Gyorgy Korniss, Professor, Department of Physics and The Social and Cognitive Networks Academic Research Center
Rensselaer Polytechnic Institute
Coordinating, distributing, and balancing resources in networks is a complex task and it is very sensitive to time delays. To understand and manage the collective response in these coupled interacting systems, one must understand the interplay of stochastic effects, network connections, and time delays. In synchronization and coordination problems in coupled interacting systems individual units attempt to adjust their local state variables (e.g., pace, orientation, load) in a decentralized fashion. They interact or communicate only with their local neighbors in the network, often with explicit or implicit intention to improve global performance. Applications of the corresponding models range from physics, biology, computer science to control theory.
I will discuss the effects of nonzero time delays in stochastic synchronization problems with linear couplings in an arbitrary network. Further, by constructing the scaling theory of the underlying fluctuations, we establish the absolute limit of synchronization efficiency in a noisy environment with uniform time delays, i.e., the minimum attainable value of the width of the synchronization landscape. These results have also strong implications for optimization and trade-offs in network synchronization with delays.
Prof. Gyorgy Korniss received his MS in Physics at Eotvos University, Budapest in 1993 and his Ph.D. in Physics at Virginia Tech in 1997. His research background is statistical physics and interacting and agent-based systems. He was a postodoc at the Supercomputer Computations Research Institute, Florida State University between 1997-2000. He has been in the Department Physics at RPI since 2000, where he has been an Associate Professor since 2006. His current research focuses on opinion dynamics and influencing in social networks, transport and flow in complex networks, and synchronization and coordination in coupled stochastic systems. More information and recent publications can be found at: http://www.rpi.edu/~korniss/