

Why grad school is hard - jlewis_st
http://office.sharingstate.com/2012/08/09/whygradschoolishard/

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dm8
There are multitude of other reasons why many students drop out of their PhD
programs. Lot of my friends started grad school with doing something
innovative and original research. But at the end of the day their advisor is
funding them and in most of the cases they were too dependent on the research
areas of their advisors rather than their own. Of course, you can choose your
advisor based on matching your research interests with theirs but things
always change due funding scenarios.

------
ten_fingers
My wife, brother, and I all got Ph.D. degrees. I was an MBA program prof.

Here's my reaction to the article and advice to people who want a technical
Ph.D. degree:

First, it helps to be 'smart' to get a Ph.D. So, in part, think of the Ph.D.
program as a path through a maze, and there don't just commit to the first
path you see. Instead, look ahead over the whole maze and possible paths,
investigate what the heck you are getting into, and then pick some candidate
paths, with 'options' along the way to respond to 'exogenous' events.

Second, what the article said was real, but some of the 'path' decisions
illustrated in that article were poor. E.g., don't get into a situation where
you are depending on an advisor: So, you don't want to have to depend on an
advisor for a problem, for funding, or for a 'research environment'.

When I was in graduate school, there as no shortage of tuition scholarships;
the school had many more such scholarships than qualified students. My wife,
brother, and I never paid even 10 cents for graduate school tuition. So,
paying $0.00 tuition should be easy enough.

I didn't get any 'stipend', but then I didn't do any teaching or 'grunt' work
either.

Third, realize that the main generic requirement for a Ph.D. is to produce "an
original contribution to knowledge worthy of publication". If you are in a
department or field that wants you to have a dozen papers published in high
end peer-reviewed journals before awarding a Ph.D., then you picked the wrong
department or field.

So pick a field and department that is reasonable about the research required.

Then maybe publish one paper just to help keep monsters off your back. I saw a
problem in a course; there was no solution in the course; I saw no solution in
the library, thought about the problem for a week and saw a rough path to a
solution, took a 'reading course' to look for a solution, within minutes after
the reading course was approved submitted my rough solution, worked for two
more weeks and found a much nicer solution, got a nice new theorem comparable
with a classic one, used the theorem to solve my problem, noticed that my
solution also solved a related problem stated but not solved in a famous
paper, and, thus, got a 'Teflon' back no one could attack. Later I published
the paper with no difficulty.

Then, get yourself ready for doing the research, pick a problem, do the work,
write it up, have the department observe that the work meets the requirements,
and graduate. If there is doubt about the quality of your work, then PUBLISH
your work.

Notice that computer science likes 'good' algorithms where a 'good' algorithm
is one with worst case running time only a polynomial in the size of the
problem. Well, usually J. Edmonds is credited with that definition of a 'good'
algorithm. So, here's a J. Edmonds story (may be true): He was a math grad
student at U MD but left and went to the Bureau of Standards (NBS). There he
published several papers on graphs, trees, flowers, etc. A committee at his
old department drove to the NBS, suggested that he stack up some of his
papers, put a staple in the UL corner, and let the department call that his
Ph.D. dissertation and award him a Ph.D.

Pick your own problem; do your own work; don't use an 'advisor' for anything
important.

Fourth, to get yourself ready for research, take some good courses, study some
good books, read some good papers, and attend some good research seminars.
There read on the lines but also sometimes between the lines. E.g., at a
research seminar, try to guess how the speaker selected their problem and
notice the prerequisites they used in getting a solution; then notice how easy
or difficult, how routine or novel, was what they did. Then consider borrowing
what seemed to work. E.g., once in grad school I went to a seminar given by S.
Eilenberg. Later a comment from a junior faculty member was "He sure doesn't
waste time working on small problems.". Okay, try to learn from something like
that.

Fifth, to pick a problem, try to start with a problem from OUTSIDE your
department and hopefully outside academics. The usual criteria for peer-
reviewed publication is work that is "new, correct, and significant". If you
are well prepared, then "correct" will be easy for you. "New" may be also. For
"significant", let that be partly or largely from the real problem and not
just from some hopeless trilogy of trying to amaze your readers, knock them
off their feet with your brilliance, and wow them with your chances for a
Nobel prize.

Sixth, quite broadly the best work in any field is to 'mathematize' the field.
Okay, basically have your Ph.D. in applied math although you may call it
mathematical sciences, systems analysis, engineering/economic systems,
statistics, mathematical finance, computer science, electronic engineering,
mathematical genetics, etc.

So, for that path, start with a good math background -- at least a good
undergraduate major in pure math, likely some selected grad courses in pure
and applied math, and some more math on your own.

For the 'original' aspect, actually good work through the math path I outlined
will have you doing enough challenging exercises so that your ability to do
'original' work will have a very good start. You might refine that start by
drawing from others, but I never did.

For the 'competitive' aspect, nearly everyone in your field will all their
careers be struggling terribly with math and be really short on it, but you
will effortlessly totally blow them out of the water. You can use theorems
they can't understand, and you can state and prove new theorems they can't
understand and where they can't check the proofs -- both easily. Did I mention
you can blow them out of the water, effortlessly? Then your research will
'mathematize' the real problem you picked and be considered good work.

Here's a big secret: The world of pure to moderately pure math is awash in
super nice tools that have not been at all well exploited in applied fields.
So, learn some such tools, pick your practical problem, make some extensions
in the tools needed by your practical problem (those extensions may be all the
challenging 'original' work you do), follow through, write any needed
software, learn TeX, type in your paper, submit it, stand for an oral exam,
graduate, and do something else.

If you want an academic career, okay, but that would extend what is here, be
chapter two, and be beyond the scope of this post!

For your 'confidence', get that from the path I outlined here and do NOT
depend on your department to give you your confidence. Don't expect to get
self-esteem, praise, acceptance, approval, a sense of belonging, emotional
security, or financial security from your department. Your main security is
that you know the math and can blow out of the water essentially all the profs
in your department.

Note: In some of the best US computer science departments, the mathematical
backgrounds and abilities of over 80% of the faculty are down in the laughable
area. Blowing them out of the water is trivial.

Notice that often departments don't want to teach or help students but want to
'filter' them. Or they want to insist that the students be like some
impossible dream in their own mind. Or they are sadistic and want to crush
students. Or they want to make sure that their students can't do better work
than they do. Or they want their students to follow the dead end path they
took and that stopped them. Looking at the faculty, you can be looking a ward
in a funny farm. Don't let them hurt you; don't let them get their rotten
hands on your program; instead, work largely independently.

If you can work through the math path I outlined, then you are plenty good
enough to do your research no matter what the faculty might say if you gave
them a chance. Try to stay out of their sights; don't let them shoot at you.

In my case, I had a good background in pure and applied math from school,
work, and independent study, selected my dissertation problem before I entered
graduate school, took some very good courses my first year (dropped some bad
ones), did my research independently in my first summer, struggled with
departmental nonsense, wrote my software, typed in my work, submitted, stood
for my oral exam, and GRADUATED.

