• Qualifications: Bachelor degree in Telecommunications Engineering from Xidian University, China, and Master degree in Electronical and Telecommunications Engineering from Xidian Univeristy, China.
  • Scholarship: UNSW-CSC joint scholarship, and the IJCAI 2019 and PAKDD 2019 travel funding.  
  • Supervisors: Dr. Lina Yao and Prof. Salil Kanhere
  • Research fields: Spatial-temporal data mining and artificial intelligence

Why did you choose UNSW Computer Science Engineering to undertake your research project? 

I chose UNSW because of its global reputation, especially in the area of engineering, and the opportunity to undertake my research with top academics such as my supervisors Dr. Lina Yao and Prof. Salil Kanhere. Besides, I also enjoy the amazing weather and scenery in Sydney! 

Can you tell us about your research project?

My current project is “Spatial-Temporal Forecasting in Smarter Cities”. I will develop new artificial intelligence methods to mine the big data generated in our cities and make accurate predictions about the future to facilitate the city management, scheduling and planning.

Why did you choose this particular project? 

I chose this project because fast urbanization has resulted in many “big city diseases”, such as traffic congestion, resource shortages and energy dissipation, which result in significant challenges to our cities’ communities and waste valuable resources. A data-driven method is an easy-deployment and low-cost way to solve or at least ease these problems.

What do you hope to achieve with your research? 

In the current stage of my research, my goal is to develop more accurate spatial-temporal forecasting models which can be applied to smart transportation applications like traffic prediction and traffic scheduling. 

What are your goals after study? 

Once I’ve completed by PhD, I intent to pursue an academic position. I would like my next research project to be on creating an accurate, robust and universal AI-based spatial-temporal data analysis system. This system would be capable of finding valuable patterns automatically, predicting the future state and making intelligent decisions to promote the efficiency of various systems in our cities.

If you are interested in learning more about this research or other projects please contact the School of Computer Science and Engineering.