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Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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kingkong88 Offline
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Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Looking at MS CS (Thesis) options.

Work ex : 6+ years now
Companies : Samsung, Flipkart, 2 startups. Work was all non-research type, backend engineering. Rails, PHP, and some frontend stuff like Bootstrap, Jquery etc.

Startups were my own. The first one ended with a small acquisition, the other one did not work out.

Research work : 4 conference papers, 1 journal paper. Related to computer vision (CAPTCHAS). 1st Author in one of them.
I don't think either the journal or the conferences were highly ranked. This was all during college.

None of the research work was in Machine Learning or AI or any of the "hot" fields at the moment.

Non profit work at an animal shelter for a year.

From what I have read, all that matters is my GPA and my research work. The college percentage is low due to 1st semester mistakes, after which my score was substantially better. Since conferences don't have an impact factor, I do not know how they will be evaluated.

Rough shortlist :

CMU
Cornell
Stanford
University of Illinois—​Urbana-​Champaign
UT Austin
USC
Uni of Toronto
Uni of British Columbia
Uni of Waterloo
UCSD

EDIT : Removing USC because my GRE score is not valid there.

Adding
UCLA

Any suggestions on safe unis? NYU? UCD or UCSB?

I have a preference for Universities that give you the flexibility of turning your masters into a Phd with another 2-4 years of work. That, has been a little hard to get clarity on. I am not sure if I want to pursue a Phd, which is why I though of doing an MS and deciding along the way, hopefully getting the right research exposure in between.

Not interested in coursework only programs like MEng.

Reason for interest in thesis programs with possibility of Phd : To see if I am a fit for research work in the long term.

On a tangent though, I am concerned that corporate RnD labs are not what they used to be, Microsoft and IBM still have them but Intel shut all 6 of its labs down in 2011. Google has a hybrid model, and even Phds work directly on product stuff, not basic research like MSR(Microsoft research). HP Labs and Sun labs have declined quite a bit.

The massive hiring of Phds currently seems to be all focused on ML/AI. Whether this will last for another 6-7 years is anyone's guess, but trends change too quickly for this boom to last for that long (7 years is an eternity in CS).

Money is not a concern. High quality work definitely is.
(This post was last modified: 11-11-2017 05:06 AM by kingkong88.)
09-05-2017 12:07 PM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Gaussian is the best person to answer this.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
09-06-2017 08:31 AM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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The_Observer Thanks for tagging, my friend. I need a favor. Could you please let OP know your suggestion on his/her choice of schools? I mean the likelihood of an admit in particular, with OP's profile in mind. I am going to take care of the rest.

kingkong88 I have answered your questions below. Please feel free to engage me in discussion if you have questions (tag me).

Your strength is your excellent, hands-on engineering skills which no publication/GPA can match. For PhD this may not be that useful but for MS this may be. The_Observer can offer you further guidance as he is an expert in MS evaluation. I shall discuss with you about research, and long term career plan.

(09-05-2017 12:07 PM)kingkong88 Wrote:  Looking at MS CS (Thesis) options. Not interested in coursework only programs like MEng. Reason for interest in thesis programs with possibility of Phd : To see if I am a fit for research work in the long term.

I have a preference for Universities that give you the flexibility of turning your masters into a Phd with another 2-4 years of work. That, has been a little hard to get clarity on.

Your first priority would be to select a good school with a strong presence of computer vision faculties and coursework. Things are pretty flexible here, and you can always make changes in most of the cases. However, given the unusually high pace of technological advancement, being in a school with a large computer vision group is definitely gonna help you in the long run.

(09-05-2017 12:07 PM)kingkong88 Wrote:  Since conferences don't have an impact factor, I do not know how they will be evaluated.
It depends on the conference. Conferences like CVPR, ICCV, ECCV are treated on par with journal papers in CS (and computer vision) community. If your conference is not any of these mentioned but is primarily a computer vision conference (e.g., ACCV, ICVGIP), even then you may expect some credits associated with your application.

Regarding the choice of schools from research standpoint, all the US schools you mentioned are excellent for anything in computer vision! I am not much aware of the Canadian schools except UToronto, which is always exceptional. The chance of admit with your profile is a different issue that The_Observer can highlight.

(09-05-2017 12:07 PM)kingkong88 Wrote:  On a tangent though, I am concerned that corporate RnD labs are not what they used to be, Microsoft and IBM still have them but Intel shut all 6 of its labs down in 2011. Google has a hybrid model, and even Phds work directly on product stuff, not basic research like MSR(Microsoft research). HP Labs and Sun labs have declined quite a bit.

That is research. If the research ceases to be contemporary and loses its impact, the end does not seem far. A company needs to reinvent itself with new tech, new disruption, and new market. Intel, a computer vision pioneer (opencv!), is now struggling after missing the train whereas Nvidia, a gaming company, spotted the wavefront and is re-emerging as a key player in computer vision. The GPUs won over the threads!

Can we see Intel making comeback with IoT? Time will tell, but my point is, research by definition is self-destructive. Like the Phoenix bird in Greek mythology that jumps into fire in order to be born anew, research has its repetitive life cycle - it destroys its old self by bringing in the new tech. The development of today's industrial machine learning algorithms, from support vectors to deep architectures, had taken place in some form or the other in AT&T Bell Labs. Where is AT&T now? Same applies to Sun, Oracle, HP. Old R&Ds die, new R&Ds emerge, companies re-invent themselves. The companies may decide and change how they would use their R&D units, but the fundamental principles of research remain the same.

