I'm more productive when working solo than in teams. And I already have a specific research project in mind. All I needed was to plan my life so I'd have 50-60hr/week free after my bills were paid. For the past two months, I've been working on my research project diligently and without any external delays. I know I won't get a degree out of this and I doubt I can get published but since that's not my end-goal, it doesn't matter. I am looking for a hardware hacker if anyone is interested - it is a very fun/rewarding project: http://ktype.net
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.
Is it an RDBMS or a NoSQL? How can I download and use your DB?
It's hard to have new paradigm without compelling "front end" - either a powerful tool or some really simple example code.
Another thought; software development is plagued by a set of "typical problems". Another way to present a new paradigm would be to show a few problems with a discussion of how your approach would get around them.
The world is full of powerful languages. Their problem is that they give you a bigger cannon to shoot yourself in the foot with after a point.
If you want to create a truly "amazing new paradigm", show ways that you would either untangle an existing mess or ways you'd prevent that mess from happening.
From the info on your website, it looks like you are developing keyboard layouts that would be useful for people with disabilities. However, I was unable to figure out what your elevator speech for this work might be. What is your hypothesis? What evidence do you have for it? What disability(ies) are you targeting? How will new mobile keyboard help?
Lastly, this looks like a useful project for others (you're not just proving random theorems in your basement :)! Why not re-frame this in your mind as a startup? Good luck!
I'm targeting http://ktype.net/wiki/research:disabilities which prevent people from talking or using a keyboard - Stephen Hawkings of the world as well as autistic children with major speech problems. There are many existing solutions out there to help people with disabilities but there are also very wide gaps in between. I'm trying to catalog everything I can find to help fill in the gaps and I will make my own bridges if necessary.
The new keyboard is an iPad app (Demo: http://ktype.net/wiki/dev:demo ) and it will be extremely customizable. On the iPad itself, you can already define your own keys/layout: http://ktype.net/wiki/research:articles:progress_20110204
Additionally, I'm working on a vastly better auto-suggest feature: http://ktype.net/wiki/research:articles:progress_20110209 than a cellphone T9. Also, I want to make it work with a variety of hardware input devices. If you are a researcher making a brain-reading interface for paralyzed patients, don't hook it up to Windows! KType will learn from each user's patterns and will be customizable enough to support easy communication. I'm also going to integrate Twitter/email etc. soon enough - http://ktype.net/wiki/dev:roadmap
Don't get me started I can keep talking about this 24/7 :)
Im planning on quitting soon, and doing independent research while creating non-startup apps. Posts like this (and the link above) really motivate me. :)
Best of luck to ya!
* Improving communication for people with disabilities
* Creating low-cost software / hardware tools, customizable for each individual
* Providing useful research material and articles for families & friends
* Sharing case studies of actual users
"I know I won't get a degree out of this and I doubt I can get published"
Sorry to disagree! :-)!
For getting published, try some journal on human-computer interaction. Since you know much more about your field than I do, look for other journal 'varieties' as well.
For what you are doing, that is, a lot of independent, call it, R&D, if you get results anything like what you want, then it would be surprising if you didn't have something publishable. If this argument is not enough, then look at much of what does get published and conclude that much of it is not very high quality stuff!
Uh, one way to improve your paper a notch or two over what is common is just to write well, say, well organized, clear, including writing good English with good spelling, punctuation, and grammar.
Once you are published at least once, better, say, three times, sorry, but you should be able to get a Ph.D.! :-)! Maybe this is a big disappointment, but it's true!
How then to get a Ph.D? Four points:
(1) At at least some of the best US research universities, there is no coursework requirement for a Ph.D.
(2) The requirement for a dissertation is, say, "an original contribution to knowledge worthy of publication". Since you've already been there, done that, got the T-shirt, there's no question. Big, huge advantage.
(3) One more requirement would likely be the qualifying exams. These exams are to show that you are 'qualified' to move on to research and do research. But, uh, did I mention that you've already been there, done that, got the T-shirt? The difficulty of the qualifying exams varies widely, but generally the 'polish on your halo' can be important in deciding who passes.
