2 PhD Students in networked learning and control cyber-physical-human systems

The Division of Decision and Control Systems is looking for up to two doctoral students with a strong background in control systems, mathematics, and modeling, and with a keen interest in network theory. The project lies in the intersection of network dynamics, learning, and control, and aims at addressing theoretical challenges within networked cyber-physical-human systems (cphs). These systems are characterized by humans in interconnected communities making decisions while interacting with a cyber-physical or control system, and applications include complex socio-technical systems such as smart cities. The project will include learning complex dynamics from big data and rigorous characterization and (data-based) modeling of decision-making dynamics over networked cphs, in addition to the development of novel tools to design and assess the impact of control strategies or interventions.