Pauli

I think it would be a better idea to decide on the program based on what labs interest you there, not on what number is given to them based on people's perception of their prestige.

Yep, I agree as well. Very sound advice.

Those acronyms don't make sense to me.

ಠ_ಠ Many graduate students start their PhDs in their late 20s.

Both are ಠ_ಠ

One of my professors once said that as long as there are computers, there will always be a need for people with advanced degrees in computer-related degrees (e.g., IT vs CS). And the specialist vs. generalist thing, IMO the generalist route gives you much more flexibility in the types of jobs available, while the specialist route would make you a stronger job candidate. Someone else in the forum might have a different take on this though. If you're interested in going the CS lecturer route, the best instructors I had in my CS program for my intro CS courses had Master's degrees in either IT or CS.

The CS qualifying exams and preliminary exams will disagree with everything you said if the OP goes the PhD route, even at weaker programs. PhD candidates in CS -- regardless of specialization -- will be expected to be prepared to correctly answer a wide variety of possible questions from core topics such as "what is a red/black tree" or "define a n*log n sorting algorithm" or "what is the difference between P vs. NP". That doesn't even cover area research topics. Those type of questions do require a bachelor's degree or at least a couple years of catching up for the OP. That's not a pessimistic view, that's a realistic one. Unless the OP decides to sacrifice two years to build up the fundamentals or decides to pursue a Bachelor's in CS prior to going for a PhD, the Master's route is the best scenario. There we go again with the false hope and after-school special talk. People with stronger academic backgrounds in related engineering and hard (i.., as opposed to soft, not as opposed to easy) science disciplines have burned out pursuing CS PhD work. You're seriously just dishing out bad advice now.

The original poster wanted an honest opinion. I provided one; you're giving false hope. There's passion and then there's realism; and the original poster really isn't qualified to do a PhD in CS. But Master's is doable and better fits the criteria. I agree. This is very sound advice.

In your original post, you said that you wanted to be a CS professor. To be a CS professor, you need to have a PhD degree in CS. To get a PhD degree in CS, you usually would need to at least pass a qualifying exam, preliminary exam, and write a contributing dissertation. To do so without a bachelor's degree in CS or without spending an additional couple years of catching up on prerequisite courses before actually starting CS graduate courses is pretty much impossible. When you said CS professor, did you mean CS lecturer? CS professors are actual scientists whom perform research, CS lecturers teach courses that usually cover courses related to technology such as what you describe in your original post. The former requires at least a PhD and goes through the more vigorous route, the latter requires at most a Master's and doesn't.

I don't understand what you're trying to ask. 你是中國人嗎?

Based on what what you described in your original post, I wouldn't recommend that you pursuing a PhD in computer science.

Choose a school by how well it matches with your interests and preferences, never by its reputation.

Digital archiving and retrieval of relevant information for a large group of people is very challenging (they even have conferences specifically dedicated to addressing this problem) such as through a wiki because it's such a huge workload. The path of least resistance with information is often through forums because people can most easily summarize answer for others based on information being distributed through others. It would take a dedicated effort for people to get a wiki set up, but unfortunately I doubt people who did the program last year would be interested or have the time.

I've seen STEM often used to mean "Science, Technology, Engineering, and Math", and usually referred to teaching programs.

ACM Digital Lib ACM Digital Library (Best) CiteSeerX IEEE Xplore DBLP Google Scholar (So-so)

Until May 31st, 2013? That probably just means that it's in the annual funding period, but since the grant only goes until the end of summer, there doesn't seem to be any conflict at all. Of course, it's always good to contact Elena regarding this, lol.

San Antonio may have a smaller metro area compared to cities in California, but the city is still large. What university are you attending, BTW? Trinity? UTSA? If you wish to live in areas that have young people and/or near some of the universities, you could try to live in the Medical area or in the 1604/I-10 area. Stay away from the south side.

There's a decent number of foreign universities on that list, especially from the Indian and Korean. And regarding the domestic schools, I don't think there really are applicants that apply to those schools from unknown domestic schools, lol. Adcomms do have a pretty good knowledge of many universities already, and people who apply to grad school tend to come from at least a somewhat familiar university.

Well, there's three points to keep in mind: The importance of networking appears in all facets of life. This is much the same with "legacy student" situations, where networking just happens to be a blood relation with an alumnus. "Legacy students" only really matters for borderline case students. A student with a great academic portfolio will be accepted to at least one university regardless. Like mentioned earlier, this is really only something that's seen at the undergrad level.

Correct. Well-known schools but not the name schools that the OP posted. And some of them are less generally known schools. aberrant still makes an indirect point that those applicants got in by the strength of their academic portfolio, not simply where they came from.

Unless you can secure a spot in a research lab at Cornell or are willing to spend a semester or two proving yourself to a specific lab's director to get funding and attention for co-authorship, it's not worth the effort.

We're in the same boat. Like yourself, some of us also have experience applying for top Masters and PhD programs in Computer Science as well, and already completed years of PhD programs like myself. What we're saying is that people should not be using where they went to school as crutch, and that the illusion of a school's prestige seriously doesn't matter because you're neglecting to mention (especially for the OP's case) that the OP actually to apply to the grad school twice (once to the actual program, once again to the research lab). Even if the OP passes through the adcomms themselves, don't forget that research lab directors have to admit them themselves, where they don't even bother looking at where the applicant went to school. Yes, this bias exists and we're aware of this. But the discussion has always been about the importance of where one went to school in isolation. What you're forgetting is that where one went to schools is a part of MANY factors. If someone did only average with their scores in the time they spent at a name university, adcomms do see this as wasted potential because they would have a bias towards higher expectations in that program. If they didn't do well or only did average at such a program but don't explain themselves in their academic portfolio or essays for the reasons why they didn't do well (e.g., personal hardships, more focus on research publications), this actually hurts the applicants even more than using their name school as a crutch. Adcomms are looking out for the interests of their own programs, and they really are looking for a great fit. And this sums up the discussion nicely. If someone goes to an unfamiliar university (like some obscure university in a foreign country or a non-name program at a known university), it hurts them. That's not really true in the converse case, especially since most applicants will be coming from prestigious name schools or had stellar performances from familiar-named schools.

No, there's a very good reason why your advisor got a PhD and was hired to be a professor at that university. Your advisor is also going to be the co-author of whatever papers you publish in grad school, so you really should be trusting your advisor on which conferences to submit to. That's why they're called advisors.

But the thing is that all engineering/science programs from the Top 40 schools are difficult in general. Yes, Berkeley has a strong program, but almost everyone who applies to grad school -- including to those prestige name schools -- already come from strong programs, so where someone went to school before is negated.

It does not, because adcomms don't judge a PhD applicant on such a narrow set of factors that the OP posted, but on much richer information such as strength of reference letters, essays, and publications. Without that information, his primarily list of scores would give an inaccurate approximation. What? No it doesn't. Adcomms put much more focus in judging candidates based on their time there, not where they went to school. Even candidates who did their undergrad in state satellite schools will get acceptance if they were stellar during their time there.