Goodbye to academic research

It hit 'singularity' (everything came down to a graph edge; the system is comprised of nothing else) in 2005. I've had some great advisors and the feedback is consistent, “That it’s unique is not interesting if it's not compelling. Show how it’s compelling.” So I’ve stumbled with my limited resources over the years to do that and I’ve come up with a database, of all things, but it’s actually the "programming language" masquerading as a database.

I'm thinking of offering it as a service and if you want to see where that's going, it's at http://www.kayadb.com (although it’s not meant to be looked at yet). I'll do a Tell HN when in a few weeks when it's closer to being ready to show.

Then go to the U.K. or the majority of the commonwealth. Required coursework is not a necessary part of doctoral research in many, many departments of these universities.

"Quals will still require reading deeply from the literature. You will be expected to know all the fundamentals in your computer science area to pass."

First, I saw very little that was "deep" anywhere in computer science, yes, from a career in computing and for some years as a researcher at Yorktown Heights. Yes, a proof of P versus NP would likely be be deep, but that's not in the literature.

Second, I've seen a lot in graduate academics and/or research in math, physics, engineering, and computer science, and I've never seen a graduate program where preparing for the qualifying exams really required reading the "literature", i.e., the journals, deeply or not. Instead there's plenty in the better texts.

For reading the "literature" in a field of specialization: Did I mention that the goal was research and, there, publication? The journal flatly doesn't ask that you have read all the literature in the field beyond what is crucial for your paper.

Indeed, in math, physical science, and more mature parts of engineering, what's in the texts is plenty deep. I can give you a list of texts, say, heavily from Springer, in stochastic processes and stochastic optimal control so that you could count without taking your shoes off everyone in the US who could pass a test on that content. E.g., can filter just a huge fraction of math profs and/or math grad students, likely over 99%, with just the statement, not even the proof, of the Lindeberg-Feller central limit theorem. Can filter a huge fraction of statistics profs with just the Radon-Nikodym approach to sufficient statistics as in the Halmos-Savage paper in the late 1940s. Could throw out nearly all the rest with just the Hahn decomposition approach to the Neyman-Pearson lemma. Just showing that every arrival process with stationary and independent increments is a Poisson process would stop nearly everyone. I know only one proof in print; I improved on that but couldn't pass a test on it; heck, I never committed the whole proof to memory, even when I improved it. Lesson: No one can carry the QA section of the library, even just the texts, between their ears. Can't be done.

I wrote:

"Maybe the US DoD VA would give you a grant."

and you responded:

"Often only professors can apply for the big grants, and writing a grant is actually non-trivial. They need to see a fantastic track record, a solid proven team, and often nods to diversity and educating the public. Some students will help their advisors write the grant, but in the end it's the advisor who doles out the money and is the PI."

We are both correct: Still, for some nice R&D work in human-computer interface for the handicapped, there could be a grant. Many grant sources can just give the grant and not follow the paradigm you outlined. E.g., the US DoD VA has a big hospital across the street from the big NIH campus in Bethesda, and both sides of the street would like to be seen as helping the handicapped, especially US soldiers wounded in battle. There's nothing to keep them from giving a grant.

You should understand the 'hidden agenda' behind the grant situation you described: At the beginning WWII, the US DoD ('War Department') laughed at science. By 1945 the laughing was over, and D. Eisenhower said, "Never again will US science be permitted to operate independently of the US military." Then several faucets for funding were set up: ONR, elsewhere in DoD, AEC (DoE), etc. J. Conant's intention was to have so many faucets that there would be no one place to cut them all off. Then the top US universities got "an offer they couldn't refuse": Take the grant money or cease to be a top US university.

So to the present about 60% of the budgets at the usual suspects are from grants such as you outlined. The overhead per grant is also about 60% and supports the English, history, and art history departments, the Lacrosse team, the art museum, the weekly string quartet concerts, etc.

The hidden agenda is just Eisenhower's, and in particular to have US Federal funding of the top US research universities.

The actual PIs are heavily pawns in this game: As you outlined, the research is very competitive. But as is too easy to see, the research is commonly a bit far from anyone's concerns, of Eisenhower, the DoD, the US economy, etc. So, the NSF keeps trying to make the research more 'relevant', e.g., with 'cross-cutting' programs, etc. Still, one way or another, about 60% of the budgets of the top few dozen US research universities are funded by the US Federal Government, and Congress is not about to change this.

That big old system aside, again, there is nothing to keep someone doing good work in human-computer interface for the handicapped from getting a good grant; all that's needed is just to please some one grant administrator. Just one.

"I feel the attitude of professors/academia being so easy to fool to be somewhat overstated here."

No one's being "fooled" in what I wrote. Again, in really simple terms, to define 'research', look at what's in the journals. That's nearly all the definition. For criteria for a Ph.D. dissertation, don't look for more.

