There is a revolution in the making when it comes to understanding the complex, interconnected world around us. For decades we have been taught to look for the source of all behavior in the properties of the system's constituents. This view is rapidly changing as we come to understand the architecture of complexity, the networks around us. Our research has a simple objective: think networks. It is about how networks emerge, what they look like, and how they evolve; and how networks impact on understanding of complex systems. To understand networks, our research has taken us to rather unexpected areas. We have studied the topology of the www - showing that webpages are on average 19 clicks form each other. We have investigated the complex cellular network inside the cell - looking at both metabolic and genetic networks. We have uncovered the Internet's Achilles' Heel. We have ventured to study how actors are connected in Hollywood. We have investigated the evolution of the collaboration network that connects scientists through joint publications. We have found that statistical physics allows us to capture the topology of these diverse systems within a single framework, understanding complex systems through networks. Our lab has various interests in many complex systems ranging from cell to the Internet.
Nano-scale structures and pattern formation
Atoms deposited on a surface through MBE (Molecular Beam Epitaxy) process diffuse until they meet one another to form dimmers which then grow into stable islands. Computer simulation method and analytic approach with non-linear equations are most common methods to study these motions of atoms on a surface. Especially, Mote Carlo simulation methods are extensively used to study structural properties of semi-conductor surfaces because of its simplicity compared to Molecular Dynamics method. Recently, our lab studies mechanisms of quantum dots and wires formation through sputtering method which has potential applications in optoelectronics. Our lab is also interested in nano-scale self-assembled systems and tries to find out underlying principles. Our research areas also include basic problems in non-equilibrium statistical mechanics, such as phase transition, universality class, fractal surface dynamics and self-organized processes.