[Research experience after you graduate from undergrad]

Do you have a friend who's already in a PhD program? Maybe they'd be interested in collaborating on something. This would work even better if you're super friendly with a professor.

 

Otherwise, maybe reach out to some professors who would remember you from undergrad, and see what they say?

[Undergrad Research for PhD Admissions]

Two questions:

 

1) Do we have to know our exact research area when applying to top CS grad schools? Or do they want us to go into grad school exploring topics/advisors?

 

2) Similarly, if we happen to know exactly what we want to research in grad school, will having all our undergrad research in a different field hurt chances of admission? For example, if I did my undergrad research in a couple areas (let's say parallel computing and mobile computing), but I want to pursue a different area (say machine learning) in grad school, will the fact that I haven't done research in the field I want to pursue hurt me? 

 

1. Thirding all the other people who said, "no."

 

2. I don't think so. You can play this in a bunch of different ways. Personally, I pretended like I wanted to stay in the area where I'd build up a research track record, then I switched areas once I was accepted to grad school. That made it easier to tell a story in my applications. That's not the only way to do it though --- I know people who were more straightforward about switching in their applications, and they were still admitted to top schools. 

[How much research do you need to get into a top 10 school?]

I agree that these are the right qualifications for a top-3 school applicant. However, this is not necessary to be admitted to a top-10 school. More important are that you have any research experience (preferably at least a year), an excellent SOP describing what you did and what you learned, experience with communicating your results, and other people (recommenders) who are also willing to write positively about the quality of your research. 

 

I'd second most of this advice.

 

Letters of recommendation are the most important thing. Sure, publications are really helpful, but if you have really strong letters of recommendation written by people known to the admissions committee, it won't matter too much either way.

 

Incidentally, the Stanford CS PhD admissions committee doesn't even read your SOP --- don't know how that compares with other schools.

[General Advice -- Questions Welcomed]

Hi fdhkjal,

many thanks for the advice, they're really good points.

I do have one question: Most of the top-ranked CS programmes / departments share two common features I think. Firstly, they are generally quite large in size. Secondly, they all do committee-based admissions to the programme (rather than to specific areas / faculty members).

For such programmes, how do you argue your fit to the department on your statement of purpose?

Sure, I can write something along the lines of 'I'm interested in Stanford because Prof. X and Y are doing very interesting work on Z, which fits well with my background in this area.', but then so are Profs. A and B at Berkeley and C and D at MIT, and so on, so I feel that this isn't a convincing argument why I should be at Stanford specifically. Also, obviously a programme like Stanford has outstanding faculty in just about any area you can think of, so I'm not sure how much an argument as above would make me stand out from the crowd.

At the other end of the spectrum, I could try to argue that I feel I fit very well with the programme overall due to the department's strength in several key areas that I might be interested in. But then this would essentially amount to not much more than 'I want to go to Stanford because it's Stanford', again not a very convincing argument.

Any thoughts?

Here are two examples of successful personal statements which, to varying degrees, address this question: Jean Yang's (now at MIT) and Ethan Fast's (now at Stanford).

From Yang's (for CMU, where she got in):

My career goal is to remain in academia as a professor so that I can pursue my research interests while training and recruiting others to solve relevant problems in programming languages. I want to continue my studies at Carnegie Mellon because it has a large programming languages group with many professors with whom I would like to work, including Professors Harper and Aldrich. Because I find it important to talk to with different areas of focus than my own, I also like the diversity of CMU's computer science research. Because I look forward to teaching as a graduate student, I like that CMU has a reputation for having motivated undergraduates who can challenge my understanding of the materials. For these reasons, I would like to spend my next six years at Carnegie Mellon.

From Fast's:

My research explores the boundaries of automated software development, investigating to what extent computers can assist humans in writing code. In particular, I am concerned with how techniques from machine learning might be applied to applications in programming languages. Along these lines, I am especially interested in working with Professor Engler on automatic bug detection, Professor Aiken on statistical debugging techniques, or Professor Koller on applications of machine learning. By combining statistical learning methods with elements of semantic and program analyses, I hope to construct algorithms that reduce the cost of developing reliable code.

[And later, addressing fit:]

In working with Professors Weimer and Forrest, I have learned much about what it means to produce high quality research, and I have come to realize that I will need a PhD to work on the cutting-edge problems with which I am interested. Moreover, I expect that I would thrive at Stanford. My contributions to APR occurred at many levels of the research process, from high-level brainstorming and hypothesis formation, to the logistics of experimental design and academic writing. Further, I have published work contributing directly to the state of knowledge in programming languages and machine learning. In short, I have discovered a passion for that deep level of understanding enabled uniquely by research, and as a graduate student at Stanford, I would have the resources and mentorship necessary to pursue this passion fully.

So I actually don't think you need to be particularly convincing (neither of these examples were!)

