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) 2017-2018Consultant 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)
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.
Korda A. I., Andreou C., & Borgwardt, S. (2021). Pattern classification as decision support tool in antipsychotic treatment algorithms. Experimental neurology, 339, 113635. doi: 10.1016/j.expneurol.2021.113635
Korda A. I., Ruef A., Neufang S., Davatzikos C., Borgwardt S., Meisenzahl E. M., & Koutsouleris N. (2021). Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions. Psychiatry research. Neuroimaging, 313, 111303. doi: 10.1016/j.pscychresns.2021.111303
Korda A. I., Asvestas P. A., Matsopoulos G. K., Ventura’s E. M., & Smyrnis N. (2018). Automatic identification of eye movements using the largest lyapunov exponent. Biomedical Signal Processing and Control, 41, 10-20
Penzel N., et al. (2021). Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis. Neuropsychopharmacology, 46(8), 1484–1493. doi: 10.1038/s41386-021-00977-9
Wenzel J., et al. (2021). Cognitive subtypes in recent onset psychosis: distinct neurobiological fingerprints?. Neuropsychopharmacology, 46(8), 1475–1483. doi: 10.1038/s41386-021-00963-1
Best paper award
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.
Grant awarded by the University Hospital Schleswig-Holstein Foundation to Alexandra Korda (PI), Stefan Borgwardt (PI), and Christina Andreou (Group Leader) to investigate Intelligent health solutions for digitally informed psychiatry (10,000 €)