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SoymilkLatte

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  1. I've heard some good comments toward OSU stat department. To me, the OSU faculties are having decent background, do not seem weaker than UMN and BU. I would suggest you looking through your POI's previous work, not their education background. A good researcher is not defined by his/her graduated school. People do most of their valuable works during PhD, not undergrad (which decides their PhD school). A few faculties with less publication cannot say a thing on the program's quality. You'll not be advised by all of the professors, and there's not a single department can be perfect and filled with top faculties. In addition, I would not worry too much about the program ranking. Again, people will value you by your work and publication, not the brand of your school. Always go to somewhere fits better instead of pursuing higher ranked program. I would say, the OSU program is a great choice, while you have to decide whether it's a good fit for you.
  2. 1. The fact that UMN Biostat may not be as strong as the current ranking shows matters if the ranking is one of the most important part for your consideration. 2. Dr. Pan is advising several students in Biostat department and also a few (>=3, I'm not sure) students from Stat & ECE now (usually the students from Stat/ECE have more solid background when doing ML/DL, probably the reason why he prefer them?). I doubt if he has enough funding to support more people working on his ML project. Given he is probably the only one who is seriously doing ML stuff in the department, if you could not get along with his style, your situation might be a little bit awkward. I'm not familiar with him personally, but I heard he is more to the pushy side. Do not put all your eggs in one basket. I guess you could find more professors from BU stat/math interested in ML. 3. I do not think BU is less reputable than UMN, at all. Considering alumni network, I would say that BU is a little bit more recognized during job hunting compared with UMN. However, going to industry, once you've gone through the initial HR screening, the brand/ranking of your university would be no longer a big deal. 4. Enjoying yourself in your daily life is one of the most important part to live a happy, healthy and successful PhD life without depression (which affect 60% of the phd students here in the U.S.). You do not know what it means when you are saying 'suffer' with ease now. If what you really want is a Stat PhD, starting a biostat PhD may not be a wise choice. UW is definitely a *big* name in Biostat area. If you don't mind to fund yourself, I would say it could be a great stepping stone to a better Stat/Biostat PhD program. If you are still hesitating on going to academia or industry, it also could be a period of time for you to figure it out with plenty of room to plan your next move. None of the choice is 100% perfect and can ensure 100% success in your future. You'll gain something and at the same time lose something, but everything'll be worth it in the end. We cannot make the decision for you here, just follow your heart.
  3. Congratulations on the two offers! They are both great places to go! I don't know much about these two programs, but my friend graduated from Brown said the placement is pretty good, and the program is hiring more great professors these years. Brown is a new program, which may also mean the future ranking could be higher than where it is now. I believe it is a considerable choice compared with BU.
  4. I would strongly vote for BU. 1. The former head of the UMN biostat division, also the one having great reputation on Bayesian analysis, Brad Carlin, was laid off (officially as 'retired', interesting) because of sexual harassment. Meanwhile, there are several elder professors are likely to retire in a few years, and a substantial part of the young faculties does not seem having very strong academic reputation/publications compared with other top programs.The ranking of the program will possibly be decreasing in the future. 2. Considering your interest, I'm pretty sure that UMN biostat does not have professor working on network science. There are one or two doing machine learning previously, but none of them mainly focusing on machine learning and deep learning for now. Most of the professors are focusing on the traditional 'biostat' fields. Stat department is always a better place if you are interested in those hot topics. 3. Biostat would definitely narrow you down in job hunting. Most of the HR people in IT/finance company would treat you as someone from biological background. You have to make more effort on persuading them that you are also good at statistics and can do the same thing as a stat phd. So why not just get a stat phd? 4. Personally, I think most of the people would prefer the weather in Boston. Minnesota is indeed too cold and boring. Half-year winter from Oct to May? 10 inches of snow in 3 hrs? Absolutely no good seafood? Remember, Phd is a 5-year or more commitment, make sure you choose somewhere you really want to go! ---- From someone graduated from UMN biostat.
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