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orchidnora

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Everything posted by orchidnora

  1. Thanks for the info! @Geococcyx: I actually have not heard that, but that's interesting. Maybe they're simply trying to expand their program. @bayessays You're right, all of these schools are great. I'll visit to decide, as you suggest, since I like both Bayesian stuff and ML. @Stat PhD Now Postdoc Cool, I didn't know about social science applications and network/spatial data at UW. I have some interest in those topics, but not strong enough to justify going there specifically for it. ML research in general though is very important to me.
  2. Hi, everyone. Does anybody have any information to compare these schools? I am very excited to have been accepted to these amazing schools and never expected I would have to make such a decision. Berkeley has been my top choice for a while for various reasons. But I want to be cautious and evaluate all my options carefully. I will definitely be visiting Duke and Berkeley to help decide, but I'm not sure if I want to attend UW. Any information about these schools (especially UW, since I'm less familiar with their program) would be helpful for me.
  3. Thanks @Stat PhD Now Postdoc! That is very good advice and reassuring. About your last point, many of the professors I'm looking at have big research groups, so hopefully the other Ph.D. students and even postdocs would be available for a chat sometimes. How often would you meet with your advisor on average? I think I would be fine, as long as my advisor can meet (or Skype) about once every 1-2 weeks.
  4. Hi, everyone. I'm supposed to be making lists of potential advisors at schools I'll be visiting. Some of the professors with whom I have the best research fit seem to be very busy people. Some have 10 or more students and postdocs. Does anybody have experience with or insights on working with very busy advisors? Thanks!
  5. I think you should also post your budget, keeping in mind that some departments/advisors might provide you with a work computer or funding for one as well. One thing that's nice about Mac is that the hyperthreading can be easily exploited in R through the "parallel" package. Using the "parallel" package, you can easily speed up certain types/sections of code drastically. This is convenient if you plan on running your code locally. If you get into heavily computational work, then you will be probably be mostly working on HPC. In that case, the quality of your computer doesn't matter as much (a $500 laptop would suffice), as long as you can connect remotely to the HPC server. Connecting to the server is obviously easier through Unix, but there are programs you can download to access it through Windows too. Personally, I like working locally in RStudio as well as using HPC, so I did recently buy a nice ASUS laptop with Windows. I would have liked a Mac, but a Mac with similar specifications is far outside my budget.
  6. Thanks to all for the insights! I never would have guessed that Michael Jordan DOESN'T come from a math/stats background. That really puts it into perspective for me. Since I am mostly interested in computational stats/ML, it makes sense more sense now that I've been drawn to these professors with strong ties to EE/CS. I've been looking at the journals potential advisors publish in, as well as the student job placement, and now I feel more confident about my choice of advisors.
  7. I was also rejected from Stanford just now. But I'm not surprised (given my less than impressive math subject test score), nor am I disappointed (given that Berkeley was my top pick anyway)
  8. Congrats to all who got accepted to Stanford! I still haven't heard anything from them. However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school.
  9. I'm looking for potential Ph.D. advisors at various schools. However, some schools (like Duke) have many professors with joint appointments. These people are listed as professors of Statistics, but when I go to their websites, I discover that the Ph.D. was in a different field, such as Electrical Engineering, Machine Learning, or CS. Other than the actual degree, they appear to do statistical research that I'm interested in. Does it matter for statistics if I am advised by somebody with a Ph.D. that's technically in a different field? I would love to hear anybody's thoughts on this matter. Thanks!
  10. I’ll be turning down NC State today because of my offer from Duke, so hopefully the spot will go towards one of ya’all on the waitlist. Good luck! Also congrats to everyone who was recently admitted to other schools!
  11. Thank you!! I almost had a heart attack when I got an email from Duke, and I immediately assumed I was rejected (since it only said to check the application portal, plus I also thought they do interviews). But I guess this time they're only interviewing some applicants.
  12. I literally just got emailed by Duke to check the application portal, and it was an acceptance letter from the department!!! I am beyond ecstatic, after checking my email almost constantly since last week. This is the first correspondence I've had from Duke (there was no request for an interview or anything like that).
  13. I haven't been informed of a visit day yet. My hunch is that I was admitted earlier than some applicants, because of my fellowship nomination (I have to fill out an application for it that is due next week). In that case, maybe the other admits haven't even been decided or notified yet.
  14. Thanks, @MathStat and @ducky500! For anyone wondering, I did email Texas A&M about my admissions. They confirmed that I am accepted and that I will receive TA/RA funding even if I'm not awarded the fellowship. I haven't heard anything yet about the Stats Ph.D. at UW and Duke. My application statuses are still just "submitted".
  15. I submitted my application on December 14th, so definitely wayyyy before the deadline. I also read on their stats dept website that admissions are rolling, so maybe they haven't gotten to your app yet
  16. Ok thanks for the info, everyone! Hopefully we'll hear more from A&M (and other schools!) soon.
  17. I've received an email from the Texas A&M Statistics Department nominating me for a university-based diversity fellowship and encouraging me to apply. But nothing was said about whether I am admitted or not. Does anybody know what this means in terms of my admission to the university?
