Yue’s research aims to develop a multi-purpose graph DL-CV model to forecast traffic flow distributions via various urban parameters and existing traffic data and generate urban scenes based on the traffic.

By providing the traffic flow prediction and urban scene images, this research enables city planners to accurately evaluate or guide their planning prior to the deployment from the respect of traffic conditions. In addition, the proposed model combines multi-layers (built environment, natural environment, human interaction, etc.) of the city to tackle the issue in understanding interactions between people and traffic conditions.

Research Interests:

• Urban Transport
• Spatio-temporal analysis
• Deep learning
• Computer vision

PhD student researcher

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