The ACM awards, which are awarded by Chinese academic institutions to encourage the dedicated research and academic achievements of young researchers, are extremely competitive and are only given to the very best doctoral dissertation in the field of computer science and engineering.

HONOUR AND MOTIVATION

During her Ph.D. study, Yan Zhao has published 12 peer-reviewed papers, including eight papers published in the most prestigious outlets in her research fields as a first author or a co-first author.

According to the award committee, Yan Zhao received the award because her doctoral dissertation addressed efficiency and effectiveness issues in task assignment in spatial crowdsourcing, which has promoted the development of spatial crowdsourcing.

- It is a great honour for me to receive this award, and I am confident that it will further my career as a researcher. It also motivates me to continue working within the field of spatial crowdsourcing, says Yan Zhao.

SPATIAL CROWDSOURCING

Spatial crowdsourcing is basically about organizing a crowd of people to complete tasks by physically moving to a specific location. Food delivery services, Uber, etc. are concrete examples.

There are quite a number of research areas involved in spatial crowdsourcing, but the core area – and the one that Yan Zhao focuses on – is task assignment. For task assignment, a spatial crowdsourcing server assigns the suitable tasks to assignees (a.k.a. workers) to guarantee that these tasks can be completed without violating the spatio-temporal constraints of tasks and workers. There may be a number of objectives like optimizing route planning in order for a worker to make as many deliveries as possible between the starting point and the destination, maximizing the total number of tasks assigned and maximizing the overall profitability of a specific service.    

In her thesis, Yan Zhao proposes an exact and efficient task assignment algorithm by utilizing the so-called tree-decomposition technique. Each worker shares common tasks with other workers referred to as relationship worker dependencies, and the tree-decomposition technique allows for the dependencies between workers to be isolated. Then the subsets of isolated workers are organized into a balanced tree such that the sibling nodes are independent from each other. The tree is then traversed in a depth-first manner to find the optimal assignment.

Other elements in her thesis include effective task assignment based on the temporal preferences of the workers, a study of Predictive Task Assignment (PTA), which aims to maximize the number of assigned tasks by taking into account both current and future workers and tasks that enter the system dynamically with location unknown in advance. In addition, she proposes a novel spatial crowdsourcing problem, called Coalition-based Task Assignment (CTA), where the spatial tasks may require more than one worker (forming a coalition) to complete the task in order to maximize the overall rewards of workers.

FURTHER INFO

• ACM (Association for Computing Machinery)
• SIGSPATIAL: Special Interest Group on Spatial Information

CONTACT

Assistant Professor Yan Zhao
Department of Computer Science, Aalborg University 
Mail: yanz@cs.aau.dk