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DanielWarlock

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About DanielWarlock

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  1. I think you definitely stand a chance. I think Cambrdige math tripo III publishes their offer rate which I believe is above 30% so your profile definitely is competitive. But of course they are still competitive.
  2. Cambridge MASt is a strong program, so is the oxford one especially you have your eyes on PhD. My cohort this year has graduate from both programs. University of Bonn has a very strong master program in mathematics also where you can specialize in probability/statistics.
  3. I'm a starting phd myself this year so I can't claim authority on this. But here is my two cents. Normally I would be tempted to say that you will have no trouble at top programs as you listed. But I have seen too many competitive people here and elsewhere this year to say that you are a shoe-in (several published at places like anal of stats/prob, jmlr, jams etc). I think one of the reasons is that the covid pushed a lot of elite people to grad school from industry. An argument can be made that there is less competition from international applicants, but as far as I know most competitive people will apply regardless. But it is really hard to say. So even if your profile is very strong, I'd be cautionary and apply broadly: this does not mean you should not consider top 10 schools. But rather to apply to some range 20-50 schools as well.
  4. First of all, you don't have to be anxious or stressed out. I read your post. You seem to be concerned about a lot of things. I am not able to answer many of your very technical questions. But trust me there is no need to be worried about any of these things. Try to relax and enjoy your senior year! Do not let the pressure get to you. Have a social life, have fun, and talk to your friends (especially when you feel low or are stressed out). Here is another fact that may soothe you: most students applying to masters or phd programs in statistics don't have nearly as much experience as you do. You have done great work and should be proud of your achievements! Master programs are often less selective than PhD programs. Your profile has far exceeded requirements of many programs out there. I'm sure that you will get into some of the places on your list. Finally, good luck!
  5. You should know that master programs do not rank exactly like PhD programs (as in US news). I would like to use this opportunity to give a TOP 10 Rankings for US Master Programs: ==================================== Tier 1: 1. University of Chicago (MA in Statistics) 1. Stanford (MS Statistics or Data Science) --------------------------------------------------------------------- Tier 2: 3. Stanford (ICME, ML/AI/Data Science track) 3. Princeton (OFRE, MSE, MFIN) 3. MIT (Masters at OR or EECS) --------------------------------------------------------------------- Tier 3: 6. UW 6. Duke 6. Upenn ---------------------------------------------------------------------- Tier 4: 9. Harvard 10. Berkeley ==================================== This list is based on personal opinion but is generally influenced by popular opinion. For example, Stanford and UChicago is considered best 2 programs (personally I think UChicago is better than Stanford with thesis option, scholarship and ~50% admission rate to its PhD program). The other overlooked program at Stanford is the data science offered under its ICME institute as opposed to the one offered at stats department, which is also very good--there is an option to just switch to PhD at ICME upon satisfying some basic requirement. The next in line must be the MFIN or MSE at Princeton ORFE--at first glance it is untraditional for statistics but there is a good chance to switch to PhD program under ORFE which gives you excellent chance to study under top probabilists and statisticians. If you orientation is industry then ORFE gives you the best platform. The other excellent option to study statistics at master level is at MIT: either through EECS or OR's master programs. There are a lot of statistics/probability going around at MIT and lots of classes even though it does not have a dedicated statistics department. Next, UW, UPenn, Duke all have very good, very solid master programs in statistics. The last category encompasses two better known schools. They are both good but curriculum is not as rigorous. For example, Berkeley only has only 8 months, no thesis, and classes are really watered down stuff compared to PhD. Harvard is autonomous --more like a self-tailored sort of program--so it is harder to say. On your profile: Your course work and research are really good. I think you have a shot at Top 10 (maybe outside of tier 1).
  6. - I recommend retaking GRE because your verbal/writing is a bit too low. - If your main interest is EM, I recommend applying to Harvard also; there is considerable interest there in Bayesian computation and I think Xiao Li Meng is quite well known as far as EM is concerned. Also Columbia is also a good choice with well-known Bayesian people like David Blei and Andrew Gelman.
  7. Your profile could become much stronger than mine. But most of your hardcore classes as well as research have not come out in time. And you have not done math GRE which is another problem. Gap one year will get you into Stanford level assuming optimal performance in those 3 graduate series (real analysis, probability, stats theory), math GRE (90%+) and research (to the point where your supervisor finds impressive). If no gap, then it is really hard to say. But still, you could get into some solid schools even with no gap. It is just hard to say if you need to get to the Stanford level. So I would personally choose to gap if I can.
  8. It is not satire and it is a collaboration effort. Actually they may have eventually resolved to buy like 10 of these and put them in the prof's office for safekeeping because it is much cheaper if you buy a bunch at a time.
  9. I must give my opinion on university computing cluster and cloud solution: (i) university computing cluster will require you to submit a batch file and you will potentially need to wait for a long time before your job is executed. And if they do provide interactive, resources allotted to you will be very limited; (ii) I definitely DO NOT recommend using cloud computing such as AWS even if you have like $200 free credits to burn through--it is nothing. The cost can be as high as $30/hr PER NODE for some luxury machines! They will also charge you on storage etc also. I used AWS last semester because the experience is better than university cluster. BIG MISTAKE! After 2 month my bill is $700+, and I haven't actually done anything substantial. So if you can convince your cohort to buy a commonly accessible GPU then do that instead. Sometimes department has spare funds so they buy stuff like massage chairs but such money in my opinion is better spent on computing equipment.
  10. I always dream of one of those "monster machines" with lots of cores (e.g. 16 cores) whereas my own macbook has only 2 cores. Some "pro people" do have such machines and would even carry around GPU/FPGA boards. Some of my classmates recently have pooled resources together to buy Nvidia's new multi-instance GPU (A100) for $199000 a piece!
  11. In this case, maybe you can ask your current supervisor to refer you directly? It is different from just writing a letter. Your prof basically sets you up with his colleagues so that they will look after your application. I know people who got in this way. Also maybe that one faculty you are interested in does not even take any students this year. If so, you are throwing money away by applying that school.
  12. Harvard applied math is affiliated to the engineering school (SEAS) instead of art and sciences; like other engineering disciplines at harvard it is very small (only 8 profs). I believe it has nothing to do with the "real" math department.
  13. Your course list is heavenly. You should get into most top programs barring possibly Stanford.
  14. Harvard is committed to be open. No one knows anything other than that. We are all very worried.
  15. They like to admit people with interesting background. I myself specialized in Monte Carlo algorithm and they thought I would be an interesting addition to the cohort. There are people who did astronomy, fashion design, environment protection, Italian language and all sorts of things that can apply data science techniques in novel ways. I thought you have good chance given your background is kind of unique although it is not guaranteed--you should make case of how you would apply stuff such as neural network or other ML things to your specialty (i.e. BA). Graduates from my cohort is highly successful which actually exceeds my expectation-- most of them went to Facebook, Google, Apple, Uber or top finance firms such as JP Morgan, Goldman Sachs, Mckinsey, Bridgewater etc., and several including myself remained at Harvard for PhD in CS or stats. I also got offers from Berkeley Duke etc. Now that I'm graduating, the outcome (both my own and my classmates) indeed exceeds my original expectation of what a master degree can achieve. Two years before I worked as an IT-type of guy in an unknown company maintaining spread sheet and emails etc. and never thought I would have progressed this far. This master degree really paid off (meanwhile it also almost bankrupts my family financially and put me in a hard spot for the future 5 years so you need to think twice if you are married). In the case where you have money, you should apply and do a master here.
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