Short Biography

Vivian is a PhD candidate in machine learning for written material culture. She holds postgraduate degrees from the Department of Informatics at the Athens University of Economics and Business and the Department of Philology at the National and Kapodistrian University of Athens. She has received specialized training in digital approaches to papyrology, paleography, epigraphy, and sigillography from leading academic institutions, including Heidelberg, London, Oxford, Cologne, and Dartmouth. She has collaborated on Digital Paleography and Papyrology research projects at the Centre for Digital and Public Humanities of Ca’ Foscari University of Venice, Italy, and at the Department of Linguistics of Ghent University, Belgium. 

Research Interests

Vivian’s research focuses on the application of data science and machine learning techniques to the analysis of ancient Greek handwritten texts, with a particular focus on Optical Character Recognition (OCR) and the use of Natural Language Processing (NLP) methods for pattern recognition. She integrates advanced digital methods into the fields of Papyrology and Paleography, with the aim to broaden our understanding of ancient cultures and cultural heritage material, address long-standing challenges in historical research, and unlock answers previously inaccessible through traditional methods.

PhD research on topic "From Stone to Paper and from Paper to Pixel: Deep learning-based Inpainting for Fragmentary Epigraphic Texts"
Abstract: This study addresses the problem of restoring fragmentary ancient inscriptions, where material deterioration often renders the text incomplete. The aim is to investigate the application of models, and in particular inpainting methods, for the digital reconstruction of lost parts. The proposed methodology seeks to enhance the existing tools of philologists by offering a computational approach to the study and interpretation of texts.