Nicoletta Nicolaou received her BSc. (Hons) in Cybernetics & Control Engineering in 2001, and her PhD in Cybernetics (Thesis title: 'Automatic artefact removal from Electroencephalograms') in 2006 from the Department of Cybernetics, University of Reading, UK. She then joined the Holistic Electronics Research Lab and the KIOS Research Centre at the University of Cyprus as a Research Fellow (2007-2014). In 2014-2016 she joined the Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering, Imperial College London as an Experienced Researcher (Marie-Curie Fellow). She is now an Honorary Research Fellow.
Her main research interests are biomedical signal processing , with emphasis on the study of electrical brain activity (EEG) during anesthesia. More specifically, she is investigating how the patterns of brain connectivity (in terms of causality, synchrony, etc) are affected by anesthetic administration, in order to identify mechanisms of anesthetic-induced unconsciousness for predicting / preventing awareness during surgery. Her general research interests include the study of EEG activity for various applications (e.g. brain-computer interfaces), mental states (e.g. sleep), and disorders (e.g. epilepsy).
Nicoletta has served as a Technical Committee member for a number of conferences and is a regular reviewer for a number of international journals and conferences. Throughout her research career she has received a number of awards, including first prize at the international data analysis competition of MLSP 2005 and the Best Paper Award at BIODEVICES 2008.
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et al., 2022, Premature mortality attributable to COVID-19: potential years of life lost in 17 countries around the world, January-August 2020, Bmc Public Health, Vol:22
et al., 2021, Excess all-cause mortality and COVID-19-related mortality: a temporal analysis in 22 countries, from January until August 2020, International Journal of Epidemiology, Vol:51, ISSN:0300-5771, Pages:35-53
Wu S-J, Nicolaou N, Bogdan M, 2020, Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis, Entropy, Vol:22
et al., 2020, Neurophysiological and Genetic Findings in Patients With Juvenile Myoclonic Epilepsy, Frontiers in Integrative Neuroscience, Vol:14, ISSN:1662-5145