My Ph.D aims to explore the under-examined phenomenon of wartime destruction of place, which remains a critical yet often overlooked aspect of armed conflict. While damage to built environments is a visible outcome of war, understanding the conditions that elevate the risk of destruction and its heterogeneous patterns across conflict theaters requires more nuanced analysis. This project seeks to bridge the gap in existing research, which has traditionally focused on either local destruction or a simplistic binary understanding of damage, limiting the applicability of findings and the ability to anticipate threats.
My project addresses limitations of current research by moving beyond a simple binary view of destruction and instead using a more detailed approach that measures damage across its various intensities. My approach seeks to make it possible to better understand the variations in destruction intensity and why damage clusters in certain ways.
Through this project, I am developing deep learning models that can analyze and predict the destruction of homes, heritage sites, and civilian infrastructure. These models are designed to accurately report damage and offer predictive insights to help practitioners take protective measures. By overcoming the shortcomings of existing models that struggle to apply findings across different settings, this research aims to provide practical, preventative strategies for reducing destruction.
Lastly, my project seeks to create a common ontology for studying wartime destruction, bringing together concepts like urbicide, domicide, and warchitecture. By promoting collaboration among scholars and practitioners, the research hopes to improve efforts to protect built environments. It also emphasizes the connection between attacks on structures and violence against people, highlighting how targeting buildings can be a way to erase a community’s identity and presence.
