I am a full-time researcher in the field of Computer Science with a bachelors as well as a masters degree in Computer Science. I am also working as a Research Assistant with some teaching duties in Computer Science. I have two publications: one in my masters and the other based on my initial PhD work. My research is not limited only to Computer Science; I have done some research work in management topics such as branding and company acquisition processes. I advise students during the process of their dissertations and have given valuable suggestions on the research directions they need.

Sample: Computer Science
In the emerging class of applications where Grid technology has been applied and found to be an effective tool, essentially include data-intensive applications that involve geographically dispersed data and human work force. These applications include high-energy physics, climate modeling, earthquake engineering, and astronomy. The common feature of such applications is the massive datasets and the need for sharing of the data in the geographically distributed locations and hundreds of researchers worldwide. These researchers need to be able to transfer large subsets of these datasets to local sites and other remote resources for processing.

The definition of Grid has evolved from time to time, as fast as in a year or two it has changed. Following are some of the definitions proposed by Ian Foster and Carl Kesselman who can be considered as the fathers of Grid technology.

In 1988, Grid is defined as “a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.”

In the year 2000, this definition was further refined as “a coordinated resource sharing and problem solving infrastructure which works in dynamic, multi-institutional virtual organizations”. The key concept at this point was the ability of Grid to negotiate resource-sharing arrangements among a set of participating parties and then the pool of resources was shared among some computational tasks. During these years, the main stress was levied on resource sharing as compared to any other advantage of Grid technology.

Sample: Management Science
Branding plays a vital role in the buying traits of customers. Intentionally or unintentionally we are poised to give preference of our choice towards specific brands. The branding theory has worked on human psychology for a long time. Branding has evolved from a marketing technique to a science, the brand science which works on human psychology.

Branding science is not limited to organisations anymore, it has been implemented in creating cities, and even countries, as brands. Consider the case of Liverpool city which is to become the European Capital of Culture in 2008. Liverpool has been actively promoted as a cultural city by the Dept. of Culture, Media and Sport, UK, while India has been branded as the IT-enabled services hub by its government. In both the examples, the brands of Liverpool and India have benefited through this image building. Branding science has worked on currencies as well; the US dollar remained a dominant currency in world markets for a long time but recently the common European currency – Euro – has challenged its position and gained initial advantage over it.

The theory of branding applies to all sectors of the industry. Branding is an evolving process and never discontinues. Organisations build brands and then sustain them. Older brands are being replaced by more innovative new brands. The branding science builds upon the science of marketing – the better you market your products and services, the better your brand value. The “mantra” of branding works in all departments of the lives of people.

Probably the most perfect example of the influence of branding can be found in the spirits and wine industry, with older brands clearly outperforming new brands in market, thus giving newer brands a real chance of creating their own mark.