BKMD

Let me add some contrast to this discussion. This past admissions season, our school had an applicant who was very qualified but not sure if she even wanted to go to grad school. She was at the top of the pile, and we recruited her very heavily, even though she was obviously a high risk student (in terms of dropping out early). If you are desired enough, then they might not care so much. The simple fact is that a ton of PhD students drop out. The company I work at is full of PhD drop-outs, not because they planned to leave with a free MS, but because they simply realized it wasn't for them and decided to stay after doing an internship. It happens. It may not cost the schools as much as some people have suggested, because stipend funds usually come out of larger government grants, and treating the tuition waiver as part of the cost isn't quite the same when you're talking about students who would never have paid it to begin with. That being said, it seems unlikely that someone who's not qualified to have their employer pay for a MS could get into a PhD program. You also seem to lack some basic understanding of the PhD process which means you won't get in. I'll also note that funding is often guaranteed only on a year to year basis. If they suspect they are being conned, then your funding will get cut off, you'll leave without a new degree, and you'll have wasted a year of your life. And I don't need to note the ethics because you don't care.

It depends on your area of interest. It can definitely help your application in some cases. A lot of CS students have a weak math background and they have a lot of catching up to do if they study, say machine learning or signal processing in grad school. Not many people take subject GREs, so I know if our committee were to see an application with a very high math score (subject) then that would at least make the application stick out. And anything you can do to make your application stand out will help. That being said, I wouldn't report your scores unless you do >90%. If you do mediocre it might even hurt you. And as others said, a GRE score won't make up for other parts of the application that are crucial (research). But, all things equal, it will help.

I wouldn't take it because it costs money and it requires a lot of studying (it's a hard test, even coming straight out of school). If you do decide to take it, don't submit your scores unless you do well. If you do take it and end up above 90%ile then definitely submit your scores because it could give you a boost. If you don't do that well, then don't bother submitting the scores because it won't help and might even hurt.

If you already have 5 years of experience then you obviously know your stuff and to me it seems like the main reason to get an MS is for the sake of having the degree and hopefully advancing your career. I don't think getting an MS from an unranked school would achieve that goal. So personally I would do either USC or not do it at all. Or maybe you can reapply next year and see if you can get into a cheaper program that's more prestigious than CSUF (other schools in the UC system, etc)?

It's really hard to come up with quantitative ways to rank schools. Publication counts might be meaningful, but you also want to consider how often the papers are cited, where they're being published (high-acceptance regional conferences vs competitive high-impact venues), etc. And you want to somehow normalize by the size of the department, since obviously larger departments will have more publications. It's hard to measure this, and you have to make arbitrary choices. And then when you try to combine several factors (e.g. publications, admissions percentages, etc.), you have to come up with a way to weigh the different factors. At the end, you're going to have a ranking that's highly sensitive to arbitrarily chosen parameters, and it's almost meaningless (though you can still get a sense of different "tiers" of schools). The US News rankings are nice because for grad programs, they're based only on opinion surveys. No parameters to tune; just a straightforward way to directly measure the perceived prestige of a school. If you're interested in the reputation of a department, this is what you want, and these are the rankings people are usually referring to. When choosing between schools, I think the thing to look at is the actual job placements of alumni of the particular labs (not departments) that you plan to work in. Assuming your end goal is a particular career, then I don't see why anything else should matter. Obviously top schools are going to have better job placements on average, but you can find plenty of labs at lower-ranked schools with stellar job records (often at schools that you wouldn't guess unless you were familiar with that particular research area) and conversely, you can certainly find research groups at top schools that have a mediocre record. You'll also find that some schools tend to be oriented more toward industry vs academia which might be something to be aware of if you have a sense of which direction you want to go. I think the advice to go to the best school you can get into is "on average" a good heuristic to follow, but it's not always black and white and it might be the wrong thing to do in some circumstances. If you dig just a little bit deeper, you should be able to figure out how good of an education you'll really get and what kind of career placement you can expect.

It wouldn't hurt. The worst that happens is that they don't respond. I think some professors would be interested, and some won't, so try it. Also keep in mind that professors are already busy managing their own students, so they will probably be indifferent about this idea. You might try directly emailing students in the lab and looking for collaborators. You'll have better luck if you have specific research ideas in mind rather than offering open-ended support.

