I'm wondering about the difference between public and private universities in terms of creating research directions for its students, specifically related to machine learning and neural networks. I found it harder to contribute to public universities in the US in general but I did my MS in CS at a private university. Does my speed have anything to do with the generality of public vs private university research or is this specific to the universities in question?
Research at Public University vs Private University: A perspective for a data science enthusiast!
3There are good groups turning out good students at either.– Jon CusterDec 3, 2022 at 22:44
7Both public and private universities range from the very best (e.g., Harvard and Berkeley) to the purely teaching oriented at the community-college level. There is nothing useful you will get if you ask about differences between such diverse groups.– Wolfgang BangerthDec 4, 2022 at 1:07
Will be quite different state to state as well.– BillOnneDec 4, 2022 at 1:12
6Would I be right in guessing that your experience is based on a very small sample size?– Nate EldredgeDec 4, 2022 at 18:04
The sample size was intentionally restricted to the groups I have interacted with at Public universities. Most of the people at the lab in the public university work on their area(s) of interest more than me, the data scientist trying to help them with work on neural networks that relates to their area of interest as a great application area for me.– Hans KDec 6, 2022 at 6:23
By "creating research directions for its students" I suppose you mean the success of faculty in suggesting and supporting research topics that turn out to be approachable and/or impactful.
I don't think there is any distinction between public and private universities that would significantly influence this one way or the other. It would have much more to do with the particular faculty member involved. The university as a whole has very little influence on how faculty work with students on a day-to-day basis; it is largely up to the individual professor's experience, advising style, skills, etc.
There could be university-level aspects that have some broader effect: available internal funding and research support, priority that faculty are expected to place on student research mentoring, emphasis on quantity versus quality of publications, and so on. But private and public universities can both be all over the spectrum in any of these respects, and systematic differences in one category of the other are fairly minor in comparison to the individual variation.
I think it might be related to data scientists being able to interact with scientists from other disciplines based on the factors that were brought up here.– Hans KDec 6, 2022 at 6:24