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UMass Amherst has a student-run PhD Applicant Support Program. This program provides 1-on-1 support for underrepresented applicants, as well as a webinar which is open to all. The webinar will be held on Monday, November 23rd at 11am EST (details at the above link). Note that a number of schools are running similar programs this year, including MIT, Stanford, CMU, Brown, Cornell, Johns Hopkins, Columbia, UW, and UT Austin. Though I think UMass Amherst is the only one additionally holding a webinar that is open to all applicants. Also note that the deadline for many of the programs has already ended, but you can still apply for support from UMass Amherst students until Dec 4th. Good luck with your applications this year!

Just a heads up, but the acceptance deadline is actually May 1st according to the NSF GRFP website.

Hey! Just joined the Telegram channel... don't see anyone there.

You could compare their research rankings at csrankings.org as one indicator.

@cabbysaurus Congrats on having offers from two amazing schools! I can't compete with @pterosaur in terms of specifics about the programs, but I do have some insights regarding some of your concerns. First, I went to undergrad in the midwest and hated the cold windy climate. When it would snow, I would walk in flip flops as my way to give a giant middle finger to the weather (a few years ago I hung out with my old roommate from undergrad, where he brought up how crazy I was to walk in flip flops in the snow). I hated the climate so much, that when I got a great offer to work in Chicago, I turned it down citing how I loathe cold windy weather. Fast forward a decade, I've just survived a winter in Alaska (where it's still snow covered), and I'm moving to UMass Amherst for a PhD. That is to say, despite not liking the cold, I bet you'll be able to handle it just fine. Regarding connections to industry, Boston has plenty. Most of the major players in the field have offices in Boston in addition to their main campuses in Seattle, the Bay Area, etc. That said, you will likely have a bit more of a diversity of choices for internships in Seattle if you aren't interested in conducting research at one of the larger more well known companies. Finally, I'm of the personal opinion that I'd prefer a smaller more intimate experience than feeling like I'm just a cog in a large academic lab. I've worked in industry for a decade, and I really preferred working at smaller companies rather than in a large corporate environment. Of course, that's personal preference and I'm not sure how/if that translates to academia. Best of luck in your decision making process (if you haven't already made a decision)!

Not sure why the formatting is weird on my previous post...

Very true. I wonder if it’s also partly due to younger applicants being more of a blank slate to be molded. This article makes a similar case for Silicon Valley. Then again, when you consider the monetary investment they put into a PhD student, let alone the time, it’s understandable why they are so risk averse.

@ray92 I think there are a lot of silent waitlists going on. I just emailed a POI at GATech, and heard back that I'm on a short waitlist. Of course, that's unofficial, but it could be what's happening to a lot of people. Until I emailed, it had been radio silence from the program. I like to think of admissions as an optimization problem. Due to the explosion of applicants to CS programs, it is a non-trivial problem to optimize admissions results, such that schools get the top applicants they are capable of attracting. As the competition grows, students rightfully fear rejection, thus apply to more schools. The stronger applicants are likely accepted to many programs, essentially holding those spots hostage as they decide. Many wait until campus visit day before accepting an offer, which is often a month or more after initial acceptances are sent out. This is exacerbated by large numbers of applicants, e.g. just got back from UMass Amherst where they stated they received 2500 applicants for grad school this year. Considering these are CS schools we are talking about, hopefully they can figure out a better algorithm for acceptance/rejection that is more optimal. That will realistically only happen if it effects the quality of applicants accepted to their programs.

Thanks! No, my prior work was not heavily related to ML. I demonstrated my interests through research and familiarity with the field. To be honest though, I cannot say what aspects of my application were deciding factors. At interview time, I think it really came down to research fit with my POI as I was one of 10 interviewed, for two open slots. I will say, my application was not the strongest academically, which looks like something you may not have working against you. Best of luck!

