Korda, A.I., Giannakakis, G., Ventouras, E., Asvestas, P.A., Smyrnis, N., Marias, K., Matsopoulos, G.K. Recognition of Blinks Activity Patterns during Stress Conditions Using CNN and Markovian Analysis. Signals 2021, 2, 55–71. https://doi.org/10.3390/signals2010006

HEALTHINF 2025, for the paper entitled “Bag-Level Multiple Instance Learning for Acute Stress Detection from Video Data”. https://www.scitepress.org/Papers/2025/133649/133649.pdf

Other awards and achievements

• Excellence Award 2022 ECNP (European College of Neuropsycopharmacology).
• Early Career Award 2023 SIRS (Schizophrenia International Research Society).
• German Academic Exchange Service (DAAD) Congress travel fund 2023 for the Early Intervention in Mental Health (IEPA’14) conference in Lausanne, July 2023.
• Symposium proposal accepted for presentation at ECNP 2024: “Towards diagnostic digital health technologies in psychiatry”
• 1st stage success on ERC StG 2024 and 2025
• Grant awarded by the University Hospital Schleswig-Holstein (UKSH) Foundation for the project entitled “Intelligent health solutions for digitally informed psychiatry” (10,000 € for technical equipment)