UBEL Logo
Linkedin

Michal Iliev

Department of Geography, UCL
UBEL Pathway: Quantitative Social Science
Supervisor: James Cheshire and Stephen Law
Contact details: michal.iliev@ucl.ac.uk
About Me

I am a PhD student in the UCL Department of Geography and Geographic Data Service (GeoDS).

Broadly, my research focuses on the geospatial analysis of mobility, accessibility, and spatial justice in cities—particularly in London and my home city of Warsaw. Data visualisation and mapping are key components of my work, and I had the opportunity to further develop these skills while working in data journalism after completing my BA.

My Research

Approximately a quarter of London’s workforce—roughly 1.32 million people—falls under the definition of a nighttime worker: an individual who typically works between 6 pm and 6 am. While the Greater London Authority (GLA) has increasingly prioritised nighttime strategies—such as the 24-Hour Vision introduced in 2017—there remains limited geospatial research on the distribution of night-time workers, their commuting patterns, and their accessibility levels to essential services at night. Existing policies still largely focus on the commercial aspects of the nighttime economy (NTE), often overlooking the needs and challenges faced by the very workers who sustain it. My PhD aims to address this gap by combining novel datasets, including mobile phone location data, with GIS methodologies to produce policy-relevant insights into how London—and its workers—function at night.

Impact of My Research

This project forms part of the ongoing collaboration between UCL and the GLA under the “Data after Dark” initiative, which seeks to generate a more nuanced understanding of nighttime activity in London—particularly among disproportionately precarious night-time workers. My research will provide critical data and evidence while also interrogating the limitations of existing data sources. Among other contributions, it will aim to investigate the spatio-temporal distribution of night workers, analyse their mobility patterns, and identify areas underserved by public transportation and food services at night. As urban analytics remain largely shaped by daytime-oriented frameworks and assumptions, this project will also contribute to the advancement of methodologies better suited to capturing nighttime urban dynamics. Although the study is focused on London, its conceptual and methodological contributions will have broader relevance, supporting the growing yet underdeveloped field of geospatial research on the night in other urban contexts.