[Phd in Computer Science at a different(better, maybe Top) school after Masters]

I can. But it will be a huge pain considering I still have one semester to go in my Masters and I have to also focus completion of my research. So, I wanted to know if it would be absolutely necessary or if I can offset it ?

You have the right idea; if your time is limited, don't re-take the GRE. Research is far more important. Focus on getting good research experience and letters of recommendation, and those things will maximize your chances at top schools.

If the admissions committee sees a wonderful LOR from someone they trust, no one will care about GRE scores.

[Does CS research topic affect job prospects?]

If you want an industry job as a software engineer, I don't think it matters. Write good code (and pass interviews) and companies will be happy to hire you. No one will care much about your research (e.g. all those PhDs who go to google don't work in their former research area).

If you want an industry research position, then of course it matters more. The key question here is: does your research have an industrial application? I'm pretty sure some companies hire all sorts of researchers (e.g. you can probably work in almost anything at MSR) but in general I don't know the ratios. A priori, HCI or networks would seem a safer bet.

You have other options, too. You could become chief scientist at some smaller technical startup, or a data scientist ("big data" is popular), CTO, etc. These positions often require a scientific background and credentials (and networking!), but in most cases your research isn't directly relevant.

So I'd say do what you're interested in if you can get it funded. You'll probably do better work. And unless you have very specific career goals, I wouldn't worry too much about a job.

[Need help deciding between two CS degrees]

Between the two, I'd say Computer Science; it's the safe, standard bet. But you might rethink getting a degree at all. It's surprisingly easy (and much less expensive) to teach yourself programming (or even the CS theory behind it) if all you want is a job in industry.

Programming jobs tend to be meritocratic, and I know plenty of people who hire candidates with no formal CS background. You just have to signal that you're good (e.g. contribute to open source, write a technical blog, post personal projects online). Then pass the interview... A degree will help, but it doesn't signal all that much, relative to what you've actually done/built.

Also, many people get their jobs through networking. So teaching yourself while developing a network (attending events/conferences/hackathons) might be a better use of your time.

Here are a few other options I can vouch for (again, if all you want is a job):

https://www.hackerschool.com/

http://www.bloc.io/

Doing a CS degree can be rewarding, but it's not the only way to enter the industry. It's also pretty expensive.

[Artificial Intelligence or High Performance Computing?]

Azezel & Anacron-- the professor who wants to work with me at UCSD does HPC. He was super nice, but idk that I def. want to do HPC. I've never even taken one class in it, and I'm more interested in theory, which seems closer to AI. I was a bit intimidated on both my school visits, so the fact that this prof was nice and encouraging, and kept saying that he really wanted me to go to UCSD made me like him more, though idk if this is a good way to choose between schools or not (since after I get there I may feel comfortable and realize I want to do something else). The UCLA prof does theoretical/game-based/problem-solving AI stuff. I've also never taken an AI class though. The AI prof was more stern, not as nice, and one of his students said that he was unhelpful as an adviser--- though his other student said he was the most amazing prof ever, and another random student was working his tail off in this professor's class just so he could have a shot at being in his research group. (he also got amazing reviews on rate my professor, though i know this isn't necessarily a good way to judge a research adviser)

Though, it sounds like I can change advisers when I get there, so maybe I should be looking at the faculty as a whole, instead of the two profs who will be my initial advisers.... I know I'm interested in theory, and UCSD has a better theory program, but if I go to UCLA I'll be essentially starting out with a theory person... it's hard.

Also, within CS do you think UCSD is recognized as a better school than UCLA? or visa versa? US News has the two tied at #14, QS world CS rankings have UCLA at #12 and UCSD at #33, though UCSD does way better (even better than CMU and other top schools) in the 'citations' category, and the National Research Council Rankings put UCSD ahead in research, student outcomes, and diversity, but UCLA ahead in two vague categories that are something like "what scholars deem a good school should have"....

UCLA seems like it would give me the overall prestige factor, right? But I get the impression that UCSD is better for CS and might give me a better overall CS education....

Is one location (La Jolla/San Diego VS Westwood/Santa Monica/LA) better in your mind...?

A final option is to reapply again this year, because I am so torn, and because I really did not do the best job at 1.pinpointing what it is I want to study, and 2. searching for faculty members who are doing that kind of research... I put together an application that was not my best (after doing internships at Harvard, MIT, and now NASA), so I also wonder if I might have a shot at a higher ranked program (I know this is superficial, but it's that what-if that bothers me).

Anyway, thanks again for your thoughts.

If you're really not sure what you're interested in, I'd consider a few things:

- How interesting do you find the general faculty at each school? (e.g. which school is better if you want to switch advisors)

- Which advisor is most (or at all) amenable to "letting" you switch, if that's what you want? While no advisor can stop you outright, some can probably make it painful. (Sounds like UCSD has the edge here).

