Spatio-Temporal Data Mining is an emerging research area under the concept of smart city and smart nation. It covers a wide range of research problems, including geospatial topic mining, trajectory mining, spatial region analysis, user mobility modeling and location-based recommendations. We exploit machine learning approaches to discovering spatio-temporal patterns underlying the data, and solve novel data mining problems in real-world.
The machine learning group at the University of Auckland is one of the world-leading ML research groups. We publish papers on top venues including (SIGKDD, ICDM, AAAI, ICDE, etc.). The candidates will have the chance to work with world-class researchers and international industrial partners. Candidates with excellent academic records or publication records will have the chance to be fully funded by scholarships.
Duration and Type
- 3 Years
- PhD Programme
- Good academic background
- Knowledge of basic maths, CS, and machine learning.
- Research experience in data mining, recommender system or probabilistic models is preferred.
- Publication in prestigious venues is preferred.
Supervisor and contact
- Kaiqi Zhao
- Send CV and transcript by email to Kaiqi Zhao