Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face, e.g. air pollution, increased energy consumption and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create win-win-win solutions that improve urban environment, human life quality, and city operation systems. This talk will present our recent research into urban computing, introducing the applications and technologies for integrating and deep mining heterogeneous data. Examples include large-scale dynamic ridesharing, identifying different functional regions (e.g., residential and commercial areas) in urban spaces, crowd sending city-wide gas consumption, and fine-grained air quality inference throughout a city. These examples have been published in top-tier conferences and journals recently, such as KDD, UbiComp, ICDE, received 4 best paper awards.