Did I aim too high?(MSc)

[ev a.]

I am a student who recently graduated from university with 3.95/4 CGPA, have an electrical engineering degree, taken 5 additional courses to my curriculum to be able to fill some gaps in my CS knowledge such as programming languages, data structures, algorithms and computer vision courses. I am assuming my LOR's are very strong, as I have done projects and helped further the research of the professors I have worked with and they seemed happy to write a LOR on my behalf.

 

I have applied to Machine learning and computer vision areas, and currently taking ML, neural networks and computational geometry courses in graduate level (i started as a "special admit" student to my current university to not waste time waiting a full semester --and god forbid, if rejected, it's a safety net: i still can finish my MS here in my hometown). 

I applied to Stanford, UT Austin, Illinois, Gatech and U of Toronto in Canada, and EPFL in Switzerland for a MS degree, mostly without financial aid as an option (no scholarships if admitted).

Two things bother me: As almost all the top CS students rush into ML and AI, I feel it is harder to get an admit from these top-50 schools, especially with insufficient backgrounds (no OS course or formal CS research as of application date --currently I am working on a project under my MS advisor here), and with a non-CS degree. 

Did I aim too high and let my ego get the best of me?

 

Thank you for reading.

Edited January 29, 2016 by ev a.

[robot_control]

I assume you are interested in an MS and not PhD. If that is the case, why didn't you just apply for MS in EE? ML has very weak connection to CS compared to other areas. Much of ML is based on optimization and statistics which are integral to EE too. You could have just taken the appropriate ML electives and got away with an EE degree IMHO. This however changes if you want to do a PhD, in which case you should apply to the department of potential advisers. 

[ev a.]

@robot_control: mainly because the deep learning, neural networks and general ML and AI are in CS department in those schools that I applied to. Also, there is another psychological factor that I want to sever my ties with EE department as well

[robot_control]

@ev a. You seem to have very peculiar reasons specific to you, not sure if anyone here can provide a good feedback. If you felt your calling for deep learning early enough, and lost interest in EE, you should have switched streams. At the very least, must have taken enough courses to cover for lack of exposure.

If you feel anxious due to your lack of CS courses alone, it is understandable, but no point in fretting over it now. You'll get to know authoritatively in another 1-2 months. On the other hand, if you are anxious because ML/AI is very competitive at the moment - this is no secret. To be frank, I think you should have applied to another 3-4 programs. I regret not doing so myself.

The deep learning professor who interviewed me said that applications to his lab nearly quadrupled from last year. Even if I do happen to get in, I may not get to work on the area of my choice due to fierce competition among admitted students. I guess everyone is anxious due to the situation being fuzzy and messy.

[robot_control]

@ev a. If you don't mind, can you elaborate on why you want to sever ties with EE. Saying that CS is better suited is one thing, but saying you wish to sever ties with EE seems to suggest you had a bad experience. If you don't mind, can you share the reasons - I am curious. Also, are you by any chance a student at Caltech?

[ev a.]

@robot_controlThank you for your response. Actually in my school's CS curriculum, I only lack 4 courses in undergraduate curriculum, and trying to catch up with courses mentioned above that are directly related with the area. The reason I did not lean towards the CS area before is that EE curriculum is incredibly full as it is, and in fact the 5 additional courses on top of those was almost an unheard of, as far as I know. BTW, if your interviewer's remark applies to another schools, then it's safe to say that I'm screwed, oh well, at least the rejection letter won't be a shock. I think I wouldn't applied to any other program even if I knew this horryfing statistic. I love the probabilistic mathematical nature of the topic, and the vision course (which includes 20-30% of pattern recognition material inside it) I already took was great, I learned so much, which I can't say for my EE courses.

[ev a.]

@robot_control Sure. EE is asymmetrical, in the sense that a lot of work goes in, and nothing comes out from the point of an undergraduate student. Perspiration does not translate to an award, let that award be work satisfaction or an actual product. By far the largest project that I did was a 56k-modem that was implemented on an FPGA, whereas you can do a lot more and meaningful sh*t in another area, such as CS. Of course, this is obviosly grossly subjective, and for some others works is perfectly satisfying and enjoyable. As a recent graduate, I only can think how much more I could do as a CS student and an undergraduate researcher in that same 4 year span. (note: these are the ramblings of an angry ms candidate who just received some bad news, please don't  take it seriously if you wish to pursue a career in engineering -- it's lovely)

[robot_control]

@ev a. Sounds very similar to my own story  However, I knew from my sophomore year that I wanted to do robotics. Only later did I figure out that CS builds the brain for the robot whereas EE is more like the central nervous system. I associate mostly with the ICRA and IROS communities (and maybe CVPR) which do have decent representation from EE people. So I don't actively abhor EE, but given a choice will obviously pick CS. I however agree that much of EE undergrad curriculum is outdated and irrelevant for anyone who doesn't want to work in that particular space; while CS provides more *general* skills which are widely applicable. Best wishes for your apps