Vikrant
     Khenat

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Vikrant Khenat is a graduate from School of Information Sciences, at the University of Pittsburgh.

Vikrant graduated in December of 2006 with masters of sciences. Download Vikrant's resume for your review by clicking here. Vikrant is a Java programmer with specialty in web applications. During his school work at School of Information Sciences, Vikrant worked for Personalized Adaptive Web Systems (PAWS) lab as a graduate student researcher. He worked in the field of adaptive hypermedia and multi dimensional data visualization in the lab.

Adaptive hypermedia means to make the web site adapt to individuals who use the site. Personalization in service provided to the user is now not just a standard, it is a necessity. Users demand personalization in all the products and services they buy. An example of this personalization and adaptive hypermedia is Amazon.com. According to what a user buys, the site suggests to the user, they should buy other products, which either are accessories to this product, or were bought by other customers that bought the same products. People and businesses demand personal attention for all the services they buy, web sites should be viewed similarly, like services people need. Web sites are sources of information that help the customer to make an informed decision to buy some product or service, in case of e-commerce or simple brand building or assistance in the case of non-commerce site. Visualization is the easiest way to analyze data.

For humans, it is easier to look at graphs and maps and understand the relation between two or more compared objects, than to look at the numbers and come to the same kind of conclusions. Looking at two axis in a graph and manipulate these two axis against each other is quite a long term practice. In real world dynamics though, most objects have more than just two attributes which needs to be compared. In that case if the objects to be compared are manageably less, we can compare the objects across multiple graphs. In reality though, most of the times, the number of objects to compare are in hundreds or thousands. It is hardly ever if even possible to compare such hundreds of objects in five different graphs. Multi dimensional visualization is the answer to this question. We can compare all of these objects at the same time against five, six or more dimensions. Vikrant worked on personalization of multi dimensional data. He wrote a web application (an applet supported by servlets) which draws a graph of a user’s career preferences as dimensions and courses as dots.