Dr Zahratu Shabrina (Zara)

My research focuses in the quantitative approach to measure the impact of digital platforms using Spatial Data Science. The video above showcases the evolution of Airbnb overtime in London – which is a prominent example of a digital platform economy.

Brief Bio

I am currently a lecturer in Spatial Data Science at KCL since November 2019. Beforehand, I pursued my doctoral degree from the Centre for Advanced Spatial Analysis, University College London. My doctoral thesis was awarded by ESRI due to its innovative spatial analysis techniques and the quality of the research output.

Prior to my PhD, I had some working experiences in the government and private sectors in The United States, Indonesia and Singapore. It has diversified my perspective regarding spatial analysis both in the Global North and the Global South. I obtained my Master in Urban Planning (MUP) degree from Sol Price School of Public Policy in Los Angeles in 2013, California. My bachelor degree was also in Urban Planning from Institut Teknologi Bandung, Indonesia, awarded back in 2011.

Research Interests

I am interested in research in the theme of Digital Geography, specifically in terms of the intersection between data, technology and the new economic geography which is based on digital platforms. Digital platforms encompass a wide variety of research leveraging the advancement of Information and Communication Technology (ICT) to facilitate economic transactions mainly in cities.

I am also interested in the advancement of the overall quantitative approaches for computational social science and urban analytics.


  • Airbnb, housing and urban tourism
  • The landscape of digital platforms


  • Spatiotemporal modelling: the use of spatial and temporal properties in a big dataset to uncover hidden patterns and inform computational models.
  • Social media analysis: the use of data from social media channels such as Twitter to inform social research using tools such as Natural Language Processing (NLP).
  • Mobility analysis: exploratory and predictive analytics involving analysis of flow data such as those using accessibility and spatial interaction modelling.