My research interest has revolved around complex network, graph signal processing and brain science. Recently, the development of neuroimaging techniques has provided a way to understand the brain network on a large scale. Studies have shown that the interaction relationships in the brain, from neuronal information flow to whole-brain functional networks, are the basis of its functionality. Thus, formulating the brain as a complex network and decoding its signals from this perspective may further deepen our understanding of human cognition process and inspire new machine learning models. The goal of my research is to study how the brain works as a complex network to process multi-modal information from multiple sensors, and reverse-engineer their functionality as complex network modeling and analysis methodologies that come close to human intelligence.