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Everything posted by seems_fair
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I couldn't find one, so I created one myself: https://t.me/umass_fall2018
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I will go to Umass Amherst as well. Is there telegram/whatsapp/facebook for those who got in?
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I thought about it as well and I agree about effort and money part. Still, I think that this process is very inefficient (as you mentioned earlier) especially comparing the number of open postdoc positions (almost every lab has them) to the number of accepted phd students. It looks like training process fails to supply the demand in good researchers. Or maybe the field (ML/DL) is new that's why there is a shortage of good researchers in this area. But that's the reality we live (and apply) in. ¯\_(ツ)_/¯
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I think that the admission process is extremely risk-averse adds another layer of complexity. Given the number of applicants, if you are non-usual applicant (i.e. 30+, switching areas or have uncommon personal history) you are at a disadvantage because there are a lot of comparable candidates which look 'safer' (i.e. solid undergrad with good GPA and decent ML-research experience even without publications). I am in similar position as you (I am 30+) and got only one offer so far although I have 4 first-author publications in related field (but I also have really bad undergrad GPA and very decent MS).
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Congratulations! I applied there as well, but haven't heard from them.
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Good point, I was thinking of this. As of now, I want to keep it as is -- otherwise, it will require generating everything again. Also, bear in mind that this data is based on 5-year period, so these spikes maybe for the particalar year in admissions.
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I checked data and these are kinda specific programs (about several hundred observations for all universities). It is just too granular. Sorry.
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I hear the Machine Spirit's voice: Mechanical and Aerospace Engineering, PhD https://imgur.com/a/qDkjN Mechanical and Aerospace Engineering, MS https://imgur.com/a/UIYnF The Emperor protects.
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Well, it's weird.
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There can be bias in self-reported scores, because rejected people with good scores may be salty. That's why I was mostly interested in timelines.
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Here you go: Communication PhD https://imgur.com/a/IRf4t Communication MS https://imgur.com/a/lF6IF
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I got a rejection from UT Austin as well. Lot of good candidates ¯\_(ツ)_/¯
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Here you go Clinical Psychology PhD https://imgur.com/a/cTTUz
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Here you go: Civil Engineering PhD https://imgur.com/a/rYcyf Civil Engineering MS https://imgur.com/a/rOarb
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I wouldn't look to acceptance rates based on this data because they are definitely skewed towards acceptance in most cases.
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Thanks! Here you go: Education PhD https://imgur.com/a/NVZQH Education MS https://imgur.com/a/yfoQz
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I have really bad undergrad GPA. But we'll see. Thanks for kind words!
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Here you go Spanish PhD https://imgur.com/a/7rGtf
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Here you go Geography PhD https://imgur.com/a/f0yfP
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Here you go Microbiology PhD https://imgur.com/a/swpLT Not enough data for particular universities.
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I wouldn't look at accepted/rejected ratio in this data because it is definitely biased. People are more likely to brag about accepts than rejects. And CS is crazy competitive. I am applying to CS and scared shitless.
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Sociology is in one of the answers above. Geography I will check if there is enough data.
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Added another one: History PhD https://imgur.com/a/lXdLe
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Added another big one: Political Science PhD https://imgur.com/a/EuNTB
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By request, added two more. Please bear in mind that some programs can be too specific (i.e. Arabian studies), thus not having enough data for particular university (I use 30 observations threshold). Biostatistics PhD https://imgur.com/a/UQ2e9 Linguistics PhD https://imgur.com/a/MauHg
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