It is nice if the school has a center in your area so that there are many people you can collaborate with. Realistically, however, most of your research will be done with one or two professors, so if you have to choose between a great fit with one or two professors or a good fit with several faculty, I would choose the former option. I do agree that it's risky to join a department if there is only one professor you think you could work with, since it's not that uncommon for professors to move between universities, or to leave academia for industry.

Your question is which one has a better CS department. Personally I would say USC, though it depends on your specific area which I'm not familiar with. However, the question I would really ask is if you should do a PhD or MS, since as others said, they are very different. If you want a job beyond standard software engineering (which seems to be the case), then a PhD is probably better. However, I would be VERY wary of taking a PhD offer that is unfunded. Realize that this is very rare (though it seems to be somewhat standard at Purdue if I remember from last year). Be sure that you feel reasonably confident that you can get funding pretty soon, because 5 years is a long commitment to make to pay for school. You might consider doing a masters first and then re-applying for a PhD.

A few thoughts. I think you're right that they will expect more of students with an MS than with a BS, and if you have publications as an undergrad, that's more impressive than as an MS, simply because it's less rare. But that doesn't mean that it will disadvantage you in any way to have a MS - adcomms are looking for candidates with the right background and experience, and an MS can only help you in this regard. The only way I think an MS could hurt is if you bomb it and get a low GPA or fail to impress the people who will eventually write your letters of recommendation. If you have the drive and you plan to do a PhD, then this scenario is unlikely. As for publications - many but not all masters students will publish during this time, and it's definitely something to aim for if you want to get into a top school for a PhD. I know you said you started late in the game with CS so it may be hard to get into research right away, but if at all possible, I would start working on a publication as soon as you can. This is because it can take some time to get it published, and remember that you'll get applying for a PhD a year before you actually attend, which means that anything you publish in the last year of your MS will not appear in your PhD applications, so you need to do this stuff in your first year. I wouldn't say that journal publications are pointless - it's just that in CS, conference pubs tend to get more exposure, and journals are generally just extended versions of existing conference papers (which is a good thing to have, but it's not what you should aim for as a starting point). It's also true that it can take a year or more to get it published, because the review process is slow and careful, and you will have to make many revisions, then those revisions are reviewed again, etc.. (Though sometimes journals periodically have "special issues" which usually have a rushed review process, so you might be able to get something finished within half a year.) I would recommend submitting to conferences, though you will have much higher impact if you submit to the top conferences in your field, and not just any conference or workshop. It's not "hard" to get something published if it's a very good paper. If it's only a "good" paper, then you'll probably eventually get it accepted, but it can be harder - the thing is that many conferences have more good papers than they can accept, so it's kind of a crapshoot which borderline papers get accepted and which don't - it also depends on the reviewers you happen to get, and it's a fact of life that some reviewers won't understand what you're doing or won't put the effort into giving a thorough review, so plenty of good papers get mediocre marks. So my point is that if you start early, you can deal with paper rejections better because hopefully you'll still have time to revise the paper and resubmit to the next conference. Good luck!

Are you still in school? Are you going to have higher grades or more experience by the time you reapply? I'm just wondering because if your application is going to be basically the same when you reapply, there's no reason you would do better the second time around, so you might as well take your admissions now. If you do think your application will be substantially better if you try again in the future, then I would reapply. UIC has a decent program but it doesn't have the name recognition that a lot of schools have and you might have better job prospects somewhere else, though it's good enough that I would just take the offer if you don't have a strong reason to think you'll do better if you reapply.

This. You'll almost certainly get into some top 20 schools with your credentials, but the quality of your publication will help distinguish you from other applicants at the most competitive (top 4) schools. It's increasingly common for undergrads to have publications under their belt, so this isn't an automatic advantage, so where you really have a chance to shine is by not only publishing a paper but publishing an idea that's non-trivial and actually moves the field forward, rather than an obvious idea with straightforward results. It's good that you're the one who came up with the idea - this is important and your letter writers will mention it. And of course fit with research interests is another major factor - when professors are deciding which prospective students they are interested in advising, a match in interests is very important. You probably won't get admitted even with the best credentials if the professors don't think your interests would align what theirs', and it's amazing how many applicants don't realize this. So my point is not to stretch yourself thin and apply to too many places since many of them won't be a good fit anyway, but focus in on schools that you really are enthusiastic about with professors who are already doing what you want to do. Play up this fact when you write your essays, and be specific about who you want to work with and why. Also keep in mind that the best professors in your particular area of interest might not necessarily be at schools with the highest US News ranking. A lot of applicants ignore this or don't realize this and it's a shame. I think you'll have a good application, so good luck!

