Discovery and design of complex dynamics and pattern formation 

Complex systems amount to more than the sum of their parts, exhibiting emergent and collective behaviors that defy expectations and resist classification. Nevertheless, over the last several decades, universal mechanisms have been recognized leading to synchronization in coupled oscillators, symmetry-breaking pattern formation, and the development of chaotic dynamics, which promise to shine a light on complex phenomena. More recently, machine-learning methods have also emerged to automate and streamline the discovery of parsimonious and accurate models of real systems. This understanding may enable the design of new technological paradigms for computation, information processing, and self-assembly that leverage complexity, much in the way that biological systems have evolved to do. In this talk, I will discuss some recent efforts to design and manipulate emergent behavior in mechanical systems, networks, and pattern-forming media.