I am a member of "Complex Network Research Group (CNeRG)". For the past four years broad area of research in CNeRG has been Complex network theory and its applications in various technological, social and biological systems. Details about the current research in our group can be found in group's website.
My topics of research span mainly in two areas of modeling bipartite network growth and information spreading in delay-tolerant networks (DTN). Currently I am working on routing algorithm in DTN.

Recently, much attention has been paid in analyzing and modeling bipartite network (BNW) as scientists are discovering its presence in many fields like information science, biology, social science, economics. My iterest is particularly about growth of a special type of BNW where the number of nodes in one set is almost fixed and other set grows with time. This type of systems can be termed as an Alphabetic Bipartite Network (α-BiN) where there are two kinds of nodes representing the elementary units and their combinations respectively. There is an edge between a node corresponding to an elementary unit u and a node corresponding to a particular combination v if u is present in v. The partition consisting of the nodes representing elementary units is fixed, while the other partition is allowed to grow unboundedly. There are many practical examples of this as Codon-Genome network where the set of codons is fixed, Protein-Protein Complex Network where the number of proteins is fixed, Phoneme-Language Network where set of phonemes is fixed, Station-Train network where the number of station is almost fixed. The objective of my research is to investigate and model the growth of these real world α-BiNs. We have modeled the growth using a mixture of random and preferential attachment process. Our current focus of research regarding this has three directions as

• Developing linear and non-linear mathematical models for α-BiN growth
• Detail investigation and consequently characterizing the growth processes
• Validating the developed models by applying them in real world systems

The wide-scale adoption of wireless devices has enabled a new platform for peer-to-peer opportunistic networking. One potential framework, termed delay tolerant networks (DTNs),is receiving increasing research attention. Delay tolerant networks comprise of mobile wireless devices that are not necessarily connected to each other (e.g., moving vehicles in a road). Messages progress from one node to another by opportunistically exploiting wireless connectivity as well as physical node mobility. Intermediate nodes receive batches of packets, store and carry them in their local memory, and forward them to other nodes until some (unicast/multicast/broadcast) conditions are satisfied. Examples of DTN application include networking using buses having predictable routes, interplanetary networking, interfacing with sensor networks, and using mobile nodes to bridge data between remote village networks and the Internet.
I am interested in broadcasting and routing in DTN inspired by epidemic dynamics using both directional antenna and omni-directional antenna. We have investigated SIRS epidemic model to understand the power efficient broadcasting in DTN. Currently we are working on epidemic routing in DTN with nodes having directional antenna. However, main directions of our research in DTN are as follows.

• Modeling information spreading in DTN employing epidemic dynamics.
• Investigaing the effects of directional antenna in broadcasting and routing in DTN using epidemic models.
• Developing efficient algorithm for epidemic routing using directional antenna.