Ilya Ilyankou
The Alan Turing Institute, University College London, University of Leeds, Trinity College
About
I am a PhD researcher at UCL SpaceTimeLab studying how people communicate about place: what they ask, how they ask it, and what this reveals about human spatial information behaviour at scale. I work at the intersection of GeoAI, NLP, and HCI, using query logs and conversational AI datasets to characterise spatial information needs across interfaces. I’m particularly interested in subjective spatial questions – those that go beyond what deterministic GIS can answer, and expose the gap between place as data and place as lived experience. My research is funded by UKRI/EPSRC and the Ordnance Survey.
I previously worked as a data engineering and a full stack developer, and I co-authored Hands-On Data Visualization (O'Reilly). I am a postgraduate TA at UCL and Birkbeck, supporting modules in geospatial programming, spatial analysis, and data analytics.
I am also a co-founder and CTO of Safest Way, a Geovation-backed startup building safety-first pedestrian navigation.
Employment
-
The Alan Turing Institute Sustainability Mission Intern2025 - 2025
Education
-
University College London PhD student2023 - 2027
-
University of Leeds MSc in Geographical Information Science2019 - 2022
-
Trinity College Bachelor of Science2014 - 2018
Projects & Funding
Projects & funding information is unavailable.
Publications (13)
- CLIP the landscape: Automated tagging of crowdsourced landscape images Save
- Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places Save
- From Geospatial Data to Narrative: A GIS-LLM Pipeline for Generating Personalised Outdoor Route Descriptions Save
- Can CLIP See Safe Streets? Comparing Human and VLM Perceptions of Walkability and Safety Save
- Reliable imputation of incomplete crash data for predicting driver injury severity Save
- CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl Save
- CycleTrajectory: An End-to-End Pipeline for Enriching and Analyzing GPS Trajectories to Understand Cycling Behavior and Environment Save
- Quantifying Geospatial in the Common Crawl Corpus Save
- Multi-Criteria Framework for Routing on Access Land: A Case Study on Dartmoor National Park Save
- Supermarket Store Locations as a Proxy for Neighbourhood Health, Wellbeing, and Wealth Save