Our research explores research related to spatial-temporal information and general crowdsourcing, from algorithms design to applications development. Our research has three main themes. The task assignment theme addresses challenges in batch-based matching of workers and tasks in various demond-supply systems, such as spatial crowdsourcing systems, public resource allocation systems and so on. The general crowdsourcing theme focuses on latency control, copying detecton and training data preparation in general crowdsourcing systems. The smart transportation theme aims at taking advantage of huge data collected by morden online dial-a-ride systems and the novel minng/learning methods to discover and predict the trends of travelers such that the efficiency of the public transportation and user experience can be improved.