compscian

Hi @perpetuavix thanks for all this info I am 90% sure at the moment about attending UW, which I absolutely love due to research fit. A few things are holding me back though: Columbia has given me a TON of money and a 4 year fellowship, so that's definitely something to consider. Also, the earthquake thing is at the back of my mind too. Are you paying $1200 for the entire apartment, or is it your share alone (i.e. total cost is $2400)? If I decide to live in a neighborhood close to UW and want an apartment to myself (1 BR), what can I expect to pay? Given my salary of $2200-ish, I'd say my budget is around $1000-1300. Thanks!

Yes, the quality of education will likely drop. See this: https://www.quora.com/What-impact-will-the-University-of-Wisconsins-recent-changes-in-tenure-and-funding-have-on-their-ability-to-recruit-faculty From the point of view of a new faculty, most wouldn't want to go to a place where they cannot get tenure. There is very little incentive to choose UW over some other university or even an industrial lab! However, I don't expect established faculty who have been in Madison for many years to just pack up and leave. They would have strong ties to the university and city. Hence, they'll try to stay back and fix the system as opposed to leaving. However, don't expect any influx of talent to join the university anytime soon.

@b-man Stanford is definitely very strong in those areas, right there at the top along with MIT, Caltech, and Berkeley. I must however warn you that digital signal processing is dying a slow death with everyone switching to statistical inference or compressed sensing type problems. I think Prof. PP Vaidyanathan is probably the only DSP-proper researcher who is active. UCSD is also very strong in communications and the new-age signal processing. If you can make sure that (a) you will have access to a lab of your interest (never take it for granted at top univs, especially if you don't have an outside fellowship); (b) you have no problems with funding; (c) you are confident about doing very well in quals (Stanford is notorious for it) - you should probably go to Stanford. If even one of the above isn't guaranteed with high probability, I'd go with UCSD primarily because of the 3-year fellowship, and also because it is definitely good for your research area!

@b-man What is your area of interest? I'd assume the choice will also depend on that. For example, Stanford is very strong in many areas, but not all. In areas like control theory and others, EPFL and UCSD are stronger. CMU also has its strengths, but there isn't much reason to choose it over Stanford in ECE. A few more things to consider: At UCSD, you have a 3 year fellowship. This means financial independence from your adviser for three years, which will make you an attractive candidate for the best of professors at UCSD. Even if things don't work out for example, there is absolutely no pressure since you are financially secure. Thus, you can take your time, interact with many professors and pick the absolute best at UCSD. However, if your only problem with Stanford is low stipend, you shouldn't be too worried. Most students there do summer internships which pay a lot. You can save this up to cover your additional expenses throughout the year. The qualifying exams on the other hand is a real concern.

True. I just checked that one of these guys had a fellowship and hence was eligible to work for a few hours and get additional money. Anyway, that is beside the point. What I wanted to convey was that money shouldn't be given excessive importance (mode of funding is very important though, IMO). As long as tuition is waived and a modest stipend is guaranteed, I wouldn't fret too much over $100-250 a month. Also, in many areas of STEM, particularly in CS and EE, I haven't really heard anyone complaining about poor standard of living due to low stipend. There are many internship opportunities over summer which pay handsomely, which you can save up to spend over the course of the year. Summer wages also tend to be higher in universities, if you wish to stay back (this might depend on university though). I would pay much closer attention to climate, number of top PIs working in my area (3 would be safe), and overall fit with the university. I will never disregard non-academic factors as you can clearly see from my comments. However, it would also be a bit naive to think that research excellence doesn't matter. If you had gotten into MIT, I am sure you wouldn't be discussing these issues (unless of course, you also had offers from UCB, Stan, or Caltech). So, it is a matter of trade-off, and each person has a different Pareto optimal curve. It's possible that your advisers perceive UIUC as significantly better than UCLA, while you disagree (and I'd agree with you). What is important is finding your Pareto optimal curve, and not that of others.

