Spatial-Temporal Crowdsourcing

As a part of the CSE department at HKUST, the STC (spatial-temporal crowdsourcing) group conducts research related to spatial-temporal information and human-powered machine learning, from algorithm design to application development. Prof. Lei Chen's research is motivated by new technologies and applications through mining/learning the spatial-temporal knowledge and exploiting the wisdom of crowds to facilitate people's daily life.

By collaborating with DiDi Chuxing (the biggest online car-hailing company in Mainland China), Prof. Chen's team can utilize the huge amount of data generated by millions of drivers and customers to help the company improve the efficiency of their services and the user experience of both drivers and customers. One such service, ridesharing, which allows drivers to share their empty seats to different groups of customers as long as the detours are acceptable, has a huge potential to alleviate the shortage of vehicles and increase the throughput of the platform. With ridesharing, customers can enjoy relatively cheaper transportation services with guarantees, such as the suitability of fellow travelers and the deadline of delivery. However, to operate a good ridesharing service is challenging. Prof. Chen's team has helped DiDi to design smart vehicle dispatching strategies and dynamic pricing strategies such that the efficiency of the ridesharing service can be improved, and the overall profit of the platform can be increased.

Prof. Chen's team also collaborates with WeChat (at Tencent) in exploiting the wisdom of humans to boost the performance of machine learning models. Recently, although many accurate models have been developed to recognize images, translate languages and compose songs (some models are even more accurate than humans in image recognition), humans are still better than machines in discovering errors, learning new items and feeling emotion. Prof. Chen's team has studied methods to combine the advantages of humans and machines to build better machine learning models benefitting our daily life with human feedback used to iteratively improve the current models.

Read about Prof. Lei Chen's STC projects.