Information Technology Reference
In-Depth Information
In choosing a topic and advisor, many students focus on the question of “is this
the most interesting topic on offer?”, often to the exclusion of other questions that are
equally important. One such question is “is this advisor right for me?” Students and
advisors form close working relationships that, in the case of a Ph.D., must endure
for several years. The student is typically responsible for most of the effort, but the
intellectual input is shared, and the relationship can growover time to be a partnership
of equals. However, most relationships have moments of tension, unhappiness, or
disagreement. Choosing the right person—considering the advisor as an individual,
not just as a respected researcher—is as important as choosing the right topic. A
charismatic or famous advisor isn't necessarily likeable or easy to work with.
The fact that a topic is in a fashionable area should be at most a minor considera-
tion; the fashion may well have passed before the student has graduated. Some trends
are profound shifts that have ongoing effects, such as the opportunities created by
the Web for new technologies; others are gone almost before they arrive. While it
isn't necessarily obvious which category a new trend belongs in, a topic should not
be investigated unless you are confident that it will continue to be relevant.
Another important question is, is this project at the right kind of technical level?
Some brilliant students are neither fast programmers nor systems experts, while
others do not have strong mathematical ability. It is not wise to select a project for
which you do not have the skills or that doesn't make use of your strengths.
A single research area can offer many different kinds of topic. Consider the fol-
lowing examples of strengths and topics in the area of Web search:
Statistical
. Identify properties of Web pages that are useful in determining whether
they are good answers to queries.
Mathematical
. Prove that the efficiency of index construction has reached a lower
bound in terms of asymptotic cost.
Analytical
. Quantify bottlenecks in query processing, and relate them to properties
of computers and networks.
Algorithmic
. Develop and demonstrate the benefit of a new index structure.
Representational
. Propose and evaluate a formal language for capturing properties
of image, video, or audio to be used in search.
Behavioural
. Quantify the effect on searchers of varying the interface.
Social
. Link changes in search technology to changes in queries and user demo-
graphics.
As this list illustrates, many skills and backgrounds can be applied to a single
problem domain.
An alternative perspective on the issue of how to choose a topic is this: most
projects that are intellectually challenging are interesting to undertake; agonizing
over whether a particular option is
the
project may not be productive. However,
it is also true that some researchers only enjoy their work if they can identify a
broader value: for example, they can see likely practical outcomes. Highly speculative