  18. In my current department, the specified hours for a TA position are really an upper bound for the amount of time it could take (my teaching duties only take me half the specified time). Hopefully it's the same at NCSU. Somebody else on here probably knows better than I do though
  19. Thanks for the help! I have adjusted my schedule accordingly.
  20. I got an email from NCSU offering unofficial acceptance from the department for the Stats Ph.D. program! Departmental funding was also offered. I also posted this on the results page. Congrats to those of you already admitted, and good luck to everyone still waiting!
  21. Thanks for the responses! The two classes I need to graduate are one math elective and foreign language. The other two classes I signed up for are Foundations of Math (which I’m pretty sure has little relevance to stats) and theoretical differential geometry. I would sign up for research credits, but I have already taken them before. I just don’t want my last semester to be too stressful, since I’ll have no break before grad school (I have a research internship that I’m looking forward to this summer). But I don’t want this to somehow affect admissions.
  22. Hi, everyone! I am graduating with my B.S. in Math and in Stats this Spring, so this is my last semester. I have applied to 7 Statistics Ph.D. programs, all within the 10 top schools (according to US News rankings). Does it matter if I take only 2 classes in my last semester as an undergrad? These are the only ones required to graduate. Other details: Several Ph.D. applications asked me for my Spring 2019 schedule, and on there are I listed 4 classes (2 math classes beyond what is necessary to graduate). This was only on the original applications I submitted in December. I have not received any correspondence from any schools yet. I'm doubtful that my admission would be contingent on the completion of these 2 additional math classes, since I still will have taken 2 years of real analysis before beginning a Ph.D. program. Any free time I'd gain from dropping these 2 classes would be spent working on a research project, which I'm hoping to relate to my Ph.D. research. I would greatly appreciate any thoughts on this, before changing my Spring schedule! Thanks.
  23. Hi there. First of all, I would recommend you repost this to the Math & Statistics Gradcafe forum, since you'll probably get more responses there. In my opinion, participating in more biostats research will only make your more competitive for biostats programs. What programs are you thinking about when referring to "diversity camps"? The 10 week full-time research programs are often NSF funded REUs. One of NSF's goals is to promote diversity in science, so decisions are made in consideration of applicants' race, gender, etc. However, these are legitimate research opportunities. But you should never be losing money from these. The applications should be free, and REUs offer stipends + living expenses ranging from $4000-10,000 value. If you're applying to a research-based Master's program, then research experience is at least equal and probably preferable to internship experience (depending on the nature of the internship). Assuming you already have satisfied prerequisites for a biostats program, then research/internship over the summer is more beneficial than additional coursework in my opinion. Also getting a decent score on the general GRE really should not take months of dedicated study over the summer, if you have excelled in the quantitative courses required for a biostats Master's.
  24. I see, that's an awesome deal! In that case, you may be competitive to apply straight for Ph.D. programs in Stats after these 34 credits, hinging on research experience of course. Do you know what language the stats courses at your school uses? For stats, R will be a big one to know. I wouldn't be too concerned about learning Python specifically, but by all means self-teach yourself in the meantime if you feel motivated. Most likely, you'll get strong in R, Python, or some other language of choice quite naturally through research projects. Now for research, since you say there aren't many research opportunities at your school, you should look elsewhere. I'm not sure if you have other commitments, but assuming not, then summers are prime time for doing research. As I mentioned before, typically it is difficult to get research without taking at least 4 semesters worth of math/stats coursework. However, if you emphasize your past research experience in science (to show that you know how to do research, even though it's a different field) + your independent projects, it may just work. If you can tie in your past Bachelor's degree and the research you've already done to your research interests in ML, then that could work even better for you. Google NSF REUs (there are some in machine learning; sometimes they're listed under stats, data science, math, etc...so just read the description) and national laboratories (Department of Energy, National Institute of Health, etc.). There are probably tons of other opportunities, but those are the ones I know. You could probably start applying for research in Fall 2019 and possibly get accepted to some research program for Summer 2020.
  25. I agree with @Stat PhD Now Postdoc that there are great opportunities in industry for ML from a stats or a CS background. ML is essentially the intersection of math, statistics, and CS. Because of that, you should choose stats vs. CS based on what you like better. Typically, statisticians are more concerned than computer scientists with the mathematical theory underlying ML approaches, including checking assumptions, model validation, model interpretation, etc. In fact, many methods now under the umbrella of ML were originally developed by statisticians. Keep in mind as well that there are Master's in Data Science programs out there. Some are cash cows (so be careful), but others seem reasonable. From what I can tell, they are typically not traditional research-based Master's degrees but rather sort of vocational, in that you learn exactly the skills to be directly applied in industry. A degree like that probably isn't enough to be the head of R&D at Google but can still offer lucrative opportunities in industry. Some of these Master's programs do not require an extensive quantitative background and even appreciate people from alternative backgrounds. Also when I asked about Master's degrees, I meant skipping a second Bachelor's and jumping straight into a Master's. Getting another Bachelor's involves repeating a lot of unnecessary coursework. I believe any Bachelor's should take more than 3-4 semesters. Are your previous credits counting toward it? Or do you mean that you plan to take 3-4 semesters of coursework but will not earn a Bachelor's from it?
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