I’m a visiting postdoctoral research fellow at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (2024-), affiliated with Chalmers University of Technology, Sweden (2021-). I work at the intersection of data science and human mobility. My research vision is the data-driven understanding of human mobility to empower the environmentally and socially sustainable transformation of global cities. The vision highlights using big and continuous data from newly emerged sources, such as mobile phones. My research focuses on understanding urban mobility patterns and social inequality through large-scale geolocation data, spatial analytics, and transport modeling.
I’m an active learner of data techniques especially data visualisation, scalable data science, and spatial analytics.
PhD in Energy and Environment, 2021
Chalmers University of Technology
MEng in Automotive Engineering, 2016
Tsinghua University
BSc in Automotive Engineering, 2013
Tsinghua University
Using 320k Swedish smartphones, we show foreign-born minorities remain segregated outside the home because limited mobility—linked to weaker transit—amplifies same-group preferences, unlike the mixing seen among native-born majorities.
This study presents a literature review of how individual mobility interacts with socio-spatial segregation experiences based on empirical evidence.
This study simulates charging infrastructure needs using a large-scale agent-based simulation of Sweden with detailed individual characteristics, including dwelling types and activity patterns.
This study explores the competition between ride-sourcing and PT through the lens of big data analysis.
A data fusion framework including real-time traffic data, transit data, and travel demand estimated using Twitter data to compare the travel time by car and PT in four cities at high spatial and temporal resolutions.