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Georgios Zoumpourlis has a diverse and extensive work experience in the field of machine learning and computer vision. Georgios is currently working as a Machine Learning Engineer at Cogitat since February 2023. Prior to this, they completed their PhD in Machine Learning at Queen Mary University of London from September 2018 to December 2022, where they focused on developing machine learning techniques for Electroencephalography (EEG) analysis. Georgios'sresearch involved motor imagery decoding from EEG data and addressed challenges such as generalization, robustness, and low data availability. Georgios also served as a Teaching Assistant during their time at Queen Mary University of London from October 2018 to December 2019.

Before pursuing their PhD, Georgios worked as a Research Assistant at the Visual Computing Lab of the Information Technologies Institute (ITI)-CERTH in Greece from January 2016 to August 2018. During this time, they participated in various EU projects and conducted research in computer vision and machine learning. Georgios'sresearch focused on ultra-low-power vision algorithms, facial expression recognition, fake image detection, and DNA information extraction.

Overall, Georgios Zoumpourlis has a strong background in machine learning, computer vision, and research experience in academia and industry settings.

Georgios Zoumpourlis completed their education with a Doctor of Philosophy degree in Machine Learning from Queen Mary University of London, where they studied from 2018 to 2022. Prior to that, they obtained a Master of Engineering degree in Electrical and Computer Engineering from Aristotle University of Thessaloniki (AUTH), where they studied from 2008 to 2015.