text:
As someone with low grades how can I prepare myself to study MSc in CS in USA?
I have completed Bachelor in IT from a third world country in 2008. I have achieved 49% marks.
I am 30 and working in a bank.
Now I want to study MSc in CS in the USA and eventually PhD.
I believe that this world is not all out for me.

How can I prepare myself so that I can improve my chance of admission in post graduate level?
Money/GRE/TOEFL/IELTS/Vendor Certification....what should I need?
how can I show that I have potential research capability?

TOEFL is must. GRE can be helpful. Vendor Certification is kind of useless. You need money anyway. You're missing the most important thing, how do you show that you have the research capability?

There are two types of computer science master's degrees in the US.  One requires only taking classes and is generally considered terminal; this is often called a "professional masters".  The other requires writing a thesis and is generally considered a gateway to the PhD.  Which are you interested in?

+1 for a good question (interesting and well-formulated) AND for a great attitude. Unfortunately I have no experience with grad schools in the U.S. (besides the TOEFL/GRE tests) so I can only wish you the best of luck.

While wish it wasn't true, money is generally enough. While I don't have a reference, donating a building will substantially improve your chances of getting admitted.

Yes, you can do it, just keep your passion up. There is nothing which can't be achieved. You need a continues hard work meanwhile Everyday. Don't forget Phd is just a degree, and we are humans who can do it easily. Its not like you have to travel to another galaxy meanwhile that is possible too.
Be good, Thanks God. Good luck

Since you intend to do it on CS I want to point out that the GRE Subject Test on CS (the one usually asked) will not be administrated anymore.
According to the ETS website:

The last administration of the GRE Computer Science Test will be in
  April 2013. The test will be discontinued after the April 2013
  administration. Scores will continue to be reportable for five years.
  (https://www.ets.org/gre/subject/about?WT.ac=grehome_gresubject_121017)

I wanted to say this in a comment (since it's not exactly an answer, but I think it's an important information to you), but I can't since I don't have enough reputation on this website to do it :(
Therefore, even though I think you wanted more a opinion from people already in academia, I feel obligated to put some more thought on my answer:
I'm a student, currently undergrad (will graduate at the end of this year) and I'm "kinda on the same boat" (from a third world country, wanna do a Ph.D. on in US in CS and I've being somewhat lost regarding what to do).
Here is a compilation about what I have found so far that may be helpful to you:
The notions of PhD and MSc in the US may be somewhat different from what you are used to. Quoting from something I've read in a university website (can't remember which one right now) "Masters is about breadth, PhD is about depth".
At least in my country (and I'm guessing it may be the same for yours), both are pretty depth-oriented. -> Keep in mind that, some MSc are breadth oriented, these may not be the droids you are looking for.
Also, the programs vary a lot from place to place... (And if you are used to the fact that you have to do a MSc prior to the PhD, this is not true for a lot of PhD programs in the US, you can join then directly if you have a bachelor's degree).
Example: At CMU, the masters degree is "breadth-oriented", meaning that you take a lot of advanced courses in various topics, and the PhD is totally research-oriented (average 6 years, in contrast to the average 2-year MSc + 4-year PhD in my country). But in MIT, as far as I've understood, you apply for grad school, if you are accept and you don't have a MSc, you are put on a MSc program, if you already do, you are put on the PhD program (so, seems to be a lot research oriented on both programs). -> Make sure you read thoroughly how the programs in the universities you intend to apply are, cause there's no "standard".
About the "money" part of your question, as far as I've seen, it goes something like this:

MSc: You have to pay for tuition, you may get a paid TA-ship
(Teaching Assitant paid position), you may get an RA-ship (Research
Assistant paid position), but nothing is guaranteed.
PhD: Top universities usually pay you monthly and if the professor    that is orientating your research doesn't have funding, you need to      get an RA or TA job. On other universities,you may need to narrow       your options to professors that have funding.
-> Keep in mind that, PhD is a better option money-wise, but harder to get in.

As pointed on the comments, research capability is a must (for the "depth" programs at least) and matters even more than grades. Quoting from a CMU professor on the "Grad School Talk" available at their website:

It does not help you, in my opinion, to be closer to 4.0 [GPA] as
  opposed to 3.5. It’s a much better idea to spend your time on research
  than on optimizing your GPA.

- Keep in mind that proving your research capability matters a lot.
But another important quote from this same pdf regarding grades is:

Your grades may be somewhat low – under 3.0 – because you were having
  a good time in college and you may therefore be having trouble getting
  into a Ph.D. program. In this case, you may want to do an MS and use
  the time to boost your grades and reapply after the MS.

