Liberal Arts Professors on Attending Grad School--Is it the same in Comp Sci?
swarthmore.edu
swarthmore.edu
Again, I don't know if the "academia uber alles" attitude pervades CS. But, suppose it's common. Imagine how that will make you feel if you want to go work in something so undignified as consumer internet applications. The academic attitude is really a brainfuck, UNLESS, you want to be an academic :)
I'm not sure that's unique to academia though. I've met several financial types that expect the best and brightest to go into finance, and the less smart to go off to academia. And several startup types that expect the best and brightest to go into startups, the less smart to go of off into finance or academia. And several bums that expect the best and brightest to drop out of school and play World of Warcraft all day, while the less smart spend all their time slaving away for the man.
Everybody wants to feel like they made the right choice. Hence, even if they didn't make the right choice, they assume that their choice requires superior intellectual ability. You get a lot of self-justification.
Me, I knew I would suck at academia, so I went and joined a financial software startup. Then I found I sucked at finance, so I'm founding my own startup. Maybe I suck at startups too, but it's what I want to do. If it totally fails I can become a bum and play WoW all day. ;-)
But the emotional ups and down they describe are a constant across fields. Smarter people than you will quit. The crappiest "bosses" rarely get fired. Indeed, the most important advice if you're going to go: Make sure your future boss is highly thought by their current students (after a few beers). And if they have no other students - Run, Forest! They're inexperienced in the art. Your adviser (and later, committees) has the power to crush you. Always get good reviews first.
Otherwise, it is pretty fun. You learn cool things while talking to superbright folks and you get paid for the pleasure. The key is how much independence you can carve for yourself.
In my opinion (but that's all I know), second only to startupping - grad school prepares you as an entrepreneur. You learn to test ideas, gather data, interpret results, and refine the process. It's iteration all the way through. I'd say if you don't think you're ready to startup, it's not a bad place to get your bearings.
It's better to be a cofounder of a successful startup than to be an academic.
Never, EVER go to grad school the way I did - just noticing that your four years are up, and seeing where you have to apply next, so you can keep on proving how smart you are.
Going to grad school straight out of college is almost always a mistake in any field, and it is especially a mistake in CS. Spend a couple years as a working programmer first, ideally at a small company.
One, it may change your mind - this should be embraced, not feared. And two, if you do go to grad school, you will find you have much more perspective and depth than your fellow grad students.
Since there is no such thing as CS, every field is different. Some just decrement the "C". Others are perfectly healthy.
Without question the soundest field in CS is graphics. I wish to God I had gone into graphics. Digital image synthesis is actually applied math, of course, and any area of applied math that actually has a real application will serve you well.
Unfortunately, pseudoapplied math is very common and quite worthless. So be sure to look fairly deeply into any claims of applicability. A genuine applied field, such as graphics, will have a steady flow of innovations (and innovators) into actual industrial practice. If you don't see this, something, somewhere, is wrong. Trust the nose.
Also, when you apply, don't just select schools by reputation, as if you were applying to college. Pick the actual group you want to work with, and don't be shy about contacting professors.
As for picking a supervisor vs. picking a university -- I agree with this with one very small caveat. If you don't need any supervision -- by which I mean that you've done independent research before and have a good idea of what research you're going to be doing as a graduate student -- there's really no need to pick a supervisor. My supervisor, Richard Brent, is one of the greatest people in my field in the world; but this was entirely coincidental, and in my time in Oxford I probably saw him an average of once every three or four months. I could have been at the University of Timbuktu (if there is such a place?) and received adequate supervision; the greatest benefit Oxford provided to my research was to open doors for me -- it's amazing how many people pay attention to an email which starts "I am a doctoral student at Oxford University".
One final remark about supervisors: If you're planning on applying to do a doctorate and there's a particular professor whose research interests you, you should absolutely contact them; if you're planning on applying to do a master's, please don't. There are far too many wannabes with no research experience entering master's programs to have a personal dialogue about one's research with every one of them.
I wouldn't characterize graphics as the "soundest" field. I might give that title to formal methods, where the bar for publication is often a machine-verifiable proof of correctness.
