Professor Qiwei Yao

About

Professor Yao's recent research has mainly (but not exclusively) focused on analysing complex and high-dimensional time series in the sense that the observation recorded at each time is more complex than a single scalar or a short vector. Two examples under this framework are spatio-temporal data and dynamic network for which the observation at each time is a space or a network. Demand for analysing those data on an ever-increasing scale is a part of the real challenge underneath the buzzword BigData. The time series thinking and methodology can contribute in facing those challenges. An overarching aim has been to develop new tools which reduce the dimension and/or the complexity of time series by exploring latent low dimensional structures.