So, it can be good to have some high quality halo polish; here are three: (A) Some of the best halo polish is published papers, the more papers, more highly regarded, the better the polish. (B) More halo polish is when it looks like you might be a successful entrepreneur who gets good publicity for the university and, maybe later on, is, uh, 'thankful and generous'! (C) More good polish is that you actually did this work, conceived it, took it on, got it done, independently, which means you are promising as a good researcher for the future bringing more good publicity to the university.
(4) There may be a requirement for 'residency' for a year. This can mean that maybe you show up on campus some day in September and again in the spring to defend your dissertation which you submit by taking a stack of your published papers and putting a big staple in the UL corner.
You should pick the university and department carefully. You might try, say, the bio-engineering program at Johns Hopkins. I would focus on such higher end engineering programs with 'biology' contact. Of course try MIT and Cal Tech. Don't settle for Southern Sawgrass U.
You may be able to get a research grant, before, during, or after your Ph.D. program: At your university, ask the people who know about grant sources. Maybe the US DoD VA would give you a grant. A research grant is the 'magic bullet' to rapid progress in academics because you are bringing money to the university! You will understand better when you see what fraction of the money the university keeps for 'overhead'! Did I hear someone say, "Money talks."?
Uh, one way to pick a department and prof: Pick your journal carefully! That is, if you want to get into program A with full prof P editor of relevant journal X, then submit your paper to journal X and, if it is accepted, then, uh, take 'advantage' of this contact you made with prof P to get your Ph.D. Note: It can be possible for prof P to 'direct' your dissertation at a school not his.
Uh, once your paper is accepted, prof P may invite you to present your paper at his conference on Computer-Human Interaction or some such. Likely accept! Then that's two bullets on your CV.
Note: When you submit your paper, likely you do not have to give any significant biographical information at all. So, you don't need a high school transcript! In particular, it doesn't have to be clear if you have a Ph.D. or not. So, before your Ph.D., you are fully 'qualified' to submit a paper.
Note: Commonly a journal plays pocket pool with your paper for a year before sending you results of reviews. So, two rejections and one acceptance would take three years. Bummer.
So, to speed up the process, go online, find maybe 50 appropriate journals, to the editor in chief of each, via e-mail or on paper, write a nice, one page letter outlining your paper and asking "might your journal be interested?", enclose a copy of your paper, and, then, only from the responses make a 'formal submission'.
Uh, the research universities make a big, huge deal out of 'research' both for the faculty and for at least the Ph.D. students. Else they'd have to know something about the real world and teach it, right? Horrors!
Uh, the research universities long since concluded that by a wide margin the most difficult part of a Ph.D. and the usual point of failure is just the research for the dissertation. For some students, that work is hard enough to threaten their life (literally). For others, it's put their feet up for an afternoon, think up some good stuff, write it up, send it in, get it accepted for publication, and shout "Done!".
In my opinion, you've already passed the main obstacle: You've decided to do some independent work.
For more, you've picked a problem, have some productive lines of attack, and are making progress.
For more, if you get the research results you have in mind, then you will have something "new, correct, and significant": "New"? No doubt what you are working on does not yet exist. "Correct"? It works! "Significant"? Ask Hawking or many people and/or groups working with the handicapped. E.g., ask the US DoD VA.
You can do something cute here: You satisfy "significant" because you solve a practical problem and not because you have a theorem or counterexample that settles some old conjecture about differential cohomology that only six people in the world know about. Readers listen up: This example makes a useful, general point!
Presto: "New, correct, and significant" are the usual criteria for publication!
That is, you've already given up on taking a problem from a prof, pleasing a prof, caring mostly about what will please a prof, looking for praise, approval, status, prestige, guidance, 'mentoring' from a prof, etc.
But, but, but, your work would never get venture funding, right? Wrong! One of the 'themes' Brad Feld likes to pursue is human-computer interaction, especially without a traditional keyboard! Uh, if you had Hawking, the DoD VA, and some organization for the handicapped on your side, had some beta testers, ..., then you might get a venture capital check -- it's not hopeless.
Sorry to disagree with your:
"I know I won't get a degree out of this and I doubt I can get published". :-)!
There's an old quote: "Be wise; generalize.".
