I’m a visiting postdoctoral research fellow at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (2024-). I’m 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 interests include urban mobility, social segregation, and sustainable transport.
In my master thesis at Tsinghua University, China (2013-2016), I studied driver distractions during driving on road safety and how to detect them in practice by combining gaze and behavioural data.
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
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.
This study systematically explores the feasibility of using geolocations of Twitter data for travel demand estimation by examining the effects of data sparsity, spatial scale, sampling methods, and sample size.
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.