4 ms·

Ask HN: Thoughts on grad school? (CS PhD)

To give a little bit of background about myself: Although I took some CS courses in college, I didn't seriously consider myself a programmer until just over a year ago, when I started writing code as a quant at a hedge fund and realized that, when using the right languages and working on cool problems, programming can be a lot of fun. I've also realized that there are many people a lot better at it than I am, so I have a lot to learn about technology and computers. Among my interests are artificial intelligence and programming languages, so I figure that graduate school might be the way to go. I'm interested in AI/machine learning research, which practically require a PhD, even in industry. I've also considered the entrepreneurial route, but I lack a certain technical maturity as well as co-founders, both of which I could find in grad school. Eventually, when I'm in my 40s, I'd like to be involved in VC... but I'd like to spend the next couple decades doing more detailed technology work so that, when I get there, I understand what I'm analyzing. So, given my interests and career aspirations, I'm considering pursuing a PhD in computer science. I'm wondering if anyone here could give me some perspective on what to expect. Here are my credentials. I'd like to know what I can expect in terms of admissions success. Are, for example, top-10 departments a possibility? 3.9 / 4.0 in-major (math) from top liberal arts college. CS courses: AI, PL, Software Eng., Data Structures, Intro. Grades of A/A- in all but SE. GRE (2004): 800Q/670V, 98% on math subj. test, have not taken CS subj. test. Top 100 finish on Putnam. Research: Two internships in applied math, but in a govt. context. Consequently, I have no publications, so this may be a weakness. Career: Entered pure-math grad program in fall 2005. Passed quals but did poorly in courses. Left after 1 year (no degree) to work on Wall Street, starting 5/2006. Worked on WS up to 2008, with a reasonably successful career and 1+ year of programming experience, but no research or publications (obviously). Specific questions are: 1. How much is it going to hurt me that I entered a PhD program and left? Is this a deal-breaker, or can I explain it away? (My reason for leaving pure math is that I realized the academic job market sucked, and that I was already qualified for a decent industry job. However, a CS PhD carries a lot of benefits outside of academia.) Could I possibly turn my grad school experience into an asset, noting (in spite of my lack of success, and departure) that I've been through the experience before and know what I'm getting into? 2. Ideally, I'd like to get an NSF or equivalent fellowship, but I have no hope of getting that without research experience. Is it likely, outside of the ivory tower, that I can hook up with a mentor and get to work on a problem so that, when it becomes time (12/08-2/09) to apply to schools and for fellowships, I'm on the ball? 3. How much does the distinction between top (5, 10, 20) schools and the rest matter in CS, assuming that I will not be seeking academia? Do AI research groups care about the distinction between #1 and #8 and #22? If I pursue the entrepreneurial route, are higher-ranked schools going to have better co-founders? 4. The most important, but most distant question: What can I expect once I am in graduate school in computer science? What are the courses, students, research opportunities, and career possibilities like?

hsu 18y ago
I can help answer #2 and #3. #2. I received an NSF fellowship in grad school with 6 months of research experience. The experience probably helped, but getting an NSF is a long shot no matter what. I know of other students with similar qualifications who didn't get it. #3. The prestige of your grad school matters in some circles but not in others. If there are particular companies that you want to work for, try to find out what their hiring practice is. Some companies place a high value on the school you graduated from, and some don't care at all.
lbrandy 18y ago
Just FYI, I have an MS in EE and I work at a pattern-rec startup. So, no PhD not really required to get a job in that field. That being said, having a PhD helps alot if you want to take on the 'scientist' role right off the bat (for example, my job duties have included things like optimizing the algorithm both computationally and algorithmically). Your stats look fine for applying to CS PhD. Top 5 is probably a long shot (but it always is). But, they love math backgrounds. The only problem is no publications. Top tier CS schools virtually require a strong research background. 1. It's probably going to hurt more than help, to be honest. Even though EE and CS and the like -do- have industrial applications, the people who are reading your application chose to stay in academia. That means they don't necessarily look kindly on people diminishing that. My suggestion say "financial obligations" and leave it at that. The key is to seem really really really really excited about CS and that's why you are applying. 2. This is a serious longshot. 3. AI research groups will care alot more about your research than the school. And yes, top tier schools will tend to have smarter people and therefore better co-founders. Any "decent" school though will have plenty of smart people. 4. The money is there at any CS school so you'll more then likely go to school for free and work on funded research projects. The career possibilities are as good as they get with any PhD.
- time_management 18y ago
  Which is the longshot, finding the mentor or the NSF? My experience is that top departments, and fellowships like NSF, basically want people who are already grad students. Actually, NSF seems to have more to do with the merits of the research problem than the student, per se. I don't think I have a shot without enough research experience to have a rough idea of what "my problem" will be.

hsu 18y ago

I can help answer #2 and #3. #2. I received an NSF fellowship in grad school with 6 months of research experience. The experience probably helped, but getting an NSF is a long shot no matter what. I know of other students with similar qualifications who didn't get it. #3. The prestige of your grad school matters in some circles but not in others. If there are particular companies that you want to work for, try to find out what their hiring practice is. Some companies place a high value on the school you graduated from, and some don't care at all.

lbrandy 18y ago

Just FYI, I have an MS in EE and I work at a pattern-rec startup. So, no PhD not really required to get a job in that field. That being said, having a PhD helps alot if you want to take on the 'scientist' role right off the bat (for example, my job duties have included things like optimizing the algorithm both computationally and algorithmically). Your stats look fine for applying to CS PhD. Top 5 is probably a long shot (but it always is). But, they love math backgrounds. The only problem is no publications. Top tier CS schools virtually require a strong research background. 1. It's probably going to hurt more than help, to be honest. Even though EE and CS and the like -do- have industrial applications, the people who are reading your application chose to stay in academia. That means they don't necessarily look kindly on people diminishing that. My suggestion say "financial obligations" and leave it at that. The key is to seem really really really really excited about CS and that's why you are applying. 2. This is a serious longshot. 3. AI research groups will care alot more about your research than the school. And yes, top tier schools will tend to have smarter people and therefore better co-founders. Any "decent" school though will have plenty of smart people. 4. The money is there at any CS school so you'll more then likely go to school for free and work on funded research projects. The career possibilities are as good as they get with any PhD.

time_management 18y ago
Which is the longshot, finding the mentor or the NSF? My experience is that top departments, and fellowships like NSF, basically want people who are already grad students. Actually, NSF seems to have more to do with the merits of the research problem than the student, per se. I don't think I have a shot without enough research experience to have a rough idea of what "my problem" will be.