As a computer scientist and statistician, I use computation and data as a lens to explore science and intelligence. To make progress, I examines this with the point of view provided by the twin windows of modern nonparametric method and probabilistic graphical model. My specific research focuses on nonparametric structure learning and representation learning. Success on this research has the potential to revolutionarize the foundation of the second generation of artificial intelligence (i.e., statistical machine learning) and push the frontier of the third generation of artificial intelligence (i.e., deep learning). My applied research interest is to develop a unified set of computational, statistical, and software tools to extract and interpret significant information from the data collected from a variety of scientific areas.