Hi everyone! I had the good fortune of being admitted into Brown University, Cornell University (College of Engineering), and the University of Washington, Seattle (Paul Allen School of CS) for my intended major of computer-science. Now, I have a really tough choice ahead of me.
Financials shouldn’t be a problem for me – however, I am in-state for UWash (and will receive in-state tuition).
I’m particularly interested in ML/AI (as of right now), and would like to do research in it as an undergrad. I’m also dead set on grad school to get my MS in CS, and that’s a big factor in my future choice.
Would love any help on this confusing decision. Thanks!
If you look at my new favorite tool - the Brown open source rankings,
UW is #6
Cornell #7
Brown #24
I’m all for Ivy prestige - but not at that price - actual $$. And while I don’t believe in ranking per se they are a nice validator - three fantastic programs. I’m sure you can find the area of CS you want at all three but you might check their curriculums and current research to be sure.
You should consider Cornell seriously from that list.
Fall back should be Brown if you don’t like the isolation of Cornell.
UW is a good choice, but will be under re-sourced in ways both large and small – you should verify that in fact the faculty student ratio (undergrad and grad students) is good for the choice that you pick. And also carefully count the number of faculty in AI.
Incidentally Brown has high median salaries for its CS grads – higher than Cornell.
But Cornell will give you a greater breadth of faculty resources to do research with in Undergrad.
This shouldn’t be a difficult decision. Even without considering the cost, you’d be better off with either UDub or Cornell (not because of some rankings). UDub is actually even stronger in ML/AI than Cornell and its CS department is very well resourced. As an in-state resident, it’s also most likely the cheapest for you, especially if you’re full pay.
Not really. You can’t just compare the medians. You must look the entire distributions. The distribution is much wider at UDub (with a much longer left tail) than at the other two schools. Students in the ML/AI subfield are likely to be in the top of the range. UDub also enjoys a geographical advantage for ML/AI jobs/internships than the other two.
I doubt the range is that large.
Consider the class at U Dub – the OOS acceptance rate is miniscule.
So most kids are in state.
Whereas Cornell draws from the national pool.
Right there you can explain the differences in median pay.
And given it is mostly a local pool at U Dub, I doubt the right wing of the distribution would be beyond the right wing of the distribution at Cornell.
It really depends on what you make of your CS education. You could go to MIT and have 0 internships, or you could go to UW and be interning at FAAMG every summer and have a excellent job lined up after graduation.
Yes, that explains the medium pay. But ML/AI students tend to come from the very top of the group (whether they’re in-state or OOS). UDub is kind of like CMU. Its CS department is in a different world from the rest of the U, and on top of that, it devotes more resources to ML/AI than most other universities on the East Coast (with the exception of CMU).
You are thinking only kids headed to grad school. There is not much happening with just an undergrad in ML/AI anyway. It is just data classification or calibrating existing models. I am also not sure the top kids head only into ML for grad school. They go to all kinds of places depending on what they are interested in – theory, programming languages, cryptography, quantum information etc. And the median salary is not relevant for kids going into grad school.
Hey everyone, thanks for the responses! What I’m understanding is that I should pick between UDub and Cornell.
Now it seems like the CS department at both schools is of a similar size. Cornell has 1000 people in its CS department (from their website), whereas UDub has ~2000 (but that’s the entire Allen School, so probably around a similar number for CS).
To answer @1NJParent, yes, I’m most likely going to be sticking with ML/AI into grad school. I’m pretty intent on studying it at a higher level (hence grad school) so my primary concern at the moment is grad-school placement over median salary.
I’m not sure how reliable csrankings is, but per them, UDub is 7th in AI and Cornell is 3rd. Probably not a huge difference, but it is there. Now what I am curious about is how much the geographic advantage UDub has will affect my ability to get internships and such in the summer.
In any event, I should probably do some more research on the curricula, grade distribution, research, etc. I’m visiting UDub on the 15th and Cornell on the 22nd, and I’ll probably make a final decision after that.
csrankings is a website that ranks colleges based on the number of publications in various subdisciplines. There’re several issues:
It doesn’t classify published papers based on their subdisciplines correctly or consistently (a faculty member may work and publish in multiple subdisciplines) and also its AI category includes some subdisciplines that are much less relevant to you.
It doesn’t adjust for the number of faculty members in each subdiscipline at each college.
It doesn’t know the quality of each published paper (without adjustment for quality, some Chinese universities would rank much higher than nearly all their American counterparts).
As most of us have said, either UDub or Cornell is a good choice. It’s great that you’ll be be able to visit both and do more research before making your final decision.
Besides their difference in costs, one thing to keep in mind is geography. I normally wouldn’t put geography high on the list when recommending schools, but in this case I would. Progresses in ML/AI are made almost daily. What you learned today may be dated (or even obsolete) tomorrow. The field will certainly look very different by the time you graduate. There’s no standard textbook. Theoreticians are born among practitioners, and practitioners become theoreticians. Unlike in any other subject that I can think of, industries play as a great role in research as academia. A student needs to keep abreast of the latest development. The greater Seattle area is one of the better places to interact with people with similar interests and hear about the latest development before it’s even published.
If headed to Wall Street, then may be. But OP hasn’t indicated an interest in a finance career. If heading to a tech firm on the west coast, the gap vs Brown is going to be significantly wider.