@am_i_too_old_fr_this Wow, you could be talking about me with a statement like that :-) I was in a similar boat. I had been in industry for 10 years and worked as both an engineering lead and an engineering manager. I also realized that being a manager was not for me. I desired the intellectual stimulation of solving challenging problems. One main difference is that I do not have kids, only an extremely understanding and supportive wife. So here's what I did. I actually quit work for self-study and to dedicate time for working on machine learning projects. I did a number of projects and actually landed an interview at a top machine learning research company in SF. Unfortunately, I did not get the position, which made me realize that maybe I should get a PhD so I can have a stronger machine learning foundation. I then found a professor online (deeplearning.net) who was looking for researchers to collaborate with. I've conducted research with this professor by email since the summer. This provided me both a research paper that I was able to put on arXiv (with plans to publish in a top conference), and a LoR from a professor that was intimately familiar with my abilities. While I had contacts at top companies in SF, both a VP of Engineering and CEO of a well known public company, willing to write me a LoR, I did not feel those were appropriate for trying to get into academia, as they would have only known me as an engineering manager. My understanding is admissions committees value people who can speak to your aptitude for research. Rather, I spoke to a professor I've kept in contact with over the years since my MS and asked him to write one of my LoR. I also, received one from a former colleague who had worked her way up to a VP at a different company, but was intimately familiar with my ability to research challenging problems. In terms of where to aim, well you can see all the places I've applied in my signature line. I applied to 15 of the top programs and I've received admission to one (which I'm very please with), I've been denied by nearly half, and I am still awaiting a response from the other half (though at this point they are likely rejections). The university I was accepted to, the POI I interviewed with specifically called out that I was a non-conventional applicant. It could be that this worked against me some other universities, but this professor was willing to take a shot since we aligned very well in research goals. That is, I have a very specific set of research goals in mind, and I've been interested in that area of research for a long time, which was clear in my application. Here's how I decided where to apply. I looked at ALL the programs that were ranked in the US on csrankings.org, and evaluated each professor to see who I would be interested in working with. I kept a spreadsheet and ranked all the professors of interest on a scale of 1-4. Interestingly, just by looking at the research and publications coming out of the universities, my interests most closely aligned with the top programs... go figure. I have a suspicion that those programs have enough money, that they have the most freedom to pick research ideas without worrying about funding. I know this post is a bit scattered, but I hope it helps you in some way. If you have any specific questions I didn't answer I'd be happy to fill in the gaps. Best of luck!

It really depends on what you mean by "safe". The safest schools are likely the ones with the highest acceptance rates, which typically are not very competitive schools. The best way to pick schools, is to research them yourself. I quite literally looked at ALL the US schools on csrankings.org, which is a merit based ranking of universities by publications in top conferences. You can then select your areas of interest, and look at the various schools and their rankings. Obviously, the higher the school's ranking the more competitive the program, the harder it will be to get in. So you can go through the list a bit, and sample what the admissions requirements are for various universities. For example, Auburn which is ranked last on that list for US schools, simply wants a 3.0 GPA and > 300 combined GRE. Seems pretty safe given your profile, but it may not be ambitious enough. Looking near the middle of the list, University of Florida states the average for accepted students is 3.3 GPA and 317 combined GRE (153V/164Q). I guess my take-away is, we cannot tell you what sort of school is a safe school you would be happy with. Rather research it given the above tools and you can make an informed decision. Best of luck!

I think it all comes down to fit. Go to the visit weekends and see who you get a better vibe from. Also, if the UW professors have only recently gotten a tenure track job they may have more time to dedicate to a new student than someone who has a large lab and is well established.

Wow, UMD seems to be quite slow this year if they are sending out acceptances in three weeks... Thanks for the heads up @LHouse!

You must not have read the excellently written document from the CMU professor regarding pursuing a CS PhD that I linked to. It covers this point pretty explicitly. I would highly recommend reading it all the way through.

Apparently University of Washington received over 2100 applications! Man, the competition this year is crazy :-/