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The Invisible City: Not All Streets Are Seen Equally
Investigates spatial bias and systematic omission in urban street view datasets and digital representations.
Mapping the Semantics of the Street: A VLM-Driven Geospatial Analysis in Fatih, Istanbul
Deploys Vision-Language Models on street-level imagery across Fatih, Istanbul, extracting multi-attribute urban semantics and mapping vibrancy.
DOI
A Graph-Based Community Detection Approach for Identifying the Semantic Neighbourhoods within London's Airbnb Properties
Awarded the Best Short Paper Award at the 29th AGILE Conference. Delineates semantic urban neighbourhoods in London using graph community detection on property listings.
DOI
Emergent Spatio-Semantic Structure in Large Language Model Embedding Spaces
Demonstrates emergent geospatial and spatial-semantic structure within LLM embedding spaces without explicit coordinate training.
DOI
Digitalising Probation with Geospatial AI: Street-Level Human Perception in İstanbul’s Fatih District
Applies Geospatial AI and street-level perception analytics to modernize probation monitoring and spatial risk assessment in Istanbul.
From Video to Recipe: Leveraging Vision Language Models for Culinary Analysis
Investigates open-weight Vision-Language Models for automated recipe extraction, ingredient identification, and culinary video analysis.
Elektronik İzleme Teknolojisi ve Türkiye'de Uygulanması
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