Okay: How I got a Ph.D.: I started with a practical problem I'd identified and worked on before grad school. I saw a solution intuitively. In my first year in grad school, I took some advanced math that let me turn my intuitive stuff into some solid theorems and proofs for a solution, and in my first summer independently I did that. That work was all but the software and typing for my dissertation.
For some interim 'halo polish', I saw a problem, thought for a few evenings, roughly saw a solution, and then signed up for a 'reading course' on that problem. I worked for a few more days and saw a much nicer solution, wrote it up, turned it in, and was done with the reading course in two weeks. The work looked publishable and was -- I published it later. So, in two weeks I'd created "an original contribution to knowledge worthy of publication", that is, satisfied the requirement for a dissertation. Good halo polish.
A student who does such independent work is "difficult", but on this point read the recent Fred Wilson blog at his AVC.COM.
You will not be the first to do some independent work and later get a Ph.D. for it. Uh, one of the biggest topics now in computer science is a 'good' algorithm as in the set of algorithms P as in the question P versus NP. Well, likely and apparently the formulator of a 'good' algorithm was Jack Edmonds. Can get a start on him at
Yes, he also won a von Neumann prize, etc. Little things like that!
As at Wikipedia, he was at University of Maryland (UM). Uh, as I heard the story, he was not a happy Ph.D. student at UM so left to the National Bureau of Standards (NBS) about 40 miles away. Then he published some good work in graph theory. Finally some of the math faculty at UM, feeling a little guilty, drove to NBS, smoked a peace pipe, and said essentially "Put a staple in the UL corner of your papers and we'll be pleased to call it a Ph.D. dissertation in our department.".
Final point: Of course, D. Knuth knows about academics. Well buried in 'The TeXBook' is:
"The traditional way is to put off all creative aspects until the last part of graduate school. For seventeen or more years, a student is taught 'examsmanship', then suddenly after passing enough exams in graduate school he's told to do something original."
Yes, there very much is a conflict here: The approach to getting into grad school can strongly conflict with the approach to writing a dissertation.
"(1) At at least some of the best US research universities, there is no coursework requirement for a Ph.D."
* I find that to be untrue. In my case, I had a M.S. before applying, and still had to take nearly 2 years of required coursework. It depends on the program, but I have not heard of any U.S. program that will accept a B.S. and not have required classes.
"(2) The requirement for a dissertation is, say, "an original contribution to knowledge worthy of publication". Since you've already been there, done that, got the T-shirt, there's no question. Big, huge advantage."
* 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.
"(3) One more requirement would likely be the qualifying exams. These exams are to show that you are 'qualified' to move on to research and do research. But, uh, did I mention that you've already been there, done that, got the T-shirt?"
* 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. Having published is irrelevant here.
"Maybe the US DoD VA would give you a grant."
* 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.
I feel the attitude of professors/academia being so easy to fool to be somewhat overstated here. 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". After doing it a few times, publishing is significantly easier since you will better know the methodology, literature, and how to write academically. I'm not trying to be discouraging, but I find the above comment to be optimistic but a bit exaggerated.
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.
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.
"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:
"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?
"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.
"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.
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.
I think it would be clear what they were even without the extra indication -- perhaps personal preference, though.
(This is not to belittle the content you've got -- really interesting stuff, pretty well backed up. awesome.)
Writing politically incorrect comments can cause a lot of high emotions that can ruin the content. Somehow some signal is needed to 'qualify' the content as, say, "not in the usual academic style"! Looks like I need a better signal.
I got a PhD from Cambridge. Everyone I worked with was helpful to a fault. Everyone shared credit when it was due, and declined offers of credit when they felt they hadn't contributed enough.
I got my PhD, got a 3 year post-doc, changed fields into another 3 year post-doc, then got head-hunted into industry.
My experience of academia couldn't be more different from the one described here.
There's a story told of an elderly gentleman sitting sunning himself outside the city gates when a traveller came by. "What are people like here?" asked the traveller. "What were they like where you came from?" asked the elderly gentleman. Then no matter what the answer, he'd always say: "You'll find people here pretty much the same."
I'm not saying that this individual didn't have bad experiences, I'm not saying he deserved them, I'm not saying academia is all roses, and I'm not saying manipulative sociopaths don't exist. They do.
