Dr. Faidon Moudopoulos-Athanasiou joined the Landscape Archaeology Research Group of ICAC in January 2023, as a Juan de la Cierva postdoctoral fellow.
He was born in Athens in 1991. He obtained his BA in History and Archaeology from the University of Crete (Rethymno, 2013) and subsequently completed two MAs, one in Aegean Archaeology (University of Sheffield, 2014) and another Heritage Management (University of Kent & AUEB, 2016). In 2021, he received his Ph.D. from the University of Sheffield (dept. of Archaeology). His research focused on the early modern (Ottoman) Zagori, NW Greece, which is also his place of origin. The methodology of his doctoral research combined landscape archaeology (extensive reconnaissance) with archival sources from local (Greek) and imperial (Ottoman) archives, ethnography and ethnoarchaeology.
During the course of his studies, he has received many scholarships and awards. As an undergraduate student he was sponsored by IKY (Greek State Scholarships, 2010-2011) and as an MA student his research was funded by the Piraeus Bank Cultural Foundation (2015-2016). His doctoral research was funded by the White Rose College of the Arts and Humanities (WRoCAH – AHRC) and the A.G. Leventis Foundation.
His research interests include landscape (esp. mountainous) archaeology, post-medieval (Ottoman) archaeology, archaeological theory, the history of archaeology and cultural landscapes. He has worked closely with regional stakeholders in Zagori while public outreach and community engagement are at the core of his practice.
As a postdoctoral fellow of GIAP/ICAC, dr. Moudopoulos-Athanasiou will work in the mountainous area of Zagori in NW Greece. He will investigate the landscape of the region in relation to afforestation. Despite being considered an area of exceptional natural heritage, Zagori’s cultural management has focused on its villages and their architectural elements, overlooking the landscape that sustained them.
Consequently, the project will identify and contextualise the cultural elements hidden underneath the currently afforested landscape. To do so, he will combine traditional archival research and pedestrian survey with an innovative remote sensing workflow joining photogrammetric reconstruction for historical aerial imagery (1945 onwards) and machine-learning probabilistic classification of multitemporal, multisource satellite imagery.