It looks like you have a decent coursework background. I would spend the rest of your masters focusing on doing either programming projects that you can use to show that you know your stuff, or research projects (better). I know you said you're in a professional program and aren't doing research, but there should still be opportunities to do this, and I think it will help your PhD application more than anything else. Unfortunately it might be too late to apply to research-oriented summer programs, but maybe you can still find something along those lines. You might also take some initiative and come up with a research project on your own - if you aren't in a research oriented MS, your professors might not get involved, BUT if you were to come up with something cool on your own time and show them what you've done, I'm sure they would be supportive in helping you publish your work or anything that might help your grad applications.

If I had to choose right away and if I had to choose only one (luckily at my school neither of those things are true, I wish this was a standard policy), I would go with B. It definitely helps to have an advisor you connect with, but if A has 30 students, I don't imagine you'll get a lot of one-on-one time which I personally value. Some tenured professors meet with their students individually every 1-2 months and have little input on their students' projects beyond helping to edit their papers. Some students don't mind this setup, but I'd rather have an advisor who is hands-on (not controlling but involved) and I find that this is much more likely to be true with younger professors who have more time. Newer professors will likely push to publish more which will benefit you as well. I would also say research fit is more important than personal fit, but then again, your research interests may change, so if you're still open to new ideas then maybe A would be better, since it sounds like you might prefer him. I think it's a bad policy for a school to assign you to an advisor right away since ideally you should be able to explore your options first. On the bright side, at least you get to choose, since some schools make the decision for you. I'm sure you will be in a good position either way and you should be able to collaborate with both faculty, plus you can always change your mind in the future. Good luck!

Both have pros and cons, so it really depends on your area. Knowing nothing else, I would say UPenn is better; I think they have a better program generally and a better reputation, but JHU might be better if you're interested in NLP or biomedical stuff. Philly is nicer than Baltimore, but Baltimore is in the D.C. area and would be good if you think you are interested in government jobs.

If school B is still far enough away to put you into a long-distance status, then it really doesn't make a difference, right? I would say short of being engaged, you shouldn't make this choice around a relationship. If it falls apart (which you say is a possibility), then you'll have no reason to be in a worse school. That being said, I don't know if school B is "worse". Most CS schools in the top 50 have good reputations and I can certainly think of some top 40 schools that are still comparable to some top 10 schools. It depends a lot on your subfield as well as what career you're looking for in the future. If you figure that the programs are close enough in quality, then pick the option that's better socially. On the other hand if one of them is clearly better than the other academically, then personally I would go with that, since that will (probably) be a more important factor in the long run. Of course, I don't know the specifics of your schools or your relationship status so take my advice with a grain of salt. Good luck!

Well, if you prefer an urban location, College Park has the advantage of being a very short metro ride from DC, if you wanted to live there. It's also somewhat close to Baltimore as well, like you mentioned (and collaborations with JHU as well as UMBC and even APL seem fairly common).

Are you planning to do a MS or PhD? Since your undergrad is a non-technical major, departments may want you to do an MS before going on to a PhD. If you do a higher degree in CS, then you'll be expected to already know core things like programming, data structures, algorithmic analysis. You might need to do some catching up on background material. The Subject GRE is recommended if your undergrad degree is in a different field, since otherwise the schools do not know how well you understand the background material. However, this test is pretty tough (it can take a lot of studying even for a CS major). It's also possible that if you are applying directly into an HCI program (I know CMU has this) then they might not require as much of a CS background. You may also consider directly applying to a social science department rather than CS, since often those departments still do computational research. It is actually fairly common for AI researchers to be in linguistics or cognitive science departments rather than computer science, if that is the area they are stronger in (in other words, if your BS is in linguistics and you want to do language processing, you might still do your PhD in linguistics even though you'll be doing computational stuff - the NLP group at Stanford is pretty evenly split between ling. and CS students, for example). Computational social science is becoming a popular sub-area so you might fit well into that - for example there is a center for that at UMass (http://www.cssi.umass.edu/). I think there are a lot of cool ways you can combine your background in sociology with computer science and statistics, so that might be something to consider. Anyway, I agree with others that you should be specific about what you want to do when you apply - but you still have several months to decide. It sounds like you already have good ideas about what you find interesting and what you'd like to do, so just keep thinking about it. Maybe read some textbooks for AI and HCI (the standard text for AI is Russel&Norvig; I don't know much about HCI) to get a sense of how they compare. Take a look at research papers in the different fields and see what excites you more. Good luck!

