Daniel Case is a Ph.D. candidate and Presidential Fellow in the Department of Physics & Astronomy at Northwestern University. His broad areas of research are networks and complex systems. Complex systems are systems composed of numerous interacting components that exhibit behavior which cannot be inferred by only knowing the properties of the individual parts. Examples of such systems include electrical power grids, social groups, financial markets, and materials. It is often natural to view these systems as networks, and an extremely active area of research is the construction of network models of these complicated systems that capture some of their observed behavior. Daniel’s thesis research focuses more so on the inverse problem: constructing a network that exhibits a desired behavior. His work is theoretical and computational and fuses concepts from network science, fluid mechanics, and nonlinear dynamics. Daniel’s research projects include: microfluidics, particle advection in fluid flows, control of coupled driven mechanical systems, and deep learning as applied to problems in physics. Daniel received B.S.’s in physics, mathematics, and economics from Louisiana State University prior to attending Northwestern to join Prof. Adilson Motter’s research group.