Another important thing to note: The things that each program prioritize when looking at your application seem to vary a lot, even among programs at the same university/department. -> Try to figure out what the programs you are aplying prioritize. (eg: by reading their websites well).
About TOEFL: It matters a lot, but as far as I understand, it matters in a sense that it prevents you from getting in a program if you don't have the minimum score needed. *Each university asks for a different TOEFL score.*
The top universities (regarding CS programs) usually ask for 100 on the IBT (internet based test, out of 120), an exception being Stanford, that asks for 110.
Regarding IELTS: All universities seem to accept TOEFL, a lot of them seem to accept IELTS, but you need only one of them, so I suggest you go for the TOELF (for US universities).
As a plan of action, I suggest this one (which is kinda what I'm doing myself).

Boost your ability to prove "research capability": It's VERY important that you have some prior research experience. Have you ever done research as an undergrad? Do you have professors that can write a recommendation letter for you? If you don't, you are (probably) gonna need to pursuit this kind of stuff. My suggestions if this is the case: Pick a professor that does research in a area that you are interested (better if it's a professor that may remember you from university) and try to contact then to see if they can let you assist on any research projects (even if voluntarily), or take some time to read his recent published papers and understand then, then go talk to him about this. Also, try to see if getting a job at any private research company is an option (in case they exist in your country, in mine "private research" is pretty much nonexistent :( ).
Figure out what your "level" is: What universities/programs that you want to get into that you can realistically hope to get in. This can be done by reading the programs/universities' websites, search for some information about the qualifications of people that got in, etc.
Make a list about the programs you are interested in: After figuring out your "level", what universities from this set have programs that you are interested to?
Read everything you can about this programs and pick the ones you want to apply: Learn what these programs prioritize on applications, what options do you have regarding money, etcs. Finally decide which ones you are going to apply and see what each of then require.
Get ready for the aplications: Taking the GREs (or whatever they are gonna use, now that the CS subject test is gone), TOEFLs and bla bla bla takes a lot of time. Prepare for the stuff you need to take, search for example tests on the internet, study for them, etc... and take they as soon as you are ready.
FYI: As far as I've seen, the deadlines for applying for grad programs are usually in December, for pretty much all universities (they gotta have something in common, after all).

Some useful stuff to read:
 -

CMU's "Grad School Talk" www.cs.cmu.edu/~harchol/gradschooltalk.pdf -
The one I quoted a lot in this answer.
Demystifying the American Graduate Admissions Process: nlp.stanford.edu/~rkarthik/DAGAP.pdf - I found this paper extremely
helpful, it's written by a guy that worked on Stanford's admissions
committee, he also has a blog where he talks about this stuff (link at the end of the paper).

Additional Notes:

In case you are unfamiliar with how the GPA works in the US, here is
some explanation:
http://www.ehow.com/how-does_4619318_a-gpa-work.html
If your grades are low, it may be hard to enter the top universities (although I don't see it as impossible) but keep this in mind: A) A lot of "not the top, but good ones" are very good, and may even be very strong in research at an area you are interested in. B) I believe that any recommendation letter saying something like "This guy showed up out of nowhere wanting to assist in my research (even though he was out of academia for some years and was working on a regular job) and helped a lot" shows a lot of "research capability", a lot of self-motivation and can be VERY strong.

Good luck. :)

Good question,
TOEFL is a must, GRE would be helpful most of the time, in the US universities, different departments really have a huge variation of admission requirements.
For instance, some departments in MIT admit students without bothering the GRE scores - as long as they want you.
For graduate studies, you need to show your mathematical skills - the fundamental for logical reasoning and calculation.
The skill for programming - needless to say it is fundamental and essential.
The skill for doing research - state any related experience, including academic contest, publication, Bachelor thesis, etc...
Some skill for engineering - highlight some of them, but keep in mind that research comes first when considering the ability for potential academic successes.
So fill your personal statement( or statement of purposes depending on the university ) with mathematical skills, research experiences while leaving a few place for your best engineering experience.
And standard test score really varies from time to time and from department to department.
The best way to find out the requirement is to visit your dream school's website an call them directly.
Good luck!