- Which advisor is most open to interdisciplinary collaborations? (e.g. what anacron mentioned) Do they expect you to come in and work on a big project, or are they open to something new? You can try to figure this out via email, if you're careful.

- What are common student outcomes for each advisor? How well are students placed, and how well are they doing?

Depending on your answers to these questions, it may be better to reapply, although UCLA and UCSD are both good schools. If you reapply, will you be getting any new (e.g. better) letters of recommendation this time around? Rec letters are often the determining factor, especially at top schools.

And I think the difference in prestige between UCLA and UCSD is pretty much a non-issue. While I've never lived in LA or San Diego, I'd probably lean toward San Diego (better weather, less traffic/sprawl, more laid back).

[Artificial Intelligence or High Performance Computing?]

HPC sounds more useful/employable, but also more frustrating/boring.

If something sounds boring, don't study it for your PhD

And AI can be very practical. Just ask the ML people.

Even if I have an adviser at each school in each field who wants to work with me... ? Just don't know how easy it is to change advisers, or how expected.

Also, if you don't mine my asking, if you had to choose between UCLA and UCSD, which would you pick...?

I'd probably choose UCSD. But this should be a very personal decision, based primarily upon advisor fit. How well do you like the potential advisors at each school? How well does the research they do fit your interests?

[Seeking advice on transition to CS PhD program]

I think the CS GRE subject test would help significantly - especially without a background in Computer Science (i.e. having majored in it). From all the various admissions FAQs I've read, you sound like the exact sort of applicant who would benefit most from taking it. I did see a forum post somewhere on the internet with preparation advice so will try and track that down later.

I can't comment on the rest of your application but it sounds like you're driven enough. Since you already have a steady source of income and you're determined to go to graduate school, take some time (as long as necessary) to prepare your application (and in particular to prepare for the CS GRE) so that it's as strong as possible when you do apply. (I think that most people can strengthen their applications enough to get in to most places, it's just a question of will, time and money, the last two of which are luxuries which most students don't often have.)

I agree. I almost never suggest that anyone take the CS GRE, but OP sounds like exactly the sort of applicant who might benefit from doing so (assuming a good performance).

I'm not going to ask what you think my chances are (I can only read "slim to none" so many times without it getting depressing), but I would appreciate any advice on how I can make this work.

Can you get in touch with your old CS professors? Letters of recommendation are the most important part of any PhD application. So if you want to get in to a good program, you should make your subgoal: "Get really good recs from one or two CS professors."

Of couse achieving this isn't easy. Is there some way to leverage your background in law? If you can find a law-related area of CS research, some (good/well-known) professors might be interested in taking you on as an RA. You can work for them as long as it takes to get a good rec (a year, maybe). Even if you have no intention of continuing research in that area, it might be a good way to bootstrap an application.

Your psychology research should also help a little bit, and you should try to get another letter from whoever you worked for. I don't think this sort of rec will greatly influence an admission committee, but it's still a great deal better than the "did well in class" recs that they see all the time.

Some of what I've said seems to conflict with your current plan. In particular, I wouldn't tie myself down to any particular region by buying property. You might also consider increasing your ambitions. There's no reason you can't go to a school like MIT/Stanford if you play your cards right. For instance, if you can find an MIT prof who's interested in having a lawyer as an RA (which doesn't really sound so absurd), that rec letter can turn into gold...

Hope this is somewhat useful.

[Chances of being admitted to MIT, Berkeley, Harvard, Stanford, Princeton, Yale, Columbia, Caltech for a PhD in CS]

I thought MIT doesn't require GRE for EECS. If so, your post may not be the best example of how GRE scores affect admissions.

You're right: MIT isn't a good example, but GREs don't matter (particularly at top schools). Just don't fail them.

What you should worry about, in order of importance: recommendations, research experience, publications, grades, GRE. (This is possibly on an exponential scale.)

[Determining Rankings]

TT at a highly regarded PhD granting institution?

If so, cool. That's a rarity/nearly impossible in the rest of the science/engineering fields.

Yes. Although CS is gradually moving toward a more post-doc centric system, TT after grad school is still a fairly common career path. None of my advisors/mentors have done post-docs, and I don't get the impression that they expect me to do one either (speaking way too soon, but if I were to go into academia...).

[Academic Opinion of Singularity Institute]

I don't know how the singularity institute is viewed inside academia, but I would be hesitant to invest much time there, given to the lack of PhD researchers among their faculty:

http://singinst.org/research/residentfaculty

I'm sure the institute does good work (probably?), but graduate admissions committees typically want letters from people who hold a doctorate.

[Determining Rankings]

Also keep in mind that if you're going into academia,, you'll be doing one or more post-docs, and the "ranking" of those is much more important than where you got your PhD.