@TakeruK Thank you for all this info When I spoke to a few PhD students at UW and Columbia (all internationals), they gave me a picture that it is possible to get additional money by doing additional work. Of course, you cannot work for more than 20 hours a week on F1 Visa. I believe what they did was grade some papers/projects (for their adviser's course) and got a raise in RA, which the adviser can do. One guy helped to design a web-page for a new research lab, and got paid for it. Not sure how the accounting was done in this case though. I just wanted to make a point that if at all additional money is required, there are possibilities. These aren't written in stone unlike other factors which I mentioned in my previous comment.

Hi @Sura Definitely agree with the above. You also have a pretty solid list of secondary factors there, which though non-exhaustive, cover most of the important factors IMO. I'll also put down my thoughts and it would be interesting to get feedback from others. I'd definitely pay attention to the funding package. Fellowships provide greater opportunity to explore and pick the perfect adviser. Even if you know whom you'd love to work with, and the person has agreed to take you, it's still possible that bad things might happen. For example, there could be clashes in personality, work-ethic, cultural issues etc. These are hard to predict without actually working with said person, and hence financial independence for at least the first year is a big bonus. Some universities have heavy teaching obligations (1 sem or quarter every year); some others provide funding packages where you don't have to teach if you aren't interesting; and some roll out the red carpet. These are important considerations too. I got a 4 year Armstrong fellowship from Columbia which pays a LOT and gives me complete freedom with zero obligations. I was heavily leaning towards UW, but this has made me think again about Columbia. I think "fixed" factors should be considered with higher priority. For example, you are annoyed with traffic and long commute - pretty easy to get another apartment. Need an additional $250, easy to get some grader or web admin position which aren't very time consuming. Unhappy with research area or adviser, much harder (without fellowship) to change. Unhappy with the climate or "culture" - impossible to change.

Hi @deborah_caf I'm assuming you are also from IIT. Hostel life in IIT is a lot of fun, but for grad student life, it's probably better to live alone. I think it would actually be beneficial to live in places where post-docs live and get into the adult world. I was accepted to UIUC last year. Funding and housing are basically non-issues. You'll have very comfortable living standards, so congratulations and best wishes for a great PhD experience.

Do you really want to do a PhD, or is your objective to work in the industry after MS? If it's the latter, the obvious choice is to go for Stanford. You'll have to take out a loan, but since you'll be working after two years, you can pay it off easily. Stanford in general offers more employment opportunities due to its brand recognition and location in the Bay Area. If you want to do a PhD: it's a bit tricky. Are you happy with doing a PhD in GIT? It's definitely a top 10 program and well known throughout US and many other parts of the world. If you are happy with the professors in GIT, you should go there. It's very hard to switch from MS EE at Stanford to PhD. Also, I would advise against taking a loan since you'll be studying for the next 4-6 years and hence cannot pay it back soon. The financial pressure which will result from the loan is not worth it. If you are very unhappy with the professors at GIT, you can try and do an MS from Stanford and apply for PhD programs again. However, there is no guarantee that you will get into a PhD program better than GIT after your MS. I personally wouldn't take the risk. I'd follow the money and go to GIT.

Hi @blubed I by and large agree with you. Everyone should look at the factors that are important to them, and I just gave a non-exhaustive list of example factors. However, not all factors are equal. Some of them are completely within a student's control (where you live, how much you spend etc.) whereas others are completely outside (climate, available professors, course requirements etc.). There are of course a number of factors which will fall in between. I would generally pay more attention to the hard or fixed factors. If you don't like a longer commute, it is certainly possible to find a place closer (at possibly higher cost). If you need additional money, it's easy to get a grader or web administrator position in the university which are not very time consuming. These are things you can adapt on the fly over the course of 5 years. Not happy with an apartment, pretty easy to change. Not happy with an adviser, much harder to change. Not happy with the climate, impossible to change! Also, in engineering, math, or stats - money is never really an issue. All programs I am aware of provide more than enough for even lavish spending. It's also possible (and encouraged in Seattle) to do summer internships which pay a lot (close to $6k per month). OP has a specific case where his wife can't work due to visa issues. IMO, this isn't a deal breaker, but you can always choose to disagree with me.

Totally agree with @juilletmercredi I may have a sampling bias, but based on my interaction with a number of current grad students and recent alumni from UW, Seattle is one of the hottest tech hubs in the world at the moment. It is probably second only, or even comparable, to the Bay Area. For people interested in applied math, statistics, data science, machine learning, and the likes; Seattle seems a wonderful place with lots of opportunities. Jobs are available everywhere. However, if you consider quality and type of role, the best research labs are in the Bay Area, Seattle, or NYC. It's definitely a big plus to be geographically located at these places to secure internships or collaborations.

Some circumstances you describe are field specific, so if you state that clearly, you might have more appropriate comments. One point to consider is that when choosing among equals for objective, I'd choose the one with the lesser constraints/commitments. You say A would require you to do some work, while B would not - in which case B is by default better since your interests could change. For example, you may realize that you don't want to do that comparative study, in which case B will be better. If you still want to do it, I'd assume B will allow you to do the same. Hence B is at least as good as A. However, if you feel that you are not 100% sure about doing a PhD, or doing it in B, then A is a safer option. It would give you an easy out option if you realize your calling for something else later. Of course, you would have to reapply, and there is no guarantee that you will get the offer from B again. There is nothing else people here can offer you. You need to figure out the probabilities for the above scenarios, and choose the option which would hedge your bets wisely.

Hello everyone, I have mostly decided to join UW. Just a few questions before I finally make up my mind: I have been offered a monthly stipend on $2250 pre-tax. Considering the cost of living, is this enough for a comfortable living? If I share an apartment with someone else (2 people in 2 bedroom apartment) - how much is it likely to cost me? I fear that I may be underpaid since a few from CSE and EE reported higher stipends last year. If someone from CSE, EE, or other engineering departments are out there, can you please share your comments? Most importantly, should I be worried for my safety, life, or livelihood due to the disaster prone nature of the city? UW is great and all, but I wouldn't want to put myself in a big danger. @Tigris any comments?

Hello everyone, I have been accepted to EE PhD programs at UW-Seattle, UT Austin, and Columbia. My research interest involve machine learning and optimization algorithms. I have been given RA/TA at all three places (TA for first term) and can pick adviser after arriving. UW and Columbia have very flexible programs where I can take courses and have advisers across CS and Stats in addition to EE. UT seems a bit more strict with requirements, with funding being a concern. It would be great if someone can discuss the strengths and weaknesses of these programs on the whole, and ML in particular. Even though I would have EE as my home department, I plan to associate myself primarily with the CS community - both coursework and adviser selection. I like the city of Seattle a lot, which is a great place for machine learning - comparable to the Bay Area. However, UWEE doesn't have a high overall ranking, even though it is highly rated for ML. Should I be concerned about this? I would like to go the academia route post PhD, but I am also very open to research positions in good labs

Moderators: Please close this thread. I'll be opening a new one. Thank you.

@Sura If you are happy with the POIs assigned, and have no preference among them, the next step would be to compare the programs on the whole. This can be coursework, flexibility, attrition rate, qualifying exam pass rate, summer internships, and most importantly the climate and your compatibility with it. On some of these, UIUC is better, while on the others UCLA is better. Depending on how important the above factors are (very subjective), different people are likely to choose different universities. I was admitted to UIUC last year (for MechE, again top 6-7 by rankings), talked to professors, and loved it. I was developing an interest in ML and signal processing at that time, and was told that I can work with nearly anyone in CSL - which is definitely comparable to LIDS, ISL, or CITRIS at top universities. However, I was totally put off by the climate. This also seems to be the trend with many universities which aren't in the best of localities (UIUC & Cornell, in particular), where many professors are leaving for greener pastures. Hence, it's very possible that by the end of your PhD, UCLA is ahead of UIUC in rankings.

Bumping thread again. Eagerly awaiting responses.

@Sura Congrats. It might be beneficial to state your research area too. UCLA is very strong in RF, devices; while UIUC is good in signals & systems. However, the classification is soft - the systems group (Ali Sayed, Vandenberghe, Soatto etc.) at UCLA is obviously strong too. However, UIUC is definitely the superior brand by a long way. I would also give a lot of importance to living conditions, flexibility of program, and the community in general. For example, some programs are notorious for making students take irrelevant courses in the name of breadth requirement. Some programs weed out many students after qualifying exams. You should also consider the "community" - e.g. conference vs journals; applications vs algorithms; proof-based vs computational etc. If you are very specific about academia, UIUC is likely to offer more based on track record. UCLA feeds primarily into the industry in SoCal. However, LA beats Urbana by a long way - weather + urban facilities + large Indian population.

I think it depends on the "flavor" and community you wish to associate yourself with. If you prefer the more mathematical statistics and probability theory variety; associate yourself with the Annals of Statistics (journal publishing) community; and prefer to work in actuaries, finance, or as a professor - U Chicago might be a better option. On the other hand, if you prefer the more computational statistics and machine learning variety; associate yourself with conference publishing style at ICML, NIPS, KDD etc.; and prefer to work as a data scientist in tech firms (MSR, Amazon etc.) - UW is definitely a better option. The classification is soft though. For example, TTIC comes up with great papers in NIPS and ICML regularly, and you could possibly tap into that resource if you decide to go to UChicago. Similarly, there are more traditional statisticians at UW too. However, if you are interested in machine learning and taking a number of CS classes in addition to stats classes, then UW is the way to go.

@blacknighterrant What you describe is a backdoor way into the PhD program, which doesn't always work out. Not to discourage you, but a good fraction of people I know who tried this ended up disappointed. In general, you would need a letter of support from a faculty member willing to take you, in addition to good standing in coursework and research. It's hard to get a research adviser if you want funding from him (he might as well take a PhD student). TAing while taking courses and doing research is simply too demanding. I'd go to a place which is offering me financial support for the first semester/quarter. Talk to a few professors over this time, and try hard to find an adviser to work with from the next term. If UCSD is offering you this deal, I'd simply take it. With regards to GATech, this is hearsay, but I believe they admit a whole lot of students and make the quals very tough to kick out many.

Makes sense. I have been through this for two years now, and I'll tell you how this usually plays out. You subconsciously attach yourself to a university (instinct, gut feeling, whatever). Then you try to find N number of faults with the other universities without paying any attention to the positives, while also adding blinders to the weaknesses of your favored program. This is a wrong way to go IMHO. If you feel that stipend at Seattle won't be enough, and this is a deal breaker, you should just go to Madison.

@vadupleix I am a bit concerned about the direction of this discussion though. Looking at housing difficulties and commuting times as criteria for choosing a university is bad IMHO. I'd rather pick the university based on potential advisers, course offerings, climate, employment opportunities etc. Housing and stipends are minor obstacles, and easy to overcome as you encounter them. On the other hand, if your mind is set on Madison, then don't try too hard to find reasons to strike Seattle off your list. Sometimes it's better to follow your heart/instinct. However, from an objective point of view, nothing here suggests one over the other. I can assure you that based on my conversations with 4 different people at UW - money is not an issue. CS/EE (and presumably math) provide funding for 9 months with close to $2300 pm. Most said they were saving nearly $500 even after very liberal spending. However, none of them and myself have ever been married..

Hi. I am choosing between UW, UT Austin, and Columbia. I have mostly eliminated Columbia for research-fit reasons, and I don't want to live in a cold place. Choosing between UW and UT, and it's extremely hard. I think that living conditions would be the primary deciding factor. Being international, I cannot visit. Can someone here possibly compare Seattle and Austin? Also, a number of my friends have been poking me about earthquakes in Seattle. Whats the reality? Is Seattle a disaster prone and unsafe city at the moment?

But salaries are adjusted for cost of living rite. For example, UIUC pays even their top grads only around 1800$ per month, U-Wash pays around 2200$, and Stanford/Berkeley/Columbia pay close to 2800$. After accounting for cost of living, all of these offers lead to the exact same standard of living. @vadupleix Another important consideration is the climate. Seattle and Madison are very different. If you like one a lot, you are likely to hate the other. This in my opinion is as important a consideration as job opportunities or advisers.

Bumping thread again. Someone, anyone?