Some of the most fascinating problems in applied mathematics today concern the structure and dynamics of systems composed of many interacting parts. Think of the thousands of power plants in the electrical grid or the companies in the global economy; the billions of people on Facebook; or the tens of billions of neurons in the human brain. In each of these complex systems, the interactions between individual parts define a network. Faculty and students at CAM are using the tools of graph theory, statistical physics, machine learning, probability theory, and dynamical systems to investigate the complex architecture and collective behavior of the diverse networked systems in the world around us.