For the first time ever, we have more people living in urban areas than rural areas. Based on this inevitable urbanization, the research in our group aims to address sustainability challenges related to urban mobility (e.g., energy consumption and traffic congestion) by data-driven applications with a Cyber-Physical-Systems approach (CPS, also known as a broader term for Internet of Things). Under the context of the smart cities initiative proposed by the White House, in this talk, I will focus on data-driven modeling and applications for large-scale cross-domain urban systems, e.g., taxi, bus, subway, private vehicle, truck, cellphone, and smart payment systems. I will first show how cross-domain data from these systems can be collaboratively utilized to capture urban mobility in real time by a new technique called multi-view bounding, which addresses overfitting issues of existing mobility models driven by single-domain data. Then I will show how the captured real-time mobility can be used to design a practical service, i.e., mobility-driven ridesharing, to provide positive feedback to urban systems themselves, e.g., reducing energy consumption and traffic congestion. Finally, I will present some research challenges related to future urban CPS in the context of the smart cities research.