I think your intuition is right that UMass is probably better for machine learning generally while UMD would be better for NLP. That being said, UMass has hired some NLP people recently (David Smith last year, Aria Haghighi this year). Conversely, the NLP people at UMD are certainly strong in ML, and they recently hired Jordan Boyd-Graber who is more ML-oriented, and Hal Daume who is very strong in both fields. That probably won't help your decision, and honestly I'd say it's a toss-up in terms of the quality of the programs. Instead you might want to consider other factors such as the location, the job placement of alumni, the type of computing resources that are available, and who specifically you might prefer as an advisor. It's unfortunate that you can't visit UMD since honestly I think the people you'll be working with (both your prospective labmates and advisor) is the most important factor and it helps to actually meet them. You might want to see if you can have a phone conversation with UMD faculty you're interested in; I was able to do that when I was choosing schools. Get a sense of their personality and how the program is run, to see how you might work with them as an advisor. You might also consider emailing grad students in each program to ask about the lab, the faculty, the program in general, etc... see if you can find a reason to prefer one over the other.

Just tell the school you need more time to hear from other schools and they will probably accommodate you. Don't keep them in the dark on your situation and give them the potentially false impression that you've accepted.

As other have said, there are certainly different "tiers" and rankings can roughly define them, but individual differences in rank are generally not important or even statistically significant. Even large differences in ranking may not matter when you consider a particular subfield. The problem with rankings is that they are for an entire field, whereas the perceived prestige within specific research areas is often different. Keep in mind that when you apply for PhD-level jobs, the people who are going to be making hiring decisions will be researchers who are already familiar with your program, rather than HR people who will be impressed by the name of your school. They will know your advisor, they will have seen you give talks at conferences, and they may have already worked with you through internships or collaborations. All of these things are more important than the overall prestige of a department. Looking at a particular lab's placement record might be more useful than rankings. I ended up choosing a #25ish school over a #1 school, which was a hard thing mainly because I couldn't get over the ranking. But honestly, my program has a better placement record (for both academia and industry) than the other program, and many of my advisor's students were directly placed in assistant professor positions at other universities (including the #1 univ that I declined). So it really just depends. And this isn't to say that placement records are the most important factor either, since ultimately what matters is finding a good fit with a lab and an advisor.

I think it would help, but mainly if it gives you research experience in the process - coming up with something innovative is more important than doing well in the contest. Saying "I came up with a new and unique algorithm, and even though it did not perform as well as existing methods, I learned a lot about the research process" would be more convincing in your essay than "I tried every algorithm I learned about in class, and this one ended up working quite well."

I think CMU is worth it. I think for a professional-oriented track, the program you go to matters even more than if you're doing a research-oriented program, since future employers will be looking primarily at your transcripts, rather than your publication record. CMU also has extremely close ties with industry. Google has offices right on the campus, and I believe IBM and Apple also have branches in Pittsburgh.

Not necessarily. The NLP group has their own interview and decision making process. I honestly don't know if the other research areas do interviews.

I'm at JHU and while I'm not directly involved with admissions, I can tell you a few things I know. 1) if you were interviewed it means you are on the short list, though I'm not exactly sure what % of those are made offers. 2) I think the professor was wrong to tell you two weeks because I know that they only started the final decision process this week and actually they have not completed all of their interviews. It will be a while longer before they have made a decision. Last year, I was not notified until the 3rd week of March (informally over the phone; I did not get an official letter until the last week of March). I also know that they do wait-listing, so if you end up on the waitlist, you might not be notified until even later. Their decisions go out much later than other schools, which is frustrating, but don't be concerned that you haven't heard back.

I agree that the regular GRE is a waste. However if you're coming from an unknown school then I think the Subject GRE could help. If you have a high score (>90%) then it will bring attention to your application. As others have said, your research experience is ultimately more important, but it can help.