bernard

Ask only if you have a good reason: like you have a family to take care, or you find the stipend is insufficient for living comfortably. Otherwise, do not ask. You are not going to grad school to make money. Beside, you can not really compare stipend, because different cities have different standard of living.

Let me say first that the placement of schools in the ranking does not really matter. The good thing about this ranking is that it is based on objective factors (citations, total papers), and no subjective factors (peer-review) were used. But I also agree with some of you that it does emphasize too much on citations and not putting enough weight on citations/paper (for smaller programs). The ranking does tell you that Cornell is not on the list, which means it is not a hot place to do research (at least overall speaking). The ranking uses more recent papers (1996-2006) for its analysis, so no ancient classic papers were used. :wink: Perhaps Cornell was more active in the old days. However, if you believe that Cornell has the right PI for you, choose it by all means. But in ML, I think UT-Austin is slightly better. Bottom line: do not trust ranking too much. Visit both schools to see where is a better fit, both academically and socially. However, if you want to remain in academia after PhD, go to a place where you are more likely to publish (hence look at places that publish a lot).

Selectivity does not indicate strength of department. And have a look at this: http://www.scribd.com/doc/8508917/World ... etrics2008

Hey rbaobao! Fellow Canadian student here. SFU has a strong CS department, so I think you chance at U of T is good. Just relax during the interview. Being a coauthor, you should be ready to tell them what your roles in the project were. You don't have to know the interviewer's research, just a general idea is fine. Good luck! Let us know if you get in.

Some of the big names got their PhD in Cornell, and that was a long time ago (like in the 70s). I think UT-Austin is more research intensive than Cornell right now in CS. The reason that Stanford, Berkeley continue to be strong is because of its California location, which can keep professors there for a long time. Even UCSD, USC are rising quickly for this reason. So, if you want to work with world renowend profs, better think location!

Cornell used to be very good in computer science, but not anymore. I think it may be due to its location, which cannot attract many good professors. UT-Austin has a reputation in computer science, and is in a much better location. This is just my opinion.

heheman3000, I have some ideas of what I want to do, but at the same time I want to be open to projects in other areas. Nobody I talked to was doing the same area of research that I was doing in my undergrad. So I am kind of stuck, and have to keep an open mind. All the projects I heard were interesting, but it is hard to know if I will like a project without trying it out myself. My background (biochemistry and computer science) really allows me to do any aspect of computational biology. So it is more like I need advice on which research area to pursue, based on my talents & skills.

Just curious, what sorts of questions do you ask faculty members and graduate students? Some questions I asked faculties were: 1) what projects could I join (I had one prof who introduced me more than 5 of his projects to me!) 2) where do graduate students go after Phd 3) have students published papers yet The questions I asked students were things like courses, how difficult they were, where they live, and how many hours do they work in lab. What about you guys? Also should you tell faculties your other offers, so that they will be forced to tell you what is bad about other schools and what is good about their own school?

I guess I will start the second visit report. School: University of Toronto Visit days: Feb 27-28 Likes: location, convenience, right in downtown, very close to Chinatown, and there are a loooot of good restaurants in the city. Food is cheap. There are weekly festivals in the city over the summer, and it is a surprisingly clean and friendly city. Subway system is really really good. There were a lot of students on the visit days. Approximate number is about 50. Department was very strong. From the information session, the admission chair (who happened to be the very famous Graeme Hirst) said the school ranks high in total publications, and is among the best in the world. Turing Award winner Steven Cook also gave a talk. Graduate students seemed very happy. MSc program is 17 months, and Phd program is 43 months on top. So one could finish a Phd in 5 years. Dislikes: probably the weather. It can get windy at times, but it's not too bad. You can't really see any snow on the ground at this time. Financial aid is not too much for international students: 24K/year plus you have to pay tuition, which is about 6k. Other information: admissions offer will be made starting March 9

Depends where you are from, and what schools you are shooting for in US. If you are from China or India, and you shoot for top 10, better get your degree from Tsinghua, Beijing univs, or IIT of India. If you are shooting for Top 50, may be an average university with good LORS will suffice. If you are from Canada, your undergrad school does not matter much, research experience is key to getting into top 10.

I am not sure about this, but I think schools sometimes group waitlisted applicants into different sub-areas. If one student rejects their offer in sub-area A, then the next waitlisted person in the same sub-area gets accepted.

I know CMU has a pretty good program.

cons: your profs might think negatively of you and will not give you strong recommendation letters.

Congratulations! Any funding?

To decide, do a background check on every professor in the department, and find out where they got their PhD, and put their papers in Google Scholar to see how many cite them. I bet you will know their circle of friends once you searched a bit deeper.

Let me say, research matters most. GRE, especially verbal, is not important if you have research experiences (in the forms of publications) + good LORS from research professors.

I don't know much about McGill in this area. But I know at Concordia, Va

You gotta be joking. He's got a Turing under his belt.

alice, I see a strong Canadian presence on the conference link you provided. Even the chair is from University of Toronto. So go to U of T. If anyone is in bioinformatics, have a look at speakers list at this link: http://casb.calit2.net/bioed/.

Also look at the program committee of the top conferences in your field, what school they are from. These people review papers submitted to the conference. Alternatively, you can also look at the top journals in the field, find out the editorial board members.

True, leogk. Some of the professors I listed are not active in research: some shift attention to writing books now (Knuth, for example). Some are emeritus professors. But regardless whether they take students or not, their names tell us what area the school is good in. Likely there will be younger profs who are working in the same area. Seriously, a large percentage of graduates from Berkeley CS later got professorship at top schools. The school name is already enough a reason to go there.

A list of big guys that I read about: Database: Ullman (Stanford) Machine Learning: Mitchell (CMU), Moore (CMU), Jordan(Berkeley) Bioinformatics: Pevner (UCSD), Haussler (UCSC), Tidor(MIT), Berger(MIT), Gerstein(Yale) Operating Systems: Silberchatz(Yale) Algorithm: Knuth (Stanford), Karp (Berkeley), Papadimitriou (Berkeley) Computational linguistics: Fillmore(Berkeley), Hirst(Toronto) (My area is bioinformatics, that's why its list is very long).

No idea since I didn't apply there. Both have good CS department though.

U Toronto is the toughest school to get into in Canada, especially so for CS. But Canadians are an exception! I read somewhere that U Toronto has about the same admit rate as UT Austin.

I think both are good. But since I've been living in the east coast for a long time and I long for pleasant weather, I prefer Berkeley for a change. Unfortunately, I did not get into Berkeley, so I can only keep dreaming... For algorithm and theories, no question, Berkeley is the best, especially because Richard Karp, who used to be in University of Washington, is now at Berkeley. Also Christo Papadimitriou is there. Those people discovered many of the NP-hard problems! For AI, I am not sure about it. AI is pretty broad, depends on what area. If you are in machine learning, Berkeley is good since they have strong theory and statistics people there. For robotics, maybe CMU and MIT are better because they have invested more money in this area. Someone can correct me here...