Let's say there are students from four backgrounds (Mathematics, Applied Mathematics, Computer Science and Statistics) all from top programs. They are applying to a machine learning PhD program at a top American university.

  1. In terms of getting in, which background is most favorable?
  2. What can the pure math student do to improve their chances of getting in?
  3. Would a double degree in any combination of the above fields be more favorable?
  • $\begingroup$ @BjørnKjos-Hanssen Sir I was thinking something like Machine Learning at MIT/Carnegie Mellon/Stanford/Berkeley. If it's good enough for them, it's probably good enough for many others too (though I know individual universities differ in research areas, I think this is too general a question for these differences to really matter?). $\endgroup$ – stranger Oct 17 '19 at 16:37
  • $\begingroup$ Can you give a couple of sample URLs of the programs in question $\endgroup$ – Bjørn Kjos-Hanssen Oct 17 '19 at 16:43
  • $\begingroup$ @BjørnKjos-Hanssen Sorry for the delay (timezone difference). I'm posting links for each program and their associated labs. $\endgroup$ – stranger Oct 18 '19 at 1:41
  • $\begingroup$ MIT program: eecs.mit.edu/academics-admissions/graduate-program Lab: CSAIL (Link is down, so posting one level up). eecs.mit.edu/research/17 $\endgroup$ – stranger Oct 18 '19 at 1:41
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    $\begingroup$ This is a question to the folks at your target universities who actually make these decisions. We cannot read their mind. $\endgroup$ – Yuval Filmus Oct 24 '19 at 10:52

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