But my personal experience is different.
I've written about it here: http://gilest.ro/2010/what-has-changed-in-science-and-what-m...
Actually, the opposite is true, at least in the United States. Many more Biological Science PhDs are granted relative to mathematics, but there is also a lot more funding in the life sciences relative to mathematics.
The mathematics job market is more similar to the notorious humanities market than to the life sciences.
I don't know anything about the social sciences. In physics, I know that postdocs are absolutely necessary and expected, to the same degree that they are in the life sciences.
Mathematics is a little different. There are a very small minority of prodigy-types that go right from graduate school to the tenure track. However, post-doc's are still the norm, although they don't go by the name 'postdoc.' Usually they are pronounced 'visiting assistant professor' or 'instructor.'
Here's an example of a 'postdoc' in mathematics. All of the big universities have them:
The other thing that occurred to me when I read this, was that he's constructed a false dichotomy for himself: work in a world-class place, which is probably indeed much like being an olympic athlete, or work in an absolutely rubbish place, which can't really support your research. Anything missing in the middle??
I can believe that the 'hard' sciences are roughly like he says, at least at many places. It's common for there to be a sort of "lab" mentality, with a lot of grad-student cogs in a famous-professor-lab machine, and credit tends to go to the head of the lab (especially if the paper has 50 authors or something, as is common in some areas). Partly that's because it takes a lot of money to set up a physics/chem/bio lab, and there is a lot of grunt-work to be done.
That's less common in CS, I think. Not inexistent, but you can find a research group that isn't like that. It's even less common in the humanities, but then you have a whole different set of problems (less money, fewer jobs).
I also spent half the article thinking that the author's struggles with vocabulary and grammar might explain his/her struggles to get ahead. Perhaps he/she is a non-native speaker and that's adding to the trouble?
Indeed, the production of PhDs has far outstripped demand for university lecturers. In a recent book, Andrew Hacker and Claudia Dreifus, an academic and a journalist, report that America produced more than 100,000 doctoral degrees between 2005 and 2009. In the same period there were just 16,000 new professorships. Using PhD students to do much of the undergraduate teaching cuts the number of full-time jobs.
I also noticed the many grammatical flaws in this post. I did a little digging, and the author does indeed appear to be a non-native speaker. (He's Italian: http://wiki.devicerandom.org/Who_am_I.)
I think most scientific progress happens in spite of the academic system, and not because of it. In some ways the old system of patronage was superior -- you had a direct connection between a king or wealthy merchant who had an interest in something, and the scientists who needed funding to investigate it, instead of a vast bureaucracy that probably consumes more than the total amount it exists to allocate.
1. The purpose of a Ph.D. is to become a pre-eminent expert in a field. It's not to get a piece of paper. If you're not working on a career that will make you an expert, you'll be disappointed with your options after you have achieved your doctorate.
2. Find the interesting problems that people are afraid to work on and work on them very hard.
3. Use lots of techniques and approach your problems from many sides. Often something cool will shake out of the mix, and it won't have been in your research proposal.
4. If you aren't self-motivated, it's not right for you. If you don't enjoy the work, take your masters and go do something you enjoy.
5. Prepare your life for long hours and low pay with lots of frustration. Research doesn't proceed easily from point to point and it's all about being around when you accidentally make a breakthrough.
I'm sure I'm about 90% wrong, but perhaps less wrong than the naive, "Ph.D. is a way to stay in school and not have to face the real world" point of view.
A rabbit is writing into a forest.
A fox see him:
Fox: "What are you writing?"
Rabbit: "How rabbit eat Foxes"
Fox: "It is completely wrong! You deserve I eat you now!"
Rabbit: "Please, just go see my supervisor before. He's in this cave."
The Fox enter into the cave and never go out. The rabbit continue to write.
The same occurs with a wolf. And a bit latter with a bear. Except the bear cannot enter into the cave. Then a Lion go out and kill the bear.
Conclusion. No matter if you are good or not. No matter the subject of your thesis. Only matter who's your supervisor.
PG has a Ph.D; he did fine (yay anecdote). In my various internships around tech companies, there were plenty of senior coders who had Ph.Ds. And if you have a Ph.D in a relevant niche, you're probably going to be headhunted and well sought after. Where else does Wall Street or Google hire top machine learning specialists?
Now a Ph.D in sociology on the other hand... where do you go from there?
Also actually doing science in sociology is tough because have to be so careful about problem formulation, controls, spurious correlations, sampling, measures (reliability and validity).
So, for any solid quantitative work on marketing, ad targeting, public relations, public opinion polling, social program design and evaluation, organizational design and evaluation (i.e., high end HR) a good sociology background is about the best.
As I recall, P&G knows this, but I don't know how many others know it!
There are a lot of good science minded people, and there are a lot of good, driven self-promoters. Most successful scientists you encounter (apart from the odd genius) belong in the intersection between groups.
Sure, if you come up with something miraculous, then it markets itself. But otherwise you have to make sure that the right group of people knows about it or your idea will just fade away.
This writing seems about right (except that I didn't experience that much bad collaboration/competition though, even if I know it exists) to me, a second year Ph.D student in AI applied to RTS games. I don't really like that you have to work 24/7 to not be left behind, and I don't work that much indeed. Life is too short to have yours dictated by the actions of others. If you want to stop at 50hours/week while doing research, just try and make it so (focus your topic and focus on your advantages). But I'm happy pursuing a Ph.D. I don't have a fixed mindset/idea of what I would like to do next though: a startup? Working at a big firm? Seeking tenure? All options will be considered, but right now: I enjoy being paid (not much, particularly compared to my Masters prom comrades) to work on interesting topics and sometimes teach guys at the University about one of my passions (CS), with a great advisor (I picked him socially great and scientifically sharp, the mid-low h-index and the beard are byproducts), and so much intelligent people all around.
The reason you find a lot of passionate people in academia, I think, has a large part to do with the PhD process. The monetary compensation isn't great for highly skilled labor, so the only way you'll be able to get through 5+ years of it is if you think it's the most fun thing you can be doing (or at least you think that for some large-ish fraction of the process).
 For hard numbers, I found this site, suggesting a professor in Italy has a real income about 2/3 that of a US professor: http://www.worldsalaries.org/professor.shtml
Cambridge is way more boring and depressing than Pisa.
What about the third option: get your PhD and work in industry? I keep coming across statistics and CS PhDs who now work for Twitter, the New York Times, and industry research labs (AT&T, Microsoft). Why isn't an industry job a viable option?
Because (speaking as one of those people), a PhD is total overkill for nearly all industry jobs, and it costs a lot more to get one. It also probably works against you in most parts of the tech industry, where there's a surprising amount of blind opposition to anyone with a doctorate.
Finally, remember people with PhDs who work in industry have made a difficult, conscious decision to abandon the academic life. It's not the expected outcome, and there's an intense cultural pressure not to leave the ivory tower.
I didn't encounter any doctorate-opposition per se. I think it's more opportunity cost issue.
Tech industry is quite meritocratic. Problem for many people with PhDs is that this is the only thing they can show after many years spent hidden in academia, working on esoteric things.
If you keep up your real world skills during graduate school, I believe nobody is going to hold your degree against you.
At least that was my experience (and experience of my classmates from graduate school).
We did a lot of nitty-gritty software engineering during graduate school (ideas from our papers had to be implemented and integrated into bigger projects, that's how funding pipeline worked).
Also it helps not to act smug about your degree - industry is full of very smart people who didn't even go to university.
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.
Fully agree with what you said - there is a lot of sampling bias because of relative rarity of PhDs (few bad apples can completely color expectations).
It was quite a surprise for me when doing a summer program at major US corporation and everybody was going gaga because our group had many PhDs.
In academia, everybody has doctorate, so degree in itself doesn't really confer any additional signal.
In industry, people take it as a signal even when it is not (person matters more than degree, the same person would be hireable / not-hireable whether having or not having degree).
But anyways, you wouldn't want to work at places / for people which can't / don't take such things into account.
That's why I mentioned meritocracy - it's nicer to work at places where it matters only if you can get the job done, not your degree / pedigree / who-you-know.
But yeah, human nature, hard to fight against, we all like signaling (it's useful heuristics after all).
The world isn't fair. This is true whether you're in academia or industry, and accepting this fact isn't a bad thing, nor does it mean you've given in to the dark side. As retube points out, if you don't play the game you're conceding before you even start.
Start PhD: 24
Meet girl: 25
Get engaged: 27
Submit thesis: 27
Get 6 figure salary working for Mozilla: 28
Am now: 29
The only reason I can, is because I really didn't spend that much time actually working during the whole period and spent a lot of time learning to surf and play tennis well.
I really feel like I learned a lot of valuable lessons from learning to play tennis and to surf. I'm really glad my PhD afforded me time and money to make that possible.
New thought: academia isn't broken, there are just too many people who want to be academics. What do people think?
I think it's really a wasted opportunity that so many are ready and willing to devote their lives to research and we can't make the economics work for it.
Not too much of a new thought, the recent Economist article  on academic made a similar assertion.
There is definitely a problem with an oversupply of PhDs relative to the job market for physics (and likely biology). For a position at say Berkeley for a biology faculty position there used to be approx. 600 applicants per position. For physics at first tier or second tier institutions the number may drop to 200. Even if we are cruel and suggest that half of those are unqualified, that still leaves a large pool of extraordinarily qualified people competing for a rather small pool of jobs. I see this regularly when there are young postdocs with good publication records (Nature, PRL, etc.) who are having trouble finding permanent positions after their postdocs. Part of this may be related to decreased state funding and hiring freezes (in several states, there have been furloughs). Even for postdocs who have decided that they would prefer to work at an undergraduate institution and teach, the competition is fierce. Oddly, even for those that want to teach at a public high school, it's hard because of the education requirements (you can run a facility, teach freshmen at an elite college--but teaching high school seniors....). Things are so fierce that it's rather hard to have much selectivity about geography. This can wreak havoc with relationships and in physics is known as the two body problem--where a couple in science has difficulty finding positions in the same zipcode. As one colleague told me, she'd be happy to just have the same timezone....
For my subfield, industrial research positions have been gradually drying up (at least for doing physics rather than engineering). A number of companies in the past were able to use monopoly profits to drive research (think of AT&T Bell Labs which is now but a shadow of it's former self--when I was there as an intern, it was amazing....). However, many have scaled back. Thus, I have seen a number of people pursuing various exit strategies.
During the internet boom (where I had decided to drop computer engineering as a major because physics was more fun), a number of people who could code dropped out an joined startups. Later, people from Ivy institutions joined consulting firms such as McKinsey (with a "mini-MBA"). Later, a number joined in the gold rush of financial engineering. While that continues, many go through a brief masters first to get their foot in the door. A few turn to more engineering related work. So, while the unemployment rate for physics PhDs is low--not so many are actually still doing physics research.
For myself, I'll take on undergraduate and high school interns. No graduate students. I really respect String Theorists who for years intentionally limited the number of students they would accept due to the paucity of permanent positions. For years, I'd been reluctant to take on a postdoc due to the current situation. Now, I've taken on my first postdoc and will do my best by him--but I have to be honest about the job market and I'm having him learn some programming as a plan B. Plan C is that I'm very confident that he'll be able to get a position in his home country afterwards.
I've seen some people who are bitter (think of the opportunity costs!) when they leave. But, I've seen some who are mellow--"At least I got to work with something beautiful for awhile....".Part of the difficulty is that for scientists, you don't go into it for the money (at least I hope you don't!), you go into it for love. So, doing science becomes not just a job, but rather a calling and a way of life. So, someone's sense of self may often become tied to being a scientist--and that's hard to leave behind...
So to summarize, while all fields of science are not cutthroat, given the level of competition, it is very hard to find a job. Also, given the level, then people have to work extremely hard and it takes a toll on people's personal lives (it's hard to have one when average work weeks extend to 60-80 hrs for a number of experimentalists--my solution has been to sleep less, but I'm told that's unhealthy...).
> but how credible is he as a source if he can't even pass his quals?
On an unrelated note, I find it mildly interesting you say it was your "fault" that you weren't cut out for academic research.
It seems like the goal might have been to put academia on notice so _it_ could determine whether or not it cares about the problem enough to solve it.