"I won't go into the 'ease of publishing' comments, but my first top-tier publication took 3 years with many rejections, when I was an a non-student doing research. I also did a lot of research that was rejected and went into the 'paper graveyard'."

I have no academic aspirations, but for various strange reasons I've published a stack of papers in applied math, mathematical statistics, and computer science. Statistics and computer science? I almost took one elementary course in each, but not really! In addition my dissertation was clearly publishable. All my papers have been accepted with little or no revisions to the first journal where a submission was made except one case: As a compliment, they wanted me to rename one of my new results from a lemma to a theorem. I waited some years; the journal got a new editor; and he said that the paper was beyond what he could review. So I submitted to another journal. I stated an old theorem with a not very well known stronger version, and the reviewers wanted the original, weaker statement. Okay. Done.

How'd I do that? There is a theme that is implicit already in this thread: Independence.

Or, here's a not so good way: Diligently follow some profs around for a few years and then write something that will impress them. Generally here are close to asking for the impossible.

If crank down the 'diligence' level, this can be made to work, and here's one way: Maybe a prof, say, at Stanford or Berkeley, gets some cash from, say, Microsoft and Google, to do some things in computer and network system management. So, the prof has a dozen or so grad students and lets them go for it. The prof doesn't actually do much or any of the technical work, and the grad students are free to spread out like a dozen scared rabbits.

We should insert: In nearly every field, especially in science and engineering, what is considered the best work 'mathematizes' the field. If you are not so mathematizing, then you are at a disadvantage. But to mathematize, really need an ugrad major in pure math plus some additional topics. Since so few people in engineering and computer science have these prerequisites, for someone with the prerequisites mathematizing the field is relatively easy.

For what I did, it was heavy on independence. So, I started in pure math, and at the ugrad level that's a good thing to do. The stuff in grad pure math looked to me as hopeless; I was wrong; it's only 99 44/100% hopeless! Actually, there is some hope in there, but nearly no one can see it!

So, with independence, I followed various other directions on applied math, while getting paid for it. Did a lot with independence.

Back in grad school, I emphasized selected, advanced, high quality topics in stochastic processes and optimization. The statistics, computing, etc. around was low quality stuff I avoided.

For specific research topics, the high quality background, the selected topics, the independent approach, and usually starting with an applied problem were all crucial.

In particular, in computer science and statistics, I did 'field crossing', that is, brought some of what I knew from outside, built on it, and got results.

Flatly on the research, I never got the problem or any significant guidance from anyone else.

So, when my stuff was reviewed, it was "new, correct (usually theorems and proofs), and significant (solved a practical problem)".

To computer science students I'd say: F'get about computer science. Study math, ugrad pure math, optimization, stochastic processes, mathematical statistics, abstract algebra grad math, get some practical problems roughly in 'computing', do research, publish papers, and pick up a Ph.D. in computer science.

If all the grad students in computer science have "top-tier publications" and still no Ph.D. degrees, then change fields to something in applied math in an interdisciplinary applied math program or something in engineering.

For more, if you really want an academic career, then think carefully a little on where you can make a 'big splash' and how you can do that. But, again, I'd recommend that your work be an example of the 'mathematization' of the field.

Sorry you had problems. Many people have had problems, even very serious ones. I've seen it happen too often that a Ph.D. program causes stress, for years, and that is well known to cause depression, clinical depression, and even suicide. I've seen really good, talented, dedicated, fantastic students have their lives and themselves be ruined.

For all my points you question, my claims are rock solid.

You wrote:

"Did you try this?".

Yes, as I indicated, I did "try this", and it did work. I hold a Ph.D. in Engineering from one of the best research universities in the world. The work I did was really some applied math with theorems and proofs. I did the work as 'operations research', but it could as well be called 'computer science' or even 'electrical engineering'. The work might also fit some 'interdisciplinary' applied math programs. The Chairman of the committee that approved the work was from outside my department and a Member, US National Academy of Engineering and Editor in Chief of one of the world's best relevant journals. One of the world's best profs in operations research chided me for not publishing: I didn't want to publish it and, instead, wanted to sell it. I certainly didn't just want to give it away. I do not now nor have I ever had any academic career aspirations at all. So, I have had no desire to build a record of academic publications.

"It reads a bit like 'phd hacking'."

I don't call it 'hacking'. But, it is a play on several points. I mention two:

(1) Universities want the big deal to be research. Okay, take advantage of that or at least go along with it. Then one way to know if have some 'research' is just to publish it. In the end, once out of school, the first criterion for 'research' is that it's published.

Commonly publication is also the last criterion since, say, short of lots of citations or an actual prestigious prize, it's tough to do more evaluation. It's tough enough for the field just to review the paper; asking for department chairs, school deans, and promotion committees to do much more with the paper is a bit much.

In school, some profs try to ask for more than just 'publishable' in ways that are often cruel, irrelevant, exploitative, destructive, domineering, demeaning, insulting, sadistic, etc. So, a way, in part or in total, around such nonsense is just to publish.

