Konstantia Zarkogianni
Konstantia Zarkogianni received the Diploma in Electrical Engineering and Computer Engineering (2003) from the Aristotle University of Thessaloniki, the Master's Degree in Electronic Engineering and Computer Engineering (2005) from the Technical University of Crete and the Ph.D. (2011) from the National Technical University of Athens (NTUA). In October 2017, she was appointed to the position of EDIP at the School of Electrical and Computer Engineering, NTUA. In June 2023, she was elected to the position of associate professor at Maastricht University with the subject "Anthropocentric Artificial Intelligence". Her research interests include intelligent user interfaces, human-computer communication, intelligent decision support systems, control systems, modeling of physiological systems. she is the author or co-author of 18 publications in prestigious international scientific journals, a chapter in a book, and more than 30 proceedings in national and international conferences. she has participated as a principal researcher in national (smarty4covid, ENDORSE) and international research projects (FP7 -MOSAIC, Horizon Europe - VoxReality). she has been an invited editor in the special issue "Emerging Technologies for the Management of Diabetes Mellitus" (Springer Journal of Medical and Biological Engineering and Computing [MBEC], 2015) and a member of the Editorial Board of the international journal SpringerPlus in the year 2016. He is a reviewer in international scientific journals (IEEE Transactions on Biomedical Engineering, IEEE Journal of Biomedical and Health Informatics, Springer Medical & Biological Engineering & Computing, Elsevier Journal of Biomedical Informatics, and Biobiology and Management JSM). she is a member of the Institute of Electrical and Electronic Engineers (IEEE) and the Technical Chamber of Greece (T.E.E).
Innovative Physiological Signal Recording Analysis Framework For Detecting Suspected CoViD-19 Cases
The subject of this lecture is the presentation of the smarty4covid system (www.smarty4covid.org) funded by the Greek Research and Innovation Foundation and developed by researchers of the National Technical University of Athens (BIOSIM, AILS). It is a system that aims to identify suspected cases of covid-19 from audio recordings of breathing, coughing, and voice. It incorporates advanced artificial intelligence methods to implement a responsible and human-centered approach to infectious disease management. In the context of the lecture, it will be presented how the basic principles of artificial intelligence are being built for the development of smarty4covid as a decision support system both at the clinical level and at the level of devising strategies to contain the pandemic. In addition, the importance of investigating biases in the data as it affects the performance of AI-based models will be highlighted.
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