Spaghettini Plot

Since Reed college is known for grade deflation I would think Washington statistics is possible but a reach. This is provided you score well on the Math GRE. I can't really say as far as applied math goes. Otherwise I'd say Wisconsin is also a bit of a reach but I think you should have a very good shot at OSU and a UW masters. Certainly if you are set on a PhD, I would look at some more places between OSU and Wisconsin depending on where your research interests are

I think you would still have a decent shot at some great programs. I think that in your case since you already will have a stats degree from a top American school, the math GRE may not be as essential for you as it would be for an international student who had not completed any part of their education in America. So if you do apply to Berkeley, Penn, Washington, Chicago etc. which consider it optional, I would imagine that it would not matter that much whether or not you have written the Math GRE. However, the competitiveness for applications in the fall could be tougher than usual depending on the state of the economy and pandemic by that time.

If you are planning on looking outside of the US, I would check out U of T as well. They have a few young professors doing ML research that may be interesting to you, David Duvenaud, Daniel Roy and Murat Erdogdu.

UBC has Jim Zidek who is a big name in the field, however he is listed as emeritus and probably not taking more students. Marie Auger-Méthé is a younger faculty working there doing some work on spatial stats applied to ecology. Elsewhere in Canada Dan Simpson at U of T is a pretty up and coming name in spatial stats.

Probably hard to say in general. A lot of these rankings seem to be pretty heuristic. US news just seems to capture it better than most in America but we don't have anything like that in Canada. In my opinion, based on general reputation and faculty strength etc, I would probably list the top stats programs in Canada as: 1. U of T 2. UBC 3. McGill 4. Waterloo Personally I think UBC is an excellent choice and very strong overall. However particularly in causal inference, I think that McGill is probably the strongest in Canada, but that's one sub-field. If you decide in your PhD that you would rather work on something like spatial stats or ML, then I think you would have a more options at UBC than McGill

Personally, if you are dead set on Causal Inference I think McGill would be the best fit. Otherwise I think UBC has plenty of research areas to pick from and I think that would also be an excellent choice

I don't think it is worth it to pick UNC just because of the prestige if you are not going to be funded. If you are dead set on Causal Inference then you'll plenty of options at McGill which is also a great school. I think the poll could be misleading if people answer it before knowing the options that you have to decide between

I think you'll be a strong applicant. Though you may not have a super well known undergrad, I think the GPA and research experience should make it clear you'll be able to handle a PhD program. Though nothing is guaranteed, I certainly think it would be worth it for you to at least give top programs a shot and apply. The math GRE is usually a more important metric for international students without any US degree, though I'm sure it would help your odds to get into a top program if you do well (80% + ) If you're into Bayesian Stats, you should definitely give Duke a shot, and Michigan is probably similarly hard to get into. Also there are some not currently ranked programs like UT Austin and UCSC that are quite Bayesian, and will probably be ranked next time those lists are updated.

I'd say Minnesota and Toronto are probably pretty similarly strong, and overall probably stronger than the other two. If you're looking specifically at mathematical finance, Toronto is a bit niche that they have it as an option. But just overall in terms of high-dimensional statistics/ ML they're both very good options. Additional factors may depend on where you want to end up living for 5 years or if you in fact did want to defer a year.

I think you really can't go wrong. Those are two of the best programs and either will be a fantastic choice. One thought is if you know there is one person that you absolutely want to work with at one of these schools, then go to that one. However, if that is not the case, one method to help decide is to look at which program has more professors you would potentially want to work with. I don't think that you can fully get an idea of what working with a particular professor may be like before you actually are there, and having several options is very important. Also as of late, several big companies have a tendency to poach faculty so this is another reason to make sure that you have several people you would be happy working with. One other thing to consider is the cost of living is much lower in Pittsburgh than the Bay area. You will be much more comfortable on your stipend at CMU if that is an issue. As for the main issue you are struggling with, I wouldn't worry too much about Berkeley being consistently ranked higher, as that difference is only slight. Best of luck on your decision!

Not that any of this information is definitive, but based on my own experience at visit days and meeting others, I'd say Canada is a bit of a special case regarding international students. Other strong schools may be a bit more known than you realize, (e.g. U Vic, SFU, McMaster, Queen's, U de M Dalhousie to name a few) and there are certainly people who come straight out of undergrad from these places and get into any of the aforementioned US programs. I'd say maybe your main area to improve is to take more core grad level stats. Certainly advanced math helps but I'd think that grad level stats is certainly also looked upon similarly well. I think if you do well in a grad level math stats, and maybe measure theory probability then you'll be in really great shape, especially if you get another publication in your masters. Best of luck if you do end up applying to the US, and feel free to DM me if you have more specific questions!

I think you have a chance of some top 10 programs in the States (i.e. Stanford, UCB, Harvard, Chicago, UW, UM, Columbia, Duke, UPenn, CMU), though this depends a bit on your GRE score. But seeing as you already have your name on an ML publication and a very high GPA I think you could have probably gotten into one this year. I also think that after doing a Masters in Stats your chances will be even possibly better so you may have even more options within that tier.

It is true that computer vision is still primarily found in CS departments, but there are a few stats profs who do study it. UCLA for instance has a number of researchers https://vcla.stat.ucla.edu/people.html. There are others elsewhere who frequently work in CV such as Yali Amit at U Chicago and Zaid Harchaoui at UW.

Additionally there are schools which either have a stats PhD through their mathematics department (i.e. UCSD) or have a joint mathematics and statistics department (i.e. Boston University). These will likely either strongly recommend it or require it. In this case UCSD requires it and BU recommends it.

U Chicago also strongly recommends it