Schweinchen

Ditto here. Maybe I'll see you all on visit day.

Texas A&M has had a well-known and long history in Stat but UT just started their Stat program recently. On the other hand, UT is very strong in machine learning. The caveat is that those ML faculty are all in CS and ECE, even Math, but not Stat. That graduate who went work for Jordan is likely a student of someone in CS or CSE.

I have a different take on this. If you are thinking of research leading to a publication in a conference or journal, then Bayesian1701 is right, it's way too late for this cycle. But on the other hand, if you volunteer to help the professors who are writing your letters of recommendation in their research, it gives them something to write about in their letters and it also gives you something to write about in your SOP.

That's what I thought too but great to have independent confirmation. Thank you, pal.

That's what I heard too from a pretty reliable source. But she also said that the SOP becomes important when you are on the border line. If they are deciding between (1) admitting you or someone else, (2) moving you or someone else off the waiting list, (3) awarding a prestigious fellowship to you or someone else, etc, your SOP begins to play a critical role because they have already compared you with that someone else using other yardsticks, the only thing they haven't used are your SOPs. Also, my undergraduate advisor told me that your SOP stays in your file even after you're admitted and they consult it before deciding whether to nominate you for NSF, DOE, Hertz fellowships. So it is best to take it seriously; I definitely am.

I just posted some (pretty reliable) hearsay about this in another thread; what is considered good mainly depends on where you're from:

What I heard from somebody who's on the admissions committee at a top school is that if you're applying from China and you get anything below the 90th percentile, it's going to hurt you; if you're applying from India, then the cut-off is somewhere between the 80-85th percentile; if you're applying from within the US, you can go as low as 75th, particularly if you belong to an under-represented group. The bottom line is that average percentile is a poor measure; say you're 80th percentile, that would be fine if you are at an American college but you're screwed if you're applying from China.

I am applying to PhD programs in Stat and CS (and a few in applied math and EE) looking to do machine learning. Somebody I know who's on the admissions committee at a top school told me that when it comes to my SOP, it's better not to emphasize too much that I want to do ML since they get a ton of applicants who write that, and that on the committee they tend to lump applicants into different groups so that if you get assigned to the ML group, you face much stiffer competition. She said that in reality a lot of applicants say that they want to do something else and after they got admitted they switched to ML. The problem is that I've already spent a lot of time writing my SOP, doing just what she told me not to. In fact since I've been gearing towards a PhD in ML, all my experience (research projects, courses, internships, etc) are somewhat ML-related. It never occurred to me that this could be a bad strategy. If I remove the focus on ML, my SOP will be weaker. Besides it's kind of hard to hide since my two of my letters will be from ML professors and my entire profile clearly points towards ML. Anyone else who's facing a similar dilemma?