One point: a missing GRE score can influence your chances of getting into MIT either greatly or not at all. It depends on the department.

good point @PeterShor


text:
How to convert from one grading scheme to another?
I'm trying to figure out the equivalence between grade schemes in different countries.
According to some Google results:

If you are a U.S. citizen, you need a GPA of 3.2+ (it varies, some say 3.2 and some others say 3.6, etc) to apply for a position in the UK (job or university) where the prerequisite is to have a minimum grade of 2:1.
In UK 2:1 is earned if you have a 60-69% of the points. I've read that 2:1 is the same as 67%.
In Spain we use a grading scheme of 10 points. So according to (2), for have a UK 2:1 you need to have 6-6.9 points.
If you are Spanish and have 6.7, when converting it to GPA the result is 1.5.

However, if you take the above points and treat them as a math equation, the final result will be GPA 1.5 = GPA 3.2, which doesn't make any sense.
GPA 3.2 = UK 2:1
UK 2:1 = Spain 6.7
Spain 6.7 = GPA 1.5

Replacing now...
UK 2:1 = GPA 1.5
GPA 3.2 = GPA 1.5

My question is if someone has a better explanation on converting grades obtained in different countries.

It's not clear what you are actually asking. Could you please expand? Are you asking about equivalence of grades in the countries, or about degrees, such as MSc.?

Related (duplicate?): http://academia.stackexchange.com/q/8170/102

@CharlesMorisset not duplicated

The spelling is "grade"; "grad" is short for "graduate" (as a noun) and is confusing in this context.

I have written an answer for Indian conversion system here: http://academia.stackexchange.com/a/42061/31973

I realize that you mainly mention translating grades between Spain-UK-USA but the final statement of your question is about converting grades in general, so that's what I will refer to.
Most countries have their own system which doesn't really make sense as you try to "translate" them to some other system.
For example in Sweden two grading systems exist at university level:

U/G/VG which stands for fail/pass/pass with distinction
U/3/4/5 which stands for fail/pass with grade 3/4/5 (5 being the best possible grade) used primarily in technical (such as engineering) universities/faculties

Our neighbouring Denmark however seems to have a 7-grade system with a scale from -3 to 12. In Germany, however, the best grade you can get is a 1, thus you would want a "GPA" as low as possible. So much so that if you apply to an institute with 4+ GPA from a Swedish engineering school, they don't even bother to reply (personal experience).
To add to this grading madness, consider the effect of the curve bell; in some countries university exams are graded based on a bell curve, so a certain percentage of students get the best grade no matter how many points they get. In other words if you are in a class of overambitious students, well, your 80% in the exam might be barely enough for a pass.
Note that a standardised grading system was attempted in the EU (with some extra countries) in connection with the Bologna Process, with the ultimate goal of facilitating internationalization amongst European countries. But it died out due to the resistance from many different institutes. When the standardised grading system introduced with the Bologna Process was trashed later on (at least in Sweden), the solution was to supply a diploma supplement, for instance upon enrolment in exchange program, where statistics (how many students were enrolled, how many passed with what grade etc) for each course the student has taken is denoted.
To sum it up, what the grades are supposed to reflect typically gets lost in translation. Trying to convert them back and forth does not make any sense, and even if it did, there is no guarantee that country A and country B will value a certain grade G from a country C the same way. In clearer terms your 6.7 Spanish GPA might not weigh equal when judged by the American and the British authorities/companies.

"If you apply to an institute with 4+ GPA from a Swedish engineering school, they don't even bother to reply (personal experience)." Of course; saying you're 4+ means you're one of the worst students!

@JoeZ. japp, the irony is that a 4+ GPA from my program in Sweden is actually pretty good. Unfortunately my faculty did not make it clear how our grading system works, and our German friends figured everyone knew about/used the same grading system as them. The moral of the story is, whenever you send/submit a transcript/GPA always attach some form of a diploma supplement, so that they can judge the grades accordingly

+1 for discussing the problems of the ECTS grading scale.

There is no clear answer for conversion between grading schemes in different countries. Sure, you could numerically try to convert using ratios and proportions as you are currently tying to do but they don't really mean anything because of the following two salient reasons:

Grade Inflation and Deflation: Grades mean differently in different institutions across different disciplines and in different courses. For instance, certain highly ranked universities in the USA are very well known for grade inflation. A 3.5 overall GPA is what almost everyone gets. On the other hand, certain other highly ranked universities suffer from grade inflation where getting a 3.0 GPA in certain courses and in certain majors is very different. Hence, merely using some base metric to convert between grading schemes of different countries is not a very good idea.
Differential grading within the same country: Not every country has a standardized grading system. For instance, India has at least 5 different grading schemes that I am aware of including but not limited to absolute CGPA's on a 4.0 scale, a percentage system on 100 and a relative CGPA system on a 10.0 scale.

tl;dr
Don't convert between different grading schemes unless it is explicitly mentioned what minimum grades you need for your own country. Just apply and hope for the best.

