Registration Link: https://meetings.vtools.ieee.org/m/38534
In this talk, I will present a high-level overview of my research in the past decade on collective behavior in networked, social, and engineering systems. These collective phenomena include social aggregation in animals such as schooling, herding, and flocking, and more broadly emergence of consensus, swarming, and synchronization in complex network of interacting dynamic systems. A common underlying theme in this line of study is to understand how a desired global behavior such as consensus, synchronization or a particular formation can emerge from purely local interactions. The evolution of these ideas into social systems has led to a new theory of collective decision making among strategic agents. Examples include participation decisions in uprisings, social cascades and investment decisions in infrastructure. I will investigate distributed strategies for information aggregation, social learning and detection problems in networked systems where heterogeneous agents with different observations (with varying quality and precision) coordinate to learn a true state (e.g., finding aggregate statistics or detecting faults and failure modes in spatially distributed wireless sensor networks, or deciding suitability of a political candidate, quality of a product and forming opinions on social issues of the day in social networks) using a stream of private observations and interaction with neighboring agents. I will end the talk with a description of contagion phenomena in networked systems and a new vision for graduate education at the interface of information and decision systems, data science and social sciences.