

Liberal Arts Professors on Attending Grad School--Is it the same in Comp Sci? - vlad
http://www.swarthmore.edu/SocSci/tburke1/gradschool.html

======
robg
At least where I was (Pittsburgh), CS majors got some of the best perqs (best
pay, great toys, best hope of finding a great job). Contrast that with the
Humanities Ph.D.'s (no money, no toys, no job prospects).

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.

------
rsel
It's not as bad in CS. In English you have the problem of working on
fundamentally bogus stuff in addition to the structural problems inherent in
grad school.

------
npk
I can't say anything about CS, but in physics, these comments are spot on. The
essay points out: "A Ph.D in the humanities is useful for one thing only these
days, and that's being an academic." Ok, a phd in physics gives you more
flexibility, but while you're in grad school, your professors expect the best
and brightest to go into academia, the less smart go off and work in industry.

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 :)

~~~
nostrademons
"while you're in grad school, your professors expect the best and brightest to
go into academia, the less smart go off and work in industry"

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. ;-)

------
amichail
My advice: only consider grad school after you have completely given up on
startups.

It's better to be a cofounder of a successful startup than to be an academic.

~~~
amichail
I should add that anything graphics related is probably an exception to this
because you need quite a lot of knowledge and mathematical sophistication to
succeed in this area. A masters degree in graphics will probably help you.

~~~
mencius
Both these comments are dead on.

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.

~~~
fadmmatt
I just finished my PhD in CS at Georgia Tech, so I'll share my two cents on
the topic. (My field was programming languages and compilers.)

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.

~~~
ecuzzillo
Both you and cperciva seem to be fundamentally theory people. IMO, you both
completely missed what mencius meant when he wrote 'soundest.' When he says
sound, he means that a field is worthwhile, both because it has problems that
are interesting in a purely technical way and because solutions to them are in
some way actually useful to non-CS humanity. When you say sound, you mean
pedantically verifiable for the benefit of other theorists. Graphics is sound
because not only does it have interesting math, it aids or entertains laymen;
PL research isn't, because nobody except PL researchers cares.

------
danteembermage
I think being an employee and launching a startup are on a continuum of sorts.
With a startup you get lots of uncertainty, but lots of independence. There is
a job to do, you decide how to do it, and the market is your metric for
success, for better or worse.

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!

------
greendestiny
I did my PhD in comp sci because I absolutely loved solving CS problems and I
wanted the respect a PhD brings. Yep, that second reason is as stupid as it
sounds, but I couldn't really consider doing anything else until I'd climbed
that mountain education put in front of me. If you can't stop yourself doing a
PhD, then go ahead and do it quick. Its exactly as frustrating as this article
makes out, and CS academia is as about as crap that unqualified rant made it
sound a few days ago.

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.

------
ivankirigin
Not all programs are alike. I got a specialized masters in robotics. That
opened up a world of opportunity and allowed me to work on very interesting
problems. The space is well funded if you go to a good school, so you don't
drain your savings to attend for two years.

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>

