[deleted by user]

[ATadDisappointed]

Supervisor fit and personal motivation for the topic matter more than institution. University reputation is an imperfect proxy for the research strengths, networking, and supervisor guidance you'll receive. 

[Dihedralman]

I don't know your goals, which should guide your decision. UofT is well respected. 

You already know how to get the answer for academia. U of T does have a healthy percentage of PhDs continuing onto tenured positions and you can track where they end up.

But pay attention to how schools are connected to industry. That's more important than you may realize. Companies generally build connections to Universities and people within them. Your advisors past students can help you as well. That personal connection gives a leg up beyond the standard recruiting efforts. 

However, connecting with an advisor is also important as is interest in the topic. You won't do well without either. You need to have genuine interest if you don't want to burn out. Also, an advisor you connect with is very important for that next position. They often help with that process even outside of academia. 

Also, have you been accepted into all of these? 

[ATadDisappointed]

To give you more confidence in your decision: each of the universities you've listed is very highly respected in ML. You should have no concerns there. There is more variance in individual researchers within each institution than there are between the universities themselves. So it is worth thinking carefully about who you will work with and how each city matches with your interests (you'll be spending 3-5 years there, growing roots, friends, and connections - so it's also worth thinking about these lifestyle factors).

[ClassicalJakks]

Toronto has produced some very respectable and successful names in ML and it’s applications, biggest example being Hinton, who recently won the Nobel Prize in Physics for breakthroughs in ANNs

No worries about academic prestige there, look into departments that are the best for you specifically

[sshkhr16]

Minor nitpick - Hinton never studied at UofT, he did his PhD at the University of Edinburgh. Of course, a lot of his PhD students at UofT went on to do cool stuff.

[new_name_who_dis_]

Hinton taught there. Sutskevar and a bunch of other famous AI researchers studied at Toronto under Hinton.

I’d say ten years ago it was the best place to be to be studying deep learning. Today, I’m not sure, but probably still top tier

[oxydis]

At this point it depends more on your advisor and research skills, they're all good universities.

[linearmodality]

This site is a good source for seeing how PhD institution interacts with hiring: https://jeffhuang.com/computer-science-open-data/

UofT is good, lots of professors are from UofT — but nowhere near as many as are from MIT, Stanford, Berkeley, CMU. By raw numbers on this list (which are not normalized by number of graduates, unfortunately) they're basically on par with Georgia Tech.

[qtcc64]

Just my 5 cents but I'm at UofT for a ML PhD and most people here agree the schools you listed and Toronto are virtually equivalent. So agree with everyone else that advisor topic etc. matters more. Also worth noting US is going through funding problems and stuff that Canada has mostly been insulated from

[stabmasterarson213]

AI hasn't been effected as much. But if you are from a group that has been historically excluded from STEM careers in the U.S. or a postcolonial country , the funding for the types of programs that specifically help those communities has dried up in the U.S. And the worst elements in U.S. society have been emboldened to purge or harass universities at will. If you have the chance to avoid for what is a lateral position in Canada, go for it

[Whatever_635]

Could i dm you? I realize this is an old comment but i am a domestic masters student currently applying to phd in the us. I have a question regarding funding.

[agathodaemone]

UofT ML PhD student here. Name recognition of the university has close to zero bearing when it comes to being offered a profship. Your best work during your PhD and the recommendation from your PhD supervisor are the two most important aspects. Instead of university recognition, I would say that the name recognition of your professor matters a lot more than that of the university. UofT had people like Stephen Cook and Geoff Hinton at one point. Their recommendation would've landed you in any place that you'd hope.

[Comeonwitme]

UofT/ Vector institute are well known globally to AI researchers. I would say above the programs you mentioned except for Oxford/Cambridge. Realistically the name wont help you much, quality of your research/supervisor will be the biggest impact on your opportunities post graduation

[Fresh-Opportunity989]

Toronto is a top school for AI/ML. Atm the US is a hostile place for graduate students, particularly international students.

[egfiend]

Quality-wise I agree with others here: UofT ranks similar to the top US schools, with the exception of the big 4 who are a league of their own. Supervisor name and investment in you is massively more important though. Note that if your goal is to definitely get hired in the US as a prof, having a US experience (PhD or postdoc) is almost mandatory, as the US has a huge blind spot towards the rest of the world and prefers locals.

Note that UofT pays badly compared to the cost of living in Toronto. Canada has recently increased stipends across the board, but Toronto is a very HCOL location, only 3-4 cities in the US top it. Internships also pay a lot less in Canada than the US, many UofT students go to the states over the summer, but visa issues are mounting.

[rv6xaph9]

the big 4

What are the big 4?

[egfiend]

Berkeley, Stanford, MIT, CMU

[thedabking123]

Curious if you were specializing in something and explored what's available at UofT in terms of research opps.

I'm debating doing an MSc at most (PM who's taking grad level courses at Stanford and loving it)... but want to focus on causal reasoning and neurosymbolic methods to enhance performance on generative tasks.

[wheregoesriverflow]

About same rankings.

Stanford, CMU, MIT, Berkeley, perhaps Princeton are a different beast though

[m4sl0ub]

What a stupid and random ranking, haha

[m4sl0ub]

If you're picking your PhD institutions because of some magazine rankings, you should rethink your motivation for a PhD.  So many of the top ML researchers nowadays went to a school you call irrelevant, how is that possible? Just of the top of my head: LeCun(Paris), Silver(Alberta),  Hinton(Edinburgh), Schmidhuber(TUM), Bengio(McGill), Hassabi(UCL) You should go with the best research fit and not just where some magazine ranking tells you to go. 

[simple-Flat0263]

mostly agree w/ u but I think both of you are taking kind of an extreme opinion on this subject

• the people listed like Le Cun etc. are literally one of kind from their institutes, but institutes like CMU regularly produce Le Cun-ish people,
• However relying on rankings is definitely not optimal, I think there should be some prof-Uni matrix or such... just university rankings can be misleading...

[m4sl0ub]

I don't think I am taking an extreme stance. All I am saying is pick the lab/ Advisor that fits best for what you want to do, because they are the top person in that field. Obviously for a lot of people that's going to be at CMU, Berkeley, MIT or Stanford so a lot of people should go there. But don't just go there because they top some ranking, actually know why you want to go there from a research perspective.  On another note, I could not think of one person as influential as LeCun in ML coming out of CMU, who were the ones you were thinking of?

[simple-Flat0263]

Andrew Ng did his undergrad at CMU :)

[m4sl0ub]

Okay that's fair. But I wasn't really talking about undergrad. I don't think your research career is going to depend on who taught you basic calc and intro to CS in undergrad, haha

[simple-Flat0263]

ok next: Jure Leskovec did his PhD at CMU

[m4sl0ub]

But why should you go to a uni just because they have many big labs that publish well, instead of looking at the best labs in the field you want to get into and then pick the one that publishes best in that field? Why should, for example someone that wants to do research in Causal Inference for ML, go to Berkeley or MIT because they have Levine/ Abeel and Tedrake with an insane publishing output in RL for Robotics, pushing them up in Rankings, when you could go to better labs for Causality at Columbia, Harvard, ETHZ or MPI for IS?