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I'm wondering about the difference between public and private universities in terms of the research explorations a professor doesn't mind their students working on. In my case, it turned out to mean that I cannot work on my interests alongside my professor's. I have industry experience and private university professors who know otherwise about my multi-tasking. This has to do with the differences between being a researcher in data science and being a data scientist. I was sure that academia would be a safe space to explore such differences, especially given that a professor showed interest in considering working with me knowing my background and research interests. The fact that I wasn't able to work on research into neural networks alongside its outcome-driven progress in another area of interest reminds me of what I've read about the 80's wrt artificial neural networks research. What are the criteria for being able to work on related problems at once if the fact that I worked for a public university was the only difference between whether or not I was able to work with this professor who didn't mind simultaneous mathematical explorations?

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    There are good groups turning out good students at either.
    – Jon Custer
    Commented Dec 3, 2022 at 22:44
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    Both 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. Commented Dec 4, 2022 at 1:07
  • Will be quite different state to state as well.
    – BillOnne
    Commented Dec 4, 2022 at 1:12
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    Would I be right in guessing that your experience is based on a very small sample size? Commented Dec 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. Commented Dec 6, 2022 at 6:23

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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.

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  • 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. Commented Dec 6, 2022 at 6:24
  • I have since modified the question a little bit. If you can spare the time, I'd like to hear about what you might have to say wrt the modified question. Commented Feb 29 at 7:03

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