My primary interest is in Data Mining. Secondary interests are Intrusion Detection and Energy Efficient Buildings.

I have done projects in data mining approaches for intrusion detection. I have also done research in data analysis on energy consumption patterns in smart-buildings.

I will be applying for graduate school (MS) shortly. Now, how do I proceed writing my statement? Should I lay more emphasis on Data Mining? Which professors should I mention I want to work with? Ones doing data mining research, or the ones doing network security/sustainable energy research?

My main concern is finding potential advisers. I believe if I can find some before the application, I can find out their requirements and write a statement accordingly. This in-turn might help me get admission in the desired school as well.

My question here is whether I should look for researchers in data mining (which I have applied in my works) or intrusion detection/sustainable energy (the domain where data mining technique was applied)

I understand that chances of me finding advisers that share interest in both data mining and (intrusion detection/sustainable energy) is very less. So which advisers should I target?

  • You say you're graduate school, but you don't say in what. That will rather dramatically change the answer.
    – Fomite
    Commented May 7, 2014 at 14:20
  • Graduate School, Masters of Science M.S. (Computer Science) Commented May 7, 2014 at 15:19
  • I would like to add my own experience to argue for generality: When I was starting grad school, I was interested in cancer biology, evolution, microbial population dynamics, bioinformatic, functional genomics and synthetic biology. Some of these I had actually worked on; others were topics unfamiliar to a typical biologist which I happened to understand and be interested in.
    – Superbest
    Commented May 7, 2014 at 16:55

2 Answers 2


I have some insight here.

There are some advantages and pitfalls in the advisers you have described and I have experience with both.

Researcher in Data Mining: Here most of your research will be focused in the way you can modify the algorithm to attack the task you have at hand, your adviser will want to see some insight from you on how things are actually working and why are you getting the results you are getting. He will be potentially interested in the application, but he has had so much experience with many different applications, that he will want you to use a generic dataset so you can compare it with other works and prove your approach works better.

You will have insightful conversations about your algorithm, and what can you do to modify it, but any insight from the data itself will probably have to come from you.

Researcher in Area X where Data Mining is going to be used: He will probably not care much about the algorithm you use, as long as it is useful in the particular problem he is working with. He will most likely have a problem for you to work with, and he will expect results, good results. You will have good conversations about the nature of the data, and will learn a lot about the field, but you might feel a bit isolated in the Data Mining part.

The main question is, what do you want to do afterwards, if you want to do a PhD, in which kind of conferences do you want to be? Data Mining Conferences, or that area conferences?

If you are going to the industry, having much expertise in a particular area can be both good or bad, depending on he job you are applying to.

As an example, I did my PhD on Machine Learning applied to Molecular Biology, and even though I had all the theoretical framework to apply it to Natural Language Processing (NLP), most places would not look at me unless I had some NLP experience.


From my experience, the process of searching for and applying to graduate programs occurs simultaneously with the searching for graduate research labs. Successfully interviewing at one can significantly impact your chances for being accepted to the other.

With that in mind, start your search with a very specific goal in mind, and only after that fails you can branch out. A simple google search shows at least one promising possibility, I'm sure that if you actually spend some time researching positions you'll find a lot more. Once you've run out of leads there then you can start looking at labs specifically focusing on one or the other. In your case specifically, it just so happens that data mining is a very broad and extremely in-demand skill in virtually all fields, so you should have no problem finding positions in almost any field that would benefit from having data mining expertise as well.

For your letter, I would express your interest in data mining (the general skill) first, and then your interest in sustainable energy or whatever (the specific skill); this way, they'll see that you have an informed set of research interests, but are interested in working in other fields as well if your specific subfield interests don't work out.


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