(2) Another point is in engineering, if work solves an important practical problem, then that fact can be used to meet the requirement for "significant". Otherwise "significant" can be in the eye of the beholder and tough to be objective about.

With this 'hack', can work around the usual, 'expected' slog through courses, qualifying exams as a 'filter', advanced courses as more 'filters', demonstrations of 'academic devotion', sacrifice, and shedding of blood, sweat, and tears, slave labor for profs on their research projects, begging a prof for a 'dissertation topic', hoping, praying that the prof likes the work, pleasing all profs on a committee of five, etc. Good way to ruin a life. "Have to be smart to get a Ph.D.", and one way to use such smarts is to avoid slogging through that long, muddy swamp. I outlined a way.

You quoted my:

"(1) At at least some of the best US research universities, there is no coursework requirement for a Ph.D."

and wrote

"I find that to be untrue."

You can't find my statement to be "untrue"! Maybe it wasn't true at the school you went to, but that is not relevant to my claim: I didn't say that no coursework holds at every school.

To make my claim true, I need find only two schools where my coursework remark holds. Well, at one time, I knew of three top research universities in the US NE, two in the Ivy League, where official statements of the universities and/or selected departments flatly stated that there was no coursework requirement for a Ph.D. Neither was there a Master's requirement.

The part about "the best US research universities" is important: At Siawash State U., the faculty is so insecure that they will drag students through no end of hell. They can ask for over 100 credit hours of courses. It can appear they want the student two show up at the qualifying exams carrying all of the QA section of the library between their ears. The faculty research sucks, and they believe that a Ph.D. is about 'acquiring knowledge'. BS: At the top schools, a Ph.D. is about the research. Trying to carry the library around between two ears is for fools.

At the top schools, the 'coursework' a student should know is to cover basic material in the field, say, enough to teach ugrad courses. The rest of 'coursework' is to get ready for doing research. If the student has already done the research and published it, then they have proven that they are ready to do research.

Indeed, one Ivy League research university, in a department likely the best in its field in the world, has flatly stated that graduate students are expected to learn the basic material on their own, that no courses are offered for such material, and that the graduate courses are introductions to research in fields by experts in those fields. They also stated that grad students are expected to have some research underway in their first year. And they also want grad students out in three years.

A secret: At such universities, commonly graduate courses are not really 'graded'. Again, the purpose is the 'research', not the courses, credits, grades, or learning.

Did I mention that the main point was just the research?

Then how the heck to evaluate the research? There is a way, in academics essentially only one very good way: Publish it. Better? Okay, publish in a 'high quality' journal. For more? Win a prize. Maybe get asked by the NSF to be a grant reviewer. Maybe become a journal reviewer, editor, or editor in chief. Usually conference proceedings are less highly regarded. But basically, especially for grad students, just publish, and asking for additional criteria is a fool's errand for all concerned. Schools that don't realize such things should be avoided.

To be more clear, for the 'standards' of what is good research, do not look to the fantasy dreams of some dissertation committees and, instead, look at what's in the better journals.

There is more: Going back decades there are far too many horror stories about sadistic abuse of grad students. So some good universities just set up some good criteria that strongly cut out the sadistic abuse: E.g., the requirement for a dissertation can be, as I said, "an original contribution to knowledge worthy of publication". Implicit but very clear is, if the student and his advisors cannot agree, then the student can just PUBLISH the stuff. Then the faculty committee members essentially have to back down and sign off on his dissertation.

There's more: The student may have whatever 'relations' with his dissertation advisors and department. So, make the process so that the dissertation is to be approved by a committee with majority from outside the student's department and Chairman from outside the student's department. So, the student gets a fresh, maybe more objective, collection of 'reviewers'.

And, if you were a dean, what other standards and processes would you set up that could be executed effectively?

You wrote:

"Most students accepted to the best PhD programs (computer science) will already have top-tier publications before entering. It is definitely a good thing to have a publication, but rather than being finished, you will have just begun."

Maybe some such holds, but this process can't work well. It's doomed to failure. As I outlined, there just is not any chance of reasonable criteria for research quality for students other than publication in a decently good journal.

So, for a program such as you outlined, the whole thing is a fool's errand for both a student and the faculty: Bluntly, a student with "top-tier publications" has proven that they have gotten nearly everything important from a Ph.D. degree program that they could hope to get. The faculty has no more to give them. Indeed, "top-tied publications" are in practice mostly the only thing the faculty members can hope for for themselves in their own careers. Thus the student's formal education is over, done with, completed. If the school doesn't know that, then the student should go to a different school.

For what it's worth, I don't find the tech industry to be more or less meritocratic than any other -- we certainly like to pretend that our hiring methods are hyper-objective, but I've seen lots of hiring decisions that just boil down to opinion and intuition. Non-meritocratic things like pedigree and 'who you know' matter a lot, even amongst engineers.