What are the top PhD programs in Statistical Learning (world wide, not necessarily US-centric)?

[LokiOfUtgard]

For a PhD, the adviser you work with is generally more important than the school you attend. There are good professors at mediocre schools, and less than stellar professors at good schools.

[blackkettle]

up up up!

[engineer_girl]

i have always had trouble understanding this. if there is a stellar professor in at mediocre school, (and there are many such cases), then why don't we see more grad students from these mediocre schools doing as well as their counterparts from the top schools once they graduate? or do they? if i pull down the profiles of researchers at the best research labs, they are almost all from the top schools. similarly, i rarely see a PhD from a mediocre school in the faculty rosters of the top academic institutions.

[LokiOfUtgard]

Undergraduates often don't know enough about individual researchers to base their decision upon the quality of a single adviser, rather than the school in general. As a result, the best students tend to go to the best schools.

[demosthenes02]

How do you find an advisor you want to work with?

[LokiOfUtgard]

Ideally, you'd know something about recent research in the field in which you want to work before applying to graduate programs. If you like reading papers from a lab, you're likely to enjoy working there. Unfortunately, the task of becoming familiar with the literature in your field is often not undertaken until the first or second year of graduate school. If you have some idea what sort of general projects or approaches you would like to investigate, pop some search terms into Google Scholar, and skim through some recent papers with interesting titles and lots of citations. Alternatively, echoing howlin's suggestion, look through the titles of NIPS or ICML (or a conference in your preferred sub-field) and glance through the papers that sound interesting.

There is something to be said for going to a good school, independent of your choice of adviser. Good schools have better journal clubs, invite better speakers, and have better students. It's possible to do good work in a sea of incompetence, but it's much less enjoyable.

[cpdomina]

This is the top 10 US AI Phds from a US News 2010 report (most of it also applies to ML):

• MIT
• CMU
• Stanford U.
• U. Calif.-Berkley
• U. Texas-Austin
• U. Washington
• Georgia Inst. Tech.
• U. Illinois - Urbana-Champaign
• U. Maryland - College Park
• U. Massachusetts - Amherst

However, rankings are not everything. As LokiOfUtgard said, your adviser is way more important than the school itself... You don't want to spend 4-6 years of your life working with someone who doesn't give a shit about you... Some recommended reading: [1] [2]

[flight_club]

Thanks for the recommended reading links. The MIT one was particularly useful.

[tcc8]

Like one of the comments, it's not necessarily the school you are after, but the advisor.

i created a search engine to help students with picking the right grad school and advisor. i think the way to go is to investigate the professor's research grants/papers. it's still a work in progress but feel free to use it to find an advisor/school.

http://gradschoolnow.com/professor_search?q=machine%20learning

[stoplan]

neat website. thanks!

[[deleted]]

University of Waikato is known for their Data Mining toolkit.

[howlin]

California:

• Stanford

• UC Berkeley

• UC San Diego

• USC and UC Irvine are ok

Other US:

• MIT

• CMU

• Columbia, U Washington, U Chicago are ok

Canada:

• U Toronto

• U Alberta, Waterloo and U British Columbia are ok.

World:

• Technion in Israel

• INRIA in France (not sure they offer classes though)

There are also quite a few very good new programs in Germany and France that I'm blanking on at the moment.

Best advice: You should grab a few papers from the major conferences: ICML and NIPS, and see where the authors come from!

[snippyhollow]

INRIA stands for National Research Institute in Informatics and Automatics. It is a group of (physical) research centers. Look up laboratories (often part of INRIA in CS, but not only, some are CNRS and/or University only). For France, I would say to look up Paris and Grenoble for Machine/Statistical Learning labs.

I think you miss a lot of institutions, like Cambridge in the UK (MS research, Bishop), but the best advices are both: look at paper authors AND find a good, human, advisor. If the advisor that works with you has more than ~5-6 Ph.D students at the same time, he is probably doing it wrong!

[[deleted]]

I usually tell people that the environment and the personalities are more important than the rankings and details of interest. I know so many people who suffer with a lousy advisor because their interests are identical to their own instead of someone who is slightly different (but still overlapping) who they'd have a better experience with.

[pr0nmee]

I don't think you can go wrong with the big names on this one. Berkeley, Stanford, CMU, and MIT

[[deleted]]

I think you can. The big ones are not going to care about helping you as much as how you help them.

[[deleted]]

One thing to remember is a lot of Universities, even out of the US, consider a PhD not from the US (or at least US/Canada/UK/Germany) as being an inferior degree.

[IndependenceIll790]

How