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So my case is a little different. I never liked my college studies much because the subjects never excited me, which eventually lead to a low CGPA (7.18/10). But I started to have a strong liking for NLP since the time I was first exposed to it. I've been drenched in NLP for a year now, and out of interest I have done several deep learning projects related to NLP, image classification etc...I also have carried out proper experimentations and submitted a paper to top NLP conferences in India and several other places(now I'm waiting for reply from these). I have 3 good LOR's, one of which is from my mentor-ship program with a reputed NLP researcher from CSIRO . My GRE score is 330/340. The programs at the top universities such as Stanford, UC Berkeley etc excite the crap out of me!!! Given the minimum aspects of my application, should I apply to these universities?? And is it plausible to expect an admit from these universities?? I am desperate for answers, so any help would be highly highly apreciated.

EDIT: This is not a duplicate of any of the questions out there. Its a specific problem which I did not find anywhere on this platform. It could be of help to students facing the same issue.

marked as duplicate by scaaahu, Stella Biderman, Nicole Hamilton, Enthusiastic Engineer, cag51 Jul 23 '18 at 21:38

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

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    I recommend either (a) reviewing your understanding of the word "literally", or (b) consulting a doctor ;-) – Flyto Jul 23 '18 at 15:27
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Like most similar questions here, the answer is that you have a negative in your background, so you need to stress the positives. A low grade point will raise eyebrows for many, but it needn't be, of itself, disqualifying.

You indicate here you have been doing interesting (to a researcher) things and that is a big positive.

I'll go out on a limb a bit here and guess that a top university will actually be easier for you than a mid-range one, simply because such universities as Stanford are used to dealing with outliers and unique situations. However, it might also be necessary for you to attract the attention of some professor there who might want to work with you.

A mid-range university might attract many students of sufficient quality simply by following a set of rules that have worked for them in the past. Their students are somewhat alike in background and interest. A top university can afford to act differently since they attract so much attention. You have to convince them, of course, that you have exceptional qualities that will fit well with their overall educational mission - turning out the best of the best.

But the best test of it is to try for admission. If you don't try you are guaranteed to not be accepted. I realize that it can be costly, of course.

Most of the other students you would find at such schools probably arrived there with an easier path, and also carry a better background of knowledge, though that isn't necessarily so.

Having been published is a plus, of course, so you should continue to work on that.

You will need to be able to explain the deficiency, how you work to overcome it, how it hasn't mattered in the things you do, etc. The new University will need to assure themselves that you can learn and that your old issues won't reappear. Good recommendations from recognized scholars can help. Likely the people you work with have some connections that you can draw on, both for advice and assistance.

Another option is to enroll in some related program at a top university and prove yourself there before applying to the program you prefer. This is a longer process, of course.

  • This answer was kind off what what I was looking for. But, can you please stress on the part where you say "I'll go out on a limb a bit here and guess that a top university will actually be easier for you than a mid-range one, simply because such universities as Stanford are used to dealing with outliers and unique situations." – Satya Jul 23 '18 at 15:41
  • @satya, see the latest version. – Buffy Jul 23 '18 at 15:47

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