In Spain, examinations are graded in 0-10 (with 0 being failing everything, and 10 a perfect score), but then the actual marks for each subject at universities is in a 4 degrees scale: 0-fail, 1-pass, 2-remarkable, 3-outstanding, 4-outstanding with honors. Marks are weighted by the number of credits (equivalent 10-hour blocks of study, including class attendance, labs, and estimated self-study) of each subject.
People with non-Spanish degrees have to convert their marks to this 4 point system, with the help of the following algorithm (in pseudo-code; you can find how to use it, for instance, in this form from the Spanish Council of Scientific Research):
Ti = 0;
Mi = 50+50*(SMi-Nmin)/(Nmax-Nmin)
if Mi >= 50 and Mi < 69.9 then Ti = 1
else if Mi >= 70 and Mi < 89.9 then Ti = 2
else if Mi >= 80 and Mi < 99.9 then Ti = 3
else if Mi > 99.9 then Ti = 4

and the final average is the total sum of the weighted average (Ci times Ti) divided by the total sum of credits (ΣCi), where:

Nmax = maximum note in the source system
Mmin = minimum note that gives a pass in the source system
Ci = number of of credits for subject i
SMi = source mark for subject i
Mi = intermediate 0-100 mark (with 50 being the first note that gives a pass)
Ti = final mark in the Spanish system

You can use that kind of intermediate step to go from any mark system to any other. The only thing you have to change is:

Nmin and Nmax; it even works for system such as the German, where Nmax = 1,0 and Nmin = 4,0
the brackets and marks for converting from the 100-point system to the target system.

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text:
How to evaluate undergrad CS programs when eventually aiming for PhD?
My daughter has a strong interest in theoretical computer science, and she has just been  admitted to several different universities as a freshman.  She is just a bright student, not a genius, with a bit of research experience in cryptography and randomness stuff, and a semifinalist in a couple of national competitions.   She intends to continue graduate study in theoretical CS, or a closely related subfield, after finishing her undergraduate degree.
Given her strong interest in eventual graduate study, what criteria should we take into account in choosing where to enroll as an undergraduate?  How can we tell which undergrad programs best prepare their students for graduate school?

Not an answer, but: all of the universities you list are excellent. If your daughter is interested in grad school, she should make sure to (a) ask about undergraduate research programs, and see whose answers she likes (there should be some sort of contact info in the admissions material), but (b) ultimately pick the university where she thinks she will be the happiest. The research experience basically consists of prolonged failure, and being happy about her life will make facing that less daunting.

Although I'm sure you already realize this, you shouldn't let a laser focus on your daughter's professional development control her choice of which school to attend.  (Influence, sure, but not control.  And yes: HER choice.)  Given your daughter's background and experience, she will likely be very successful no matter where she enrolls.  I've seen very successful theoretical computer scientists come from a huge variety of undergraduate programs, not all of which were associated with strong graduate CS programs.  It is at least as important for her to find a place where she feels (and not just is) supported and challenged, both by her faculty and her peers.  Otherwise, no matter how strong the department is on average, it won't be a good fit for her personally.
There is absolutely no substitute for a personal visit to each campus, if you can manage it.  Let her drop into the comptuer science department, get a feel for the community vibe, sit in on a class, talk to a professor or two if she can, hang out in the dorms.  Meanwhile, you go somewhere else.  Go'way.  Shoo.
But if you really want hard data, I recommend that you—or better yet, your daughter—directly contact the computer science departments at the schools where she's been admitted, describe her experience and her goals (which should make them very eager to attract her), and then ask questions like the following:

How many students graduated from your program in the last five years?
How many / what fraction of those students are currently enrolled in strong computer science PhD programs?
How many / what fraction of your current undergraduates are involved in research with your faculty?
How many of your faculty do research in theoretical computer science?
[The Hail Mary:] Would you mind asking one of them to contact me?  I'd like to ask some more questions.

Beware the answer "I don't know", or qualitative waffle like like "quite a lot" that really mean "I don't know".  Ask for numbers.  Ask for examples.  Channel your inner Cuba Gooding Jr: Show me the data!
Your first contact will almost certainly be answered by someone on the administrative staff, who may not have the data you want at hand.  Be prepared make an appointment to speak over the phone (or Skype or whatever) with the director of undergraduate programs or another faculty member.  If you do speak over the phone, try to keep your conversation short and to the point; these people are very very busy.
Don't bother asking admissions officers these questions; Chances are very high that they just don't know.  You really need to contact the departments directly.
Another good place to look is the list of current and past winners and runners-up for the Computing Research Association's Outstanding Undergraduate award, which specifically recognizes undergraduate research.  A significant fraction of winners did their undergraduate research in theoretical computer science.  Also, a significant fraction of winners were not enrolled in departments with a top-10 graduate program.
But as Anonymous Mathematician notes in a comment, you shouldn't take the CRA list too seriously; some departments are more interested in awards like this and push hard for their students to be selected.  The fact that some prominent departments have few or no students on this list may reflect a disinterest in this particular award, not in undergraduate research in general.
[I'm a theoretical computer scientist at a top-10 CS department; I serve on my department's graduate admissions committee.]

JeffE, thanks for migrating my post to the `right' place and answering with great insights. Among them, I am particularly stunned to see the list of Computing Research Association's Outstanding Undergraduate Research awardees/runner-ups over the last 7 years. In particular, I do not see one most prominently ranked CS dept in the west coast and one prominently ranked theoretical CS dept in the midwest producing NONE in this list, and one most prominently ranked CS dept in the east coast prouducing VERY FEW for its size and fame in this list. This is really stark surprising. Should I read someth

These sorts of lists mean something, but I wouldn't take them too seriously.  Some departments are very interested in particular awards and push hard for their students to be selected (for example, by writing over the top letters of support), while some don't.  If this reflects a department-wide atmosphere of support for students, then it could be a valuable consideration in where to study, but I think it often just reflects which departments happen to have one or two faculty members who really care about this particular award.

Best researchers go to Universities where they get the best students to teach, and the best students go to Universities where they get good education and enough attention from the faculty.  So, things balance out.  Departmental reputation and standard University ranking tables are perfectly fine to use as a guide to decide where to go.  Pretty much all the top departments will have good strength in Theoretical Computer Science.  You will need to look closely only if you are looking at lower-ranking Universities, which might have strength in some areas but not others.
There is also no conflict between good undergraduate education and good grad school, because the grad students do contribute to teaching.  They run tutorials/discussions and help students with questions and exercises.  So, a department that is good at grad school is also likely to be good in undergraduate teaching.
There can be a bit of difference between private Universities and State Universities.  Because private Universities are more dependent on the tuition fees and alumni donations, they are likely to spend more effort on undergraduate teaching.  State Universities also tend to have larger class sizes, something to consider if you are looking for "personalized attention".  You can't ask for too much personalized attention because, if that is what the faculty are engaged in, they are not going to have much time for research and, as a result, the quality of the department would go down in the long run.
If you are really after personalized attention, then you might consider Liberal  Arts Colleges rather than Universities.  Undergraduate teaching is their No. 1 focus.  They don't normally have a grad school.  While the faculty would engage in some research, research is not considered the top priority.  Teaching is.

+1 but think its simplistic. there has been noted a tension between undergraduate education & research as noted by many authorities & alluded to in the question. a relevant (and old) ref on this is why the professor cant teach by morris kline. in some ways the tension is heightened since the book was published.

Your last paragraph is particularly important.  Sometimes smaller (particularly liberal arts) departments that have strong research (not all do) provide much more support for undergraduates than departments where professors are too busy completing difficult research to hold an undergrad's hand as they start.  That said, this is really a school-by-school thing and you're much better off asking students at individual places than getting a big list here.

It is commonly said that the only university that counts is the one you've graduated from last.  If your daughter wants to eventually earn a PhD, the graduate school she attends will most likely figure more importantly to her future employability than her undergraduate school.
With that in mind, it is also true that many undergraduate schools with some of the top graduate schools in CS also produce excellent candidates for graduate school, primarily because the number of undergraduate research opportunities are greater, and also because it can be assumed that there is a good deal of correlation between the quality of the graduate program and the quality of the undergraduate program.
However, it would be wise to also consider the strength of the undergraduate program from the standpoint of all the normal factors that go into choosing an undergraduate school, e.g., (1) the kind of student your daughter is, and (2) whether the undergraduate program will give her what she needs as a student holistically.  For example, some phenomenal CS programs are at schools where class sizes can be in the hundreds (e.g., UC Berkeley), but if your daughter thinks she would get swallowed up in a giant class, that probably isn't the place for her.  A smaller school with smaller classes might be more appropriate, even if the CS program is weaker as a whole.
Finally, the top two (in my opinion) factors that will affect your daughter's success in getting into graduate school are:

