Christos Stergiadis

Ι am a physicist, with an MSc in Cognitive Neuropsychology, and currently a PhD candidate in Electronic Engineering at the University of York. I am working in the field of computational neurosciences, with my primary research interests focused on epilepsy and epilepsy surgery. I am the main research technician in the Neuroscience Lab of the University of York Europe Campus, where I coordinate and conduct electroencephalography (EEG) experiments and neurofeedback/biofeedback sessions. I am also teaching applied neuroscience, neuroanatomy and neuroimaging at the Psychology Department of the University of York Europe Campus in Thessaloniki and the National Bulgarian University in Sofia. In addition, I work as a research associate at the South East European Research Center (SEERC), where I am currently involved in EU funded HORIZON projects.

The main arm of my research program investigates different brain pathologies with specific focus in epilepsy, and more specifically drug-resistant epilepsy, a condition where patients cannot control epileptic seizures with pharmacological treatment. I am particularly interested in the localization of the epileptogenic focus in the brains of patients with this condition, using advanced mathematical concepts, such as functional connectivity, graph theory and machine learning models. I have also been interested and published works on EEG signal possessing optimization and EEG-based cyber security systems.

ORCID profile: Research, scholarship, and innovation activities

1. Hamza Massar, Christos Stergiadis, Benayad Nsiri, Belhoussine Drissi Taoufiq, and Manousos
Klados. (2024). "EMD-BSS: A hybrid methodology combining Empirical Mode Decomposition and Blind Source Separation to eliminate the ocular artifacts from EEG recordings".
Biomedical Signal Processing and Control, Volume 95, Part A, 2024, 106475. DOI: https://
doi.org/10.1016/j.bspc.2024.106475

2. Tron Baraku, Christos Stergiadis, Simos Veloudis, and Manousos A. Klados. (2024).
"Personalized User Authentication System Using Wireless EEG Headset and Machine
Learning". Brain Organoid and Systems Neuroscience Journal, Volume 2, 17 – 22. DOI: 10.1016/
j.bosn.2024.03.003

3. Christos Stergiadis, Dimitrios Kazis, and Manousos A. Klados. (2024). "Epileptic tissue
localization using graph-based networks in the high frequency oscillation range of
intracranial electroencephalography". Seizure – European Journal of Epilepsy, Volume 117, 28-35. DOI: 10.1016/j.seizure.2024.01.015

4. Christos Stergiadis, David. M. Halliday, Dimitrios Kazis, and Manousos A. Klados. (2023).
"Functional connectivity of interictal iEEG and the connectivity of high-frequency
components in epilepsy". Brain Organoid and Systems Neuroscience Journal, Volume 1, 3 – 12. DOI:10.1016/j.bosn.2023.11.001

5. Christos Stergiadis, Vasiliki-Despoina Kostaridou, Simos Veloudis, Dimitrios Kazis, and
Manousos A. Klados. (2022). "A Personalized User Authentication System Based on EEG
Signals". Sensors 22, no. 18: 6929. DOI: https://doi.org/10.3390/ s22186929

6. Christos Stergiadis, Vasiliki-Despoina Kostaridou, and Manousos A. Klados. (2022). "Which BSS method separates better the EEG Signals? A comparison of five different algorithms". Biomedical Signal Processing and Control. 72. 103292. DOI: 10.1016/j.bspc.2021.103292.