Of course, graphics is math-heavy, too. A lot of the good graphics folks I know started off as mathematical physicists.
For that matter, many sub-disciplines within CS are quite math-heavy. For my own dissertation, I developed static analyses of programs. To do so, I modeled the semantics of a programming language as a mathematical relation on machine states. I then defined new (finitely computable) relations---the analyses---and I proved these are sound simulations of the semantics relation. Plenty of math involved.
Theory folks do plenty of math on the complexity and correctness of algorithms.
Machine learning involves lots of probability and statistics.
Even the top-notch human-computer interaction people know statistics well.
I could go on. But, I think you could find a way to do some "real" math in any field within CS. (Though I've noticed each sub-discipline has its own self-aggrandizing definition of "real.")
As far as how much of the article resonated with my own experience, I would have to say not much. I had plenty of cordial debates with professors, but ultimately, we would arrive at either a theorem or a contradiction, and then the debate was ended. No feelings hurt. No ego assuaged. Just a truth uncovered.
The one part of the article that does ring true is the myopic vision of the world one receives in academia. Academia takes center stage as the noblest of all possible pursuits. The thrill of publication and peer recognition can be intoxicating, especially if you're the kind of person who is obsessed with publicly validating their own intelligence.
I'm now taking a year off from academia to work full-time for my two startups, but a part of me feels like I'm selling out by not going on to become a professor right away. My own advisor warned strenuously me to continue publishing, lest the "jealous priesthood" of academia reject my attempt to return. I know enough, though, to know that he's right. If I don't continue to publish, academia will cut me off, regardless of how might money I might make doing startups.
My parting advice to potential grad students in CS is: (1) choose a field that's growing rather than shrinking, and (2) find an advisor with whom you can develop a comfortable working relationship. After that, lots of hard work and a modicum of smarts can get you the rest of the way.
Arguably, you could get these same benefits by working at a good company like Google, but Google itself sprung out of a graduate school project. Graduate school gives people an environment to think about "crazy" ideas in depth. Google wouldn't exist if Larry and Sergey had been employees at Altavista rather than bouncing ideas off of each other at Stanford.
[1] a lot of free time compared to a startup, or even a 9-5 grind. (most jobs are 8-6 and require at least some commute)
In school you're busy 24/7: doing schoolwork, worrying about schoolwork, or procrastinating on schoolwork. At least when I was working full-time, I would leave the office at 5-ish and not worry about work for 16 hours.
As an employee you have a lot more security (worse case your perfectly steady paycheck disappears for a bit to be replaced by another, maybe smaller maybe larger steady paycheck) but most likely your performance is reviewed by a pointy-haired boss.
As a graduate student, usually you get paid a pittance (sometimes you pay for the privilege), have even more uncertainty that a startup (after 5 years or more you may be kicked out; good luck transferring your credits) and your performance is reviewed by a committee of pointy-haired bosses.
If you were to actually plug all that uncertainty into a utility maximization problem assuming a risk-averse individual, I seriously doubt it comes out as a good idea for any field, without maybe adding in a variable for "must prove myself more intelligent than the mundanes with a formal title bestowed by the intellectual aristocracy"
Of course most don't really know that going in, and the article was right; once you are on that train it's hard to get off. All of this sounds a little bitter (I used to be a bright eyed idealist; I promise!) but I'm in the midst of slogging through my dissertation and things will be much better when (if) I can finally put on my ridiculous floor length hood.
Anyone good with optimal control of vector-valued stochastic processes? Have I got a deal for you!
For the record I did my PhD in graphics, and while its a maths heavy field, so are so many others, it really depends on what kind of maths you're into.
For PhDs in the field, I've never seen a more interesting set of problems, though I'm biased. A friend is working on rhythm as related to conversation, and studies dancing robots. It doesn't get much better than that. http://beatbots.org/
The drama of a PhD is less than that of normal office politics. If you act like an adult, everything should be fine.
Here is what Monzy says about drama in the PhD for CS: http://www.monzy.com/intro/drama_lyrics.html