Maybe. But if you are working in computer science, it's not uncommon to get a tenure-track position straight out of grad school.

[Advice needed for a 3.0 junior at a UC]

I agree with newms, although that UTEP admissions estimator is garbage. Want a good predictor? Ask professors where they think you will get in.

And do research. It will give you a sense of whether you actually want to go to grad school (extra important for a PhD). Even better, it will likely get you some decent LOR, which are (IMO) the most important part of your application. If you find that you like research, and you want to optimize your grad school chances, you might even consider spending an extra year at undergrad. One year is often not enough to get anything interesting done, or to publish.

On the grade issue:

[Best preparation for CS PHD programs]

So, what is the best option? Either, I can go for a masters in Computer Science (which I don't want to do unless it is fully funded). Also, I don't know of any fully funded programs that are decent. I can spend a year and take undergrad CS classes and (hopefully) get some research experience and good letters of rec. Or, I can work. I feel like working would be kind of pointless in strengthening my resume.

I would take an another year and do CS research, maybe taking a few classes on the side. I've come to believe that LOR are the most important part of your application. Get good ones, and you are set. Generally speaking, the best way to get useful letters is to do great research.

You might also consider working for a bit, if your job is "researchy" enough and you are working under a current CS PhD. But if your goal is to get into the best grad school possible, I'd be skeptical of this option.

[Evolutionary Computing or Computational Creativity]

Would I be better off talking about other areas of focus in a SoP and if I'm really interested in the work, using some GA/Evo stuff as a tool if it's applicable to a certain problem?

That would be my advice. I've done a bit of work in the area myself, and I've found that when I talk about it, people tend to react with suspicion. For whatever reason, the subfield seems to have (a bit unfairly) attracted an oddball reputation.

For instance, upon hearing that I'd done some work with GAs, one professor launched into stories about a "crazy" EvComp zealot the department had a while back. So YMMV, but I'd tread a bit cautiously if you are not sure that GA/Evo stuff is what you want to do.

[Evolutionary Computing or Computational Creativity]

So I'm trying to find programs/professors doing working in evolutionary computing/genetic algorithms or computational creativity but I haven't found too much work done on either of these topics recently. Is this type of research out of fashion? Should I be using different terms when looking for this type of work?

Generally speaking, I do think this kind of research has gone a bit "out of fashion."

That said, some people still work in the area. A few places you might find reasonable leads are GECCO (the conference), UNM, and the Santa Fe Institute.

[To blog or not to blog?]

Go for it. I have a blog, and it's only ever helped me. I don't think it really factors much into the application process, but the one comment I got about mine from a PI was very positive.

Also, blogs are fun if you like writing ;-)

[Now that you've been accepted/rejected.......]

When applying, I didn't particularly care about the GRE. I didn't study for it, and my scores were mediocre. I got in at all my top choices.

If I had to do things all over again, I would care even less about the GRE (although arguably that's not possible). I've come to believe that letters of recommendation make or break most applications.

That said, I'm in Computer Science, and your field may be different.

[Two great schools - where to go?]

You sound as though you really want to choose School A. If that's true, then you should go there ;-)

I do think rankings matter, but between two top ten schools, they seem to matter quite a bit less.

[How much is our professional worth tied to our admissions?]

If an applicant with Ivy degree, multiple publications, work experience gets rejected by a lot of schools and an applicant with none of those things gets accepted by a lot of programs, how much does the mere acceptance or rejection reconstruct their market value?

For example, every time you apply for credit and get turned down, it hurts your overall credit score. Is reputational harm from grad rejections aking to that? Better not to apply at all, than to apply and be rejected?

Or is the applicant not harmed by a lot of rejections?

I can't see any "market value" downside to getting rejected. No one has to know about it unless you tell them. Now, if you are wondering about how rejection affects your chances of reapplication to some of the same places -- well, that I don't know.

On the other hand, I've already used my acceptance letters to enhance my credibility in certain "marketable" respects, unrelated to grad school. So really, I only see an upside.

[Stanford vs. Berkeley, CS MS]

If you have to spend money either way, and you are interested in entrepreneurship/startups, I'd say go with Stanford.

I agree its possible (probable?) that MSCS students may be treated as second class citizens in certain respects (e.g. no "offices" in Gates), and that you may have a harder time getting research opportunities with faculty. But if you are interested in startups, these things shouldn't be your primary concern ;-)

Good luck with the decision.

[Stanford University]

Hi all. I'm also going to Stanford, for a CS PhD.

I'll probably apply for housing in Munger, Escondido, and Rains.

@Kirov

When I visited the campus, none of the housing complexes seemed too far away, so I wouldn't worry about that. Then again, I'm fond of walking... so YMMV.

[So where are you going?! (Fall 2011)]

Going to Stanford. I do a mix of PL, SE, and AI.