Dr. Michael M. Zavlanos' main research interests include a range of topics in the emerging discipline of network science, which explores links among physical and engineered networks in search of common principles that determine network behavior. His focus is on robotic and sensor networks, with applications in shape formation, flocking, communication maintenance and intruder detection. This work also has applications in understanding biological and social networks, whose structure and operations respectively determine the way in which many diseases are formed and information is spread. He is particularly interested in hybrid solution techniques, on the interface of control theory with the discrete science of networks and graphs.

Dr. Zavlanos is the recipient of the prestigious National Science Foundation CAREER Award for early faculty development. The goal of Dr. Zavlanos' NSF-funded research is to develop formal methods for networks of mobile robots that integrate control in the communication (cyber) and physical (robot) domains. This research will offer a more realistic look at networked robot systems as it jointly addresses important control and networking objectives, such as environmental interference, power management and robot dynamics, all of which so far have only been investigated individually. The algorithms that Dr. Zavlanos and his collaborators develop stand to revolutionize the way we understand and utilize robot communication networks.

The Innovation University ^TM