Hi everyone,
I have been agonizing over this decision for weeks. I applied to a combination of both CS and PhD programs this season, and got a few offers. Out of my CS admits, CMU CS is my best option and out of my Stats admits, Michigan is currently my best choice. In the beginning, I am pretty much set to go to CMU. However, the more I knew about the Michigan Stats program, the more I think it is a better fit for me. Yet I can not really let CMU go. I am heading to Pittsburgh this Thursday and will go to Ann Arbor on the mid of March for visitation so hopefully I can get a better feelings by then. But for now I would just like to get it off my chest and hear from your (hopefully impartial) opinion.
Background: CS senior in the Foundation & Theory track who took at lot of math classes (Cal I, II, II, IV + Linear Algebra), ODE, Abstract Algebra I, Real Analysis I + II, Probability Theory. I am interested in Machine Learning, Bayesian Machine Learning and Bayesian Nonparametric Model.
CMU: PhD Computer Science - Theory (not ML or Joint Stat-ML but my POI is an active researcher in Theoretical ML)
(+) Best CS school in the world (I have wanted to go to CMU CS grad school since my 1st year in college)
(+) Probably have the best ML faculty in the US which I can hopefully collaborate
(+) Copious numbers of interesting CS courses
(+) Very good placement record: Have placed one to Stanford and one to Berkeley and one to UChicago for tenured track positions.
(/) Many of my friends go there so I know the place quiet well
(/) No Qual Exam -> could be good or bad depending on your own opinions
(-) Heavily CS oriented curriculum. Please let me explain why it is a negative point. I am admitted into Computer Science PhD program (not ML or Stat-ML) so I have to take breadth courses from 6 main area of CS including Software Systems, Computer Architecture and Programming Language so I will not have enough time to take courses in Probability & Statistical & Measure Theory which are very crucial to ML research.
(-) Top 30 Math department - again, please let me explain why math department has anything to do here. I like mathematics a lot so I would like to get an additional MS in Pure Mathematics during my PhD
Michigan: PhD in Statistics
(+) Very good program reputation: most of my professors think very highly of Michigan in general and especially of their Stats program in specific.
(+) Math-Stats curriculum oriented: I only need to take courses in Probability & Statistics & Measure theories so I guess I will have solid foundation to do research in ML.
(+) Perfect Research Fit: My POI at Michigan does exactly what I want to do for my PhD.
(+) Comparable placement record: Surprised to me, Michigan Stat has a comparable placement record to CMU. Even only looking at the CMU ML department, not including one to Stanford and one to Berkeley Assistant Professors, they are similar:
https://www.ml.cmu.edu/people/alumni-phd.html
https://lsa.umich.edu/stats/alumni-friends/statistics-phd-alumni.html
(+) Have Qual Exam: I like the fact that there are two Qual Exam (Theory + Data Analysis) which helps me to master material better
(+) Top 10 Math department: Since my Stat curriculum is very close to Analysis, it is easy for me to take extra 6 courses in Analysis, Topology and Numerical Method to get an extra MS degree in Math from a very good Math department.
(-) Overall prestige: I know it is petty but I went to college in the North East and not many people know that Michigan is a good school.
(-) Research output: I am not sure if it is reliable but according to this website (http://csrankings.org/) which ranks institutions by number of papers in top tier journals and conferences. For AI field, CMU research output is almost 3 times Michigan (59 vs 30), so I could potentially miss out more interesting projects at CMU ?
So am I right to go to Michigan where I think it best-fits me ? Or Am I crazy to turn down CMU offer?