In a disruptive world, markets saturate and profit margins shrink. You can not continue with the old markets on and on. For example, look at smartphone market. Globally, the smartphone sale is shrinking. Similar observation holds for desktop PC sales, and of course, the mainframe is dead. This is the reason phone or digital device manufacturers are increasingly turning into service based companies. Data is growing, analytics is creating new market. In this context, Microsoft has made a spectacular turnaround (at least so far) by reinventing themselves into a cloud based service company. IBM too is a new IBM at present - it has shut down all (almost all) its hardware business and it is aggressively hinging its fortune upon cloud and analytics (with IBM Watson as the nerve center). Though late, but Apple has also followed their footprint.

Coming back to your point, not all hype is bad: hype creates excitement and hope, and money flows in (corporate investment as well as federal). As a result we scientists and developers earn our bread and butter. As a result new tech is developed. New markets emerge. You need to use your experience and acumen to winnow the wheat from the chaff. The question is, how to survive in such a hostile environment. Read on.

(09-05-2017 12:07 PM)kingkong88 Wrote:  The massive hiring of Phds currently seems to be all focused on ML/AI. Whether this will last for another 6-7 years is anyone's guess, but trends change too quickly for this boom to last for that long (7 years is an eternity in CS).
I know in the age of disruption it is hard to keep up. But that is what technology life cycle is, that is what research is. Can you imagine I had to change the course of my PhD three years into it? With all my frustration when I met a smart young faculty at CVPR, and ranted about this changing landscape, he just said, "Adapt to it. I am doing the same".

Let me take the cat out of the bag: the way you survive "the trends changing too quickly" is by swimming at the wavefront. If you are already there, at the vantage point, you are gonna be the first person to see the change of tomorrow. And you will be able to leverage it. New tech emerges by riding on the limitation of the old. You need to be up to date with the current tech in order to make first use of the new one.

Adapt to it. Hype is not always bad. Not all hypes are bad either.

Gaussian

There was an old man of Esser,
Whose knowledge grew lesser and lesser,
It grew at last so small -
He knew nothing at all,
And now he calls himself a researcher!


I do not evaluate MS profiles
(This post was last modified: 09-08-2017 12:54 AM by Gaussian.)
09-07-2017 03:59 PM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Of course, Gaussian!

CMU - mod
Cornell - mod-ambi
Stanford - ambi
University of Illinois—​Urbana-​Champaign - ambi
UT Austin - ambi
USC - safe
Uni of Toronto - ambi
Uni of British Columbia - mod-ambi
Uni of Waterloo - mod-ambi
UCSD - mod

With a profile like yours, I see no reason why you shouldn't be able to get into most of them. That said, you should also consider applying to some other great schools such as GaTech, Columbia, Penn, Michigan, Berkeley, UNC Chapel Hill, UCLA, and even the likes of MIT/CalTech if you're interested in the research being conducted at those places (and I can't tell you which ones would be suitable for your profile, because Comp Vision isn't my area of interest/expertise).

P.S.: kingkong88, please see point #1 below.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
(This post was last modified: 09-07-2017 09:57 PM by The_Observer.)
09-07-2017 09:37 PM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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(09-07-2017 09:37 PM)The_Observer Wrote:  That said, you should also consider applying to some other great schools such as GaTech, Columbia, Penn, Michigan, Berkeley, UNC Chapel Hill, UCLA, and even the likes of MIT/CalTech if you're interested in the research being conducted at those places.

I don't know about OP's specific field of interest but each one of these schools should be a dream to get into. All of them have great faculties with excellent coursework and numerous opportunities for research. Computer vision, AI, machine learning, almost everything is great in these schools.

Gaussian

There was an old man of Esser,
Whose knowledge grew lesser and lesser,
It grew at last so small -
He knew nothing at all,
And now he calls himself a researcher!


I do not evaluate MS profiles
(This post was last modified: 09-08-2017 12:46 AM by Gaussian.)
09-08-2017 12:46 AM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Thank you for all the inputs, sorry I couldn't update earlier.

I have added all the information on my profile : http://www.edulix.com/unisearch/user.php?uid=338056

I have also added my research papers to the Misc section, since they play a heavy role in my profile.

I have removed USC since my score won't be valid there. I have added UCLA.

Will make one final adjustment.
11-11-2017 05:17 AM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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The_Observer Gaussian I have updated my infobank with the research work I have done. I was hoping you'd be kind enough to take a relook and tell me if that changes anything.
(This post was last modified: 11-13-2017 01:44 AM by kingkong88.)
11-12-2017 10:47 PM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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I'd defer to Gaussian on this.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
11-16-2017 02:59 AM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Any suggestions for safe universities The_Observer?

Would any of these be safe ?

UC Irvine
NYU
Simon Fraser
Uni of Alberta
11-16-2017 03:58 PM
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RE: Fall 2018 | MS |CS|GRE 333(Q-167/V-166)|CGPA 69.6%| DTU
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Not in the least.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
11-16-2017 04:38 PM
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