Dr Zhou received his bachelor's degree in physics at Nankai University, China. He then went on to obtain both his MPhil and PhD degree at the same university. Dr Zhou had been a research scientist at the University of Potsdam, Germany from 2000 to 2007. He joined the Department of Physics at Hong Kong Baptist University as an assistant professor in late 2007.

The main research in Dr Zhou's lab involves analysis and modeling of complex brain interaction networks in cognitive processes. Brain is one of the most complex systems in nature. It is composed of billions of neurons through a hierarchy of complex network connectivity, from local circuits and mini-columuns to macro columns, functional areas and functional subsystems (visual, auditory, etc.). The experimentally observed activity, e.g. by electroencephalograph (EEG), or functional magnetic resonance imaging (fMRI), is characterized by oscillations and synchronization over a wide range of spatial and temporal scales, even when the brain is at the resting state or perform tasks. How to analyze the relationship between the complex activity and various functions of the brain is a long-term challenging problem. The approaches taken rely on hypotheses and assumptions about how the brain works. Classical theories viewed the brain as a passive, stimulus-driven device, and the spontaneous activity is considered as background noise independent of the stimulus-induced activation. Another hypothesis is that the rhythmic oscillations are important for function. In the last decade, a new hypothesis that synchronization is crucial for integration in brain function has created shift of research in neuroscience to emphasize functional interaction of different brain regions. Nowadays, the complex network hypothesis has extended the picture of synchronization between a few pairs of areas to the whole brain network. Dr Zhou collaborates closely with both anatomical and cognitive neuroscientists to apply our expertise on dynamics of large-scale complex networks to investigate the structure-dynamics-function relationships in the brain. By studying models of neural networks with features of realistic brain cortical network connectivity, the hope is to obtain understanding of the structure-dynamics relationship. The understanding from such dynamical complex neural networks will allow further development of new approaches for analysis of functional data from the perspective of interacting networks, in order to reveal the interplay between spontaneous and stimulus-induced activity in cognitive processes.