CS vs IEOR vs Statistics (which is more competitive)

[DMX]

My interest is in machine learning.

 

For some schools, this (mainly) falls under IEOR (e.g. Princeton).

For some schools, this (mainly) falls under CS (e.g. NYU, CMU).

And at other schools, this (mainly) falls under Stats (e.g. Stanford).

 

I have no real preference for which department, as long as I can work with faculty doing ML.

 

But I was interested in people's opinions as to which departments were (generally) more competitive?

 

From my perusal of the forums/departments it seems like the competitiveness of admission (in order of decreasing competitiveness) is:

 

CS (it seems like you can't even think about admission to the top 5 without publications)

IEOR

Stats.

 

Anyone care to chime in?

 

 

[efh0888]

Generally speaking, I think you are right. There are just a ton of people doing CS right now, so it's more competitive.

 

One thing to note, if you are doing an MS, your job opportunities would probably be different coming from a IEOR or Stats background vs CS. At least that's what I would think...

[33andathirdRPM]

Princeton IEOR is extremely competitive.

[efh0888]

I should note, though, when you say for CS that, "it seems like you can't even think about admission to the top 5 without publications," I believe this is really true for any quant discipline. The competition at the top is fierce; I couldn't crack the top 5 in IEOR this year, and, of course, I had no pubs.

 

ASU has a top 15-20 PhD program in IEOR, and is arguably the best program in Industrial Statistics (within IEOR), except for perhaps Georgia Tech. I got in with full funding and two good fellowships. This year there were only 15 admits with funding out of 150+ applicants. Maybe that gives some perspective, at least anecdotally?