pgbovine

Brand-new CS assistant professor hires at any research-intensive CS department (there are ~80 of these schools in the U.S.) probably come in around $100k right now (as arjun said, many salaries are public) ... now that's a 9-month salary, so if you get grants to fund your summers (which you will if you're in the groove), that's a starting of $133k annual. That's not bad, considering most of these schools are located in low-ish cost of living areas. Of course, there are no stock options, huge bonuses, and other lavish benefits of industry, but it's definitely still a financially privileged position.

both can be true. super rough approximation for CS faculty job candidate consideration: Ph.D. outside of the U.S. followed by a postdoc in U.S. at School X ~ Ph.D. in the U.S. at School X

that's actually absolutely correct :) academia is best at doing things that are not directly marketable in the capitalist economy. in the early 1900s, a group of weirdos working on theoretical quantum mechanics couldn't find marketable jobs in industry of the day, so they had to do their work in academia. thanks to them, you have your iPhone now.

... though I will concede that one legitimate source of inequality is due to larger institutions simply having more financial and material resources, so they can perform more "high-impact" sorts of research. e.g., if I'm at a small school without a $100m piece of state-of-the-art lab equipment or a staff of 20, i can't do certain kinds of research and thus can't publish certain kinds of Big Science sorts of papers as easily.

I obviously can't speak for other fields, but at least in my field, "peer review" means that the people reviewing your papers are from all kinds of academic (and sometimes industry) settings; it's not like it's just a bunch of MIT professors criticizing all submissions and discriminating based on the authors' credentials. For instance, here is a program committee that I'm on right now for a top conference in my sub-field ... you can see for yourself which institutions people come from:

http://www.educationaldatamining.org/EDM2016/committees.html

The chances of your paper being reviewed exclusively by "top credential" people (whatever that means) is astonishingly low; reviewers come from all sorts of institutions around the world. Even if someone exhibited an "elitist" opinion in discussions, they would be summarily shot down by the majority of people on the committee, who are not from top-ranked institutions. Again, N=small personal anecdotes, but in paper/grant review meetings I've sat on, I've never seen this to be an issue simply because most members are not from top-ranked institutions.

The same is true for NSF grant reviewing in the U.S.. Again, different funding agencies have different models, but the NSF is a peer-based model just like papers.

That sounds good in theory but is unlikely to yield satisfactory results since you're not on their critical path. PIs are busy people; they will turn most of their attention on grant-funded critical-path projects. It's a similar instance of this problem: http://pgbovine.net/fellowship-warnings.htm

That's 1000% correct. As someone who came from industry (Google) back to academia 3 years ago, and who has been involved in faculty hiring for the past 2 years, the odds are totally against traditional industry applicants unless they've been in a publication-oriented lab such as MSR for computer science (or unless they've won some really notable international award).

[Edit: also, the longer it's been since your Ph.D., the higher the bar implicitly is for you. so if you haven't published much since finishing your Ph.D., with each year you wait, there will be a new crop of fresh Ph.D. graduates who look more competitive on the market.]

Not commenting on this particular project, but to the general point of "just do it": very, very, very few people are autodidacts; it just happens that autodidacts frequent sites such as HN. The vast majority of learners need (ideally face-to-face) guidance to provide structure, motivation, and feedback.

I hope you print out that comment and put it in your future presentations. This is the "No wireless. Less space than a nomad. Lame." iPod moment here.

The default reaction to innovation is naysaying; sometimes the critics are right, and sometimes they're wrong. But nobody can predict the future. Keep marching forward.

you're welcome :)

http://pgbovine.net/publications.htm

this is something i try to do for all my papers, although of course people will still need to manually re-name to fit their own conventions. but at least it's better than Guo.pdf

the python case is interesting ... after all, the interpreter is just another binary executable. perhaps there's a way to write a layer above rr to "step" in Python code rather than the underlying C code. same with JS (Node.js) or any other language run-time.

a principled way to think about layering graphics and animations ... it's a bit higher level of abstraction than generating raw SVG. paper here: http://vis.stanford.edu/files/2011-D3-InfoVis.pdf

definitely! i'm generalizing the underlying API to be more generic so that people can plug in custom visualizations like those you mentioned.

Yes, recursion is an extremely challenging topic for novices. Beware of the expert blind spot, in which experts such as yourself drastically underestimate how difficult concepts are for novices to learn:

http://teaching.colostate.edu/tips/tip.cfm?tipid=181

thanks for the links!

i should do a much better job consolidating and advertising all of these resources, but time is never on my side :) so i figure that i'll just keep putting more stuff up and let google figure it out for now.

blocks-based languages were designed mainly for education, especially targeting younger users such as children. as experienced programmers, we often take it for granted how demoralizing syntax errors can be; blocks languages eliminate that giant hurdle for novices to help get them hooked on programming before they move onto traditional text-based languages.

[author here] it's not too bad, actually; i mean there's the usual hairiness of anything implemented in C, but the interpreter doesn't try to do much in terms of clever optimizations, so the code base is fairly readable for a production-grade system. check it out!

true, but big companies will usually take care of visa issues if you're hired full-time (or join as a summer intern and convert to full time). yes, it's hard to quit to join a startup; but those foreign students would've had a hard time joining a U.S. startup even without a Ph.D. due to visa issues.

As for "get[ting] trapped because of that mild ignorance", I don't buy that for CS, at least. Any competent CS Ph.D. student can instantly quit and at least QUADRUPLE their salary by getting a software engineering job. As an advisor, we have no way of "trapping" students in the Ph.D. program when they can instantly quit and make more money than we do ;) Now in other fields, the job market isn't as rosy. But I don't buy the "trapped" trope for CS Ph.D. for a minute.

As with any profession, you hear only from those with the absolute worst experiences who write on HN, Reddit, etc. (The students who are excelling are not writing rants on Reddit.) I've seen the full gamut of Ph.D.-level experiences, from the terrible to the amazing. I've also seen a large dynamic range of software engineering experiences at various companies, at both startups and large orgs. In the end, I don't have any definitive answers, but I wouldn't rule out academia if you can get yourself to be as well-positioned as possible. The same holds for industry. So yeah, I didn't add any info here! (-random dude in academia defending academia, ducks)

i enjoyed reading the book Team Geek http://www.amazon.com/Team-Geek-Software-Developers-Working/...

yep, agreed. and also the macarthur isn't nearly as much money as the usual lottery windfalls

The opposite is true. Many federal research scholarships are open only to U.S. citizens or at least permanent residents.

eugene is just THAT good. and also in the U.S., the first tenure-track position after a Ph.D. is called "assistant professor", which differs from terminology used in other countries.

oh wow i need to update that webpage ... haven't maintained this project in years :)

yep great idea. one of my pipe dreams was to combine all of those systems into one giant uber pipeline for data science ... but then i finished my Ph.D. and moved on to other things :)

wow, this is a really old project that was a two-month-long hack culminating in a workshop paper: http://www.pgbovine.net/publications/SlopPy-error-tolerant-P...

i haven't maintained the code for ~5 years, so ymmv

Agreed. Approaching someone with the question of "can you be my mentor?" is unlikely to work. These sorts of relationships often form organically throughout the process of working together on projects. So seek out projects where you can meaningfully contribute, even in small ways at first. And then show that you're the hardest working and most reliable person on the team.

It's like this: http://pgbovine.net/hacker-school-residency.htm

(I haven't updated the name retroactively yet!)

This is a topic I've thought a lot about ... here's a strawperson proposal that might incite some discussion, though it's by no means a panacea: http://pgbovine.net/undergrad-course-limits.htm