As a person who reads PhD applications and works with graduate students, bullshit.

I care a little about your GRE scores, it is a filter, you need some kind of standardized comparable. Congrats on getting in the 99th percentile (that's expected). I don't care much about your GPA. I might look at what classes you took. I will probably look at your reference letters briefly. They might be from professors, they might not. I don't care. I love the fact that you have some startup or industry experience, you are slightly more likely to actually know how to get things done.

The very first thing I read is your cover letter, then straight to your research statement which I will read in great detail. The only thing I care about is do you have a passion for research, are you likely to be successful at it.

At most research institutions in most areas of science, we have to pay our graduate students stipend and tuition, either right away or after a year. This is a damn good incentive to get students in who are going to do great research.

All I care about is getting great researchers in the door and (eventually, hopefully) into my lab. So, my advice: focus on your research statement. Tailor it to the department your are applying to, talk about the research they are doing there. But, have your own agenda. At least know what research areas you are passionate about.

What you are telling me is completely at odds with what others have told me (including faculty on admissions committees) so I imagine it varies from institution to institution. I had a pretty compelling application a year ago and my statement (in my opinion anyways) demonstrated that I was caught up with the academic literature on a particular topic and I had done some work myself implementing and attempting to improve existing techniques. I realized that I may not have worked on that topic in particular, but my hope was that it would demonstrate research aptitude. My application was rejected from 8 schools and I contacted several to see what the problem may have been.

The GRE point I was trying to make was that since 99th percentiles are expected, the test shouldn't exist at all as it is clearly a poor filter.

Did you have a low GPA by any chance? In academia, this is considered a black mark :(

Honestly, I think you dodged a bullet. Academia isn't that magical (CS PhD here). I think you get a better education reading Hacker News some days.

Perhaps this was the case. I did not do well the first two years. I hated school in fact and averaged a 3.3 or so (the engineering courses felt very soft and uninteresting). This changed when I discovered pure math and theoretical physics and I averaged almost a 4.0 for the last two years with the most difficult courses so I didn't think it would matter. I like engineering now, but I wished that the fundamentals were covered more rigorously as the lack of rigor made me initially very disinterested.

HAHA. As a PhD student, I agree with most of your sentiments. The PhD application process is nothing, try applying for fellowships. Go to a prestigious institution, pull allnighters, to get a subpar gpa, and have no time for volunteering activities. These are the criteria you need to satisfy to get something like NSF GRP (Broader Impact is 50% of the application). You might have a better shot at a lesser prestigious university with a not-so-great engineering program and being a super smart person, killing it. Then, apply for fellowship --> you will get it. It is all a rubric.

Now on to the game of academia. It is one that is based on reputation, papers, and not money. No one cares for efficiency either and no one is building crap. All they are doing is trying out different "solutions," which may or may not make any sense. For instance, "hey guys, let's apply game theory to problem X, it will be a good/novel experiment and we can get a paper out of it." Waste of tax dollars. The logical answer that solves problem X might have already been solved and can be solved using ordinary methods, but academia doesn't want that. Research labs have business models, keep proposing new complexity on complexities, very unnecessary. Overcrowded fields like computer vision reek of this.

Don't even get me started on funding and fellowships haha. I think trying to get funding in math must be the worst. Every formula has to boil down to "security this" or "missile navigation that."