The foci of Dr. Xu’s research include mobile sensing, machine learning, urban computing, and smart infrastructure systems. She develops and deploys crowdsensing systems, machine learning algorithms, and incentive mechanisms to help understand urban dynamics and enable a self-adaptive smart city. She is particularly interested in (1) developing tools to improve efficiency and fairness of urban crowdsensing networks; (2) developing collaborative and physics-informed machine learning algorithms for urban computing; (3) designing incentive mechanisms for efficient and resilient urban infrastructure systems. Target applications include spatio-temporal urban sensing and data mining (air pollution, traffic, noise), large-scale infrastructure monitoring (buildings, bridges, and railway tracks).