PhD Machine Learning

[alguru]

Hey guys,

I'm in the process of completing my master's degree in Computer Science (Machine Learning specifically) at the University of Oxford, and deciding where I would like to go next for my PhD in Machine Learning. I have received fully funded offers from the following universities:

Georgia Tech
Cambridge University
University of British Columbia
McGill University
Ohio State University

After graduation, I will most likely be interested in pursuing a research-oriented position in a company (such Google) rather than an academic institution. Note that I am not a citizen of any of the countries in which the above universities are located, so that issue won't play a factor in my decision. I am slightly inclined to choose from either Georgia Tech or Cambridge, but I'm not sure yet.

Any suggestions? 
Thanks!

[ssk2]

Out of your choices I'd strongly advocate going to Cambridge for the following reasons (assuming that all other things are equal - such as funding):

• The CS department is extremely strong there overall - it's probably ranked higher than Georgia Tech.
• Cambridge is a beautiful city. Depending on what you're into, you may enjoy living there for a number of years more than Atlanta. There's a LOT of culture in the place, the university celebrated its 800th anniversary a few years ago - approximately 7 times as old as Georgia Tech. Extra curriculars at Cambridge are fantastic and the college system is great.
• It's a shorter course, the opportunity cost of studying is much less. You'll save yourself two years. Depending on your funding situation, you're will probably have to do less teaching while you're at Cambridge which gives you more time to focus on your research.
• Employers all over have heard of the university. It has consistently been in the top five universities worldwide. I know people who have graduated from Cambridge to go into Google / Microsoft Research. In fact, there's a large Microsoft Research department in Cambridge. By the time you graduate, Google's new London headquarters will have been completed and they'll no doubt be sucking up as many computer scientists as possible.

[SANDIEGO]

I second Cambridge. Georgia Tech is probably a top 10 in the states, UBC and McGill are both top 5-10 in Canada, but you're looking at Cambridge which is arguably a top 5-10 in the world. Not to say that you should be basing your decisions on reputation alone, but the gap here is significant.

[fukuyama]

You have five good choices. I think the choice of school isn't as relevant as factors such as faculty pairing, and lab environment. 

 

My colleague has a really good post here: http://www.theclimatecode.com/2013/02/a-phd-is-like-haute-couture-its.html . I think the best (if you can manage) is to visit the labs you are interested in with these things in mind, or even email some of the senior PhD students to get a sense. All of them are within the top quarter of universities in terms of rankings so your opportunities won't much depend on 'name' recognition. In any case, places such as MSR or Google Research are less focused on pedigree than in tenured academic positions. You'll find several people in Machine learning and data mining coming into these places with Hong Kong, Greece, Singapore PhDs, or from lower-ranking universities in the U.S. and Canada. 

 

Another note of advice is that in choosing an advisor you should keep in mind that your advisor does not dedicate themselves to your goals. At best the advisor relationship is mutually productive, but (especially with 'superstars') it can be somewhat predatory; having a strong idea what you want to do and what resources you need to do it will save you months or even years of 'working for' your advisor, and being pushed out with a lackluster publication record because of expected PhD timelines.

 

I'd contact three or so faculty at each of these schools, looking for a match. Also consider that redundancy is a good factor. My M.S. was at Minnesota, where there are a good selection of data mining faculty (5, solidly). People switch advisors if things dont work out, and being at a university which is an island of you and your advisor is a precarious situation.