lias Gkotsikas is a member of the Laboratory Teaching Staff (ETEP) at the Schools of Philology and History & Archaeology of Aristotle University of Thessaloniki (AUTH), Greece. He is also a PhD candidate in the Department of Electrical and Computer Engineering at AUTH, conducting research on the application of Machine Learning to Ancient Greek Epigraphy, with a focus on the quantitative modelling of chronological uncertainty in archaic inscriptions.

He holds a degree in Informatics and Communications and a degree from the School of Electronic and Electrical Engineering of the University of Leeds. He has worked since 2007 in both the private and public sectors as an IT specialist, with particular expertise in computer networks.

Since 2019, he has been a research associate at the Laboratory of Epigraphy and Papyrology of the Department of Philology at AUTH and a member of the DIGIA (Digitizing Greek Inscriptions & Alphabets) research team. His work focuses on the creation of datasets of archaic alphabets for use in Artificial Intelligence models, as well as on the 3D digitization and digital documentation of inscriptions and archaeological artifacts.

His research interests include Artificial Intelligence, scientific photography and image processing, photogrammetry, laser scanning, LiDAR, Reflectance Transformation Imaging (RTI), Geographic Information Systems (GIS), and digital methods for extracting information from archaeological artefacts.