Almagest

I think you really should go to CMU if you are interested in machine learning and related topics. Their advantage over Chicago in this area is tremendous. It is indeed my top choice, but sadly I got rejected. Also, I talked to one of my professors, he told me that Chicago Stat department is not such a large department. There are many affiliated faculty members in that department. The number of core faculty members is quite small. Besides, I heard from some current statistics graduate students that the atmosphere in Chicago Stat is not so good. Students there are under a lot of pressure and many of them are quite depressed. Anyway, congratulations on your offers, and hope you make a wise selection!

Hi all, These two offers are my top choices, and I'm really having a hard time deciding which graduate school to attend. My research interests are mainly in the area of statistical machine learning, and the applications of statistics to problems in artificial intelligence. I mainly applied to Statistics Ph.D. programs, but also got this offer in Applied Math. I'm still not sure what I want to do after graduation, but I think I definitely want a research-oriented job, and I think to stay in academia or to become a research scientist in industry both fit my interests. I've visiited these two universities, and I think concerning these two schools, they each have some pros and cons. Brown pros: 1. I'm in contact with one of the professors. Very interesting research (in computer vision), lots of statistics involved, also very famous. 2. Flexible course requirements, lots of collaboration among different departments. And the newly built ICERM, which may provide some potential opportunities. 3. The applied math program is highly ranked. Ivy league university. Also more money (approximately $8000/year more than Umich, and no TA for the first year). cons: 1. The size of the graduate school at Brown is rather small, and only one or two professors in the Applied Math department, maybe plus a few professors from the computer science department, have research interests that are similar to mine. I'm not quite interested in traditional applied math like PDEs, ect. 2. Statistics is really not what Brown is good at. Umich: pros: 1. Quite strong in statistical machine learning. In fact, nearly half of the department is working on problems related to statistical machine learning, and the chair says they have recruited one more guy in this area this year. I think it's really a great place for machine learning. 2. Large gradute schools, lots of strong graduate programs, more to offer with regard to research. cons: 1. I taked to one of the professors in machine learning, and looked through the websites of some other professors. But currently I find their research less interesting than that of the professor at Brown. I'm not sure what I would feel like once I actually start to work on them. 2. Less money, and have to be GSI for the first year. Providence and Ann Arbor are of different styles, but I don't have a clear preference. I think Providence has a much better geological location, though. Thanks!