A collection of my recent works.
S. Liang, Y. Xu, G. Li, X. Zhang, Q. Li
Travel Behaviour and Society, 2026
To predict local demand, is proximity enough, or do the pathways people travel also matter? Our AI model (GeoTopo-Net) proves that including the layout of urban networks is key. We find that metro lines give a greater accuracy boost than cycling paths, especially in urban centers and near stations.
S. Liang, Q. Li, L. Zhuo, D. Zou, Y. Xu, S. Zhou
International Journal of Digital Earth, 2025
To predict where someone is headed, do we need to know why? This study shows that giving AI the "why" makes its predictions much sharper. We find that using a diverse mix of activities works better than sticking to a few safe, accurate categories, even if the specific guesses are imperfect.
Q. Li, S. Liang, Y. Xu, L. Liu, S. Zhou
Health & Place, 2022
Does your commute hide a pollution risk? We measure it in Guangzhou by linking city-wide travel data with mobile sensors, and uncover three distinct patterns based on how and when people travel.