jawaiah
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Posts posted by jawaiah
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I won't claim to be an expert on this, but everyone I've talked to seems to think that PhD is the way to get funded, whereas MS is much more difficult to do so.
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I wouldn't recommend changing your interest just to get into grad school. Your interests are what you're going to be working on for at least 5 years in school and then in your career after that. Granted your interests are going to change naturally over time, but I don't think you should just say you're interested in a field to get into grad school - adcomms will probably be able to figure out that you're not very interested in that area if you really aren't interested in it.
As for your chances, I think you have a fairly good chance of getting into a few of those schools you have listed there. Brown, Johns Hopkins and Columbia will be very difficult to get into (around 10% or less). Rensselaer isn't a very highly ranked program but it's acceptance rate is around 12%. I think you would have a fair chance at Stony Brook and you should have a pretty good chance at the other schools you have listed. Also, don't short change your research experience - you have research experience, which is a very important part of the application. That alone will help you to stand out. Also while your GPA is 3.0, the fact that it improved significantly over the last two years will help mitigate that. All best!
Wow thanks bro, that really boosts my confidence. I appreciate it much.
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Hey guys thanks,
Academic:
Graduating from pretty low-key school, University of Hawaii (best CS program in the state!) with a BS in CS and math minor
Only a 3.0 overall (rough times early on) but 3.5 the past two years and 3.89 last year.
I want to get into a PhD program because I am genuinely interested in research.
I'm interested in text data mining right now, but mostly because I want to get a good start in the field of machine learning in data mining.
I'm also interested in neuroscience, but only extracurricularly.
Research and Work:
I had a small geoscience database research project a couple of years ago, but it's barely worth putting on the resume.
I spent a summer and a winter working as an intern software engineer for the WM Keck observatory here on the Big Island, doing some cool (but fairly rudimentary) database and web interface stuff.
This past summer I traveled to South Carolina and did a text data mining REU internship at a university.
Currently I'm working on an avalanche classification machine learning project for my school, which I'll have a paper for probably in January or February, but not in time for this application season. I'm also doing assignment preparation for a python bioinformatics class next semester.
GRE:
I have 800 quant. and 650 english but only 4.0 on the writing part (I accidentally skipped the last portion of written material because I thought it said it was optional).
Recommendations:
My department chair (known me for 6 years, taught me AI), my current boss for the avalanche project (was also my database teacher for one year), and my mentor from this past summer's south carolina internship. fairly strong references from each of them.
My biggest concern is that text data mining doesn't seem like a particularly well-funded field; and the best places to study it are top-30 schools, which I don't think I'm really qualified for (see list below)
However it is the only thing in which I have serious research experience at this point, so I can't see justifying applying to grad school under any other premise. Would it make more sense to just change my field of interest in the applications?
Top-Schools:
Brown University
Johns Hopkins
Washington University in St. Louis
Stony Brook
Rensselaer
Columbia University
Mid-Schools:
Northeastern
UMass Boston
Worcester Poly Inst
Safety:
University of Rhode Island
Fellowships (so far, planning on a couple more):
NSF GRFP
Am I aiming too high? What are my chances of getting in to something?
Also, any ideas on good fellowships?
Good school or larger research group?
in Decisions, Decisions
Posted
Hello again,
I'm trying to decide between offers from a couple of (both fully-funded) CS PhD programs; I won't name any names, but let's call them "University of Alpha" and "Theta College".
U of Alpha is a very well-known school with a super-strong reputation in programming languages. In fact, most of its department is oriented towards the study of programming languages (PL). It also just got some really big grants for the study of PL, so I know that the department itself, in addition to having a strong reputation, is well-funded.
The only problem with me accepting at UA is that I'm not exactly pro at PL. My research interests are tangential at best (machine learning (ML) and data mining) and given that I was very straightforward and honest with these interests in my application, I'm kind of wondering why I even got admitted. UA does have a ML research group, but it is a fraction of the size of their PL research group, and I get the impression that all but a few of the ML professors are not very active with publishing their research any more.
Theta College on the other hand is by no means a well-known school, but has a larger percentage of their CS faculty studying ML and data mining, and in particular has several younger, tenure-track professors who are pleasingly active ML researchers, having published multiple papers in both journals and conferences already this year.
I see my options at this point as follows:
Any advice?