The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …

Dynamic Graph Neural Networks (DGNNs) have become one of the most promising
methods for traffic speed forecasting. However, when adapting DGNNs for traffic speed …

Human mobility prediction is a core functionality in many location-based services and
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …

Point-of-interest (POI) recommendation is essential to a variety of services for both users and
business. An extensive number of models have been developed to improve the …

Predicting the density and flow of the crowd or traffic at a citywide level becomes possible by
using the big data and cutting-edge AI technologies. It has been a very significant research …

Human daily activities, such as working, eating out, and traveling, play an essential role in
contact tracing and modeling the diffusion patterns of the COVID-19 pandemic. However …

The vast amounts of mobile communication data collected by mobile operators can provide
important insights regarding epidemic transmission or traffic patterns. By analyzing historical …

Understanding in-network information diffusion is a fundamental problem in many
applications and one of the primary challenges is to predict the information cascade size …

Human mobility prediction is of great importance for various applications such as smart
transportation and personalized recommender systems. Although many traditional pattern …