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Posted

Hi! I am trying to decide between the current offers for Stats PhD I have from Purdue, Minnesota, Ohio State and Univ of Toronto (Math Finance track in Statistics dept). I am interested in the areas of Machine Learning and high dimensional statistics, although I am open to explore new areas and then decide. Other than UoT where supervisors are already assigned, I have the flexibility to choose my supervisor in the other 3 places. In UoT, I have the chance to work at the interface of machine learning & finance which I find appealing. My questions are:

1. Which would be a better choice if I want a career in industry and which would be more suited for academia?

2. Among the US universities, is there any significant difference in the reputation of the 3 places? How close does the best of the 3 come to UoT in terms of research and future prospects?

It would be really helpful if someone could suggest well-reputed faculty members or someone doing good research in the areas of ML and  high dimensional statistics at Purdue, Minnesota & OSU.

Note: Due to the COVID-19 issues, I am considering deferment to next fall. While the US universities have given me the option to do so, there has been no such assurance from UoT so far.

Posted

Minnesota should be very strong in high dimensional stats. Prof. Hui Zou goes without saying but I have also seen plenty of influential papers by Prof. Y. Yang from the same department. I think it's also the highest ranked of the US universities there on USNews.

Posted (edited)

I'd say Minnesota and Toronto are probably pretty similarly strong, and overall probably stronger than the other two.  If you're looking specifically at mathematical finance, Toronto is a bit niche that they have it as an option.  But just overall in terms of high-dimensional statistics/ ML they're both very good options. 

Additional factors may depend on where you want to end up living for 5 years or if you in fact did want to defer a year. 

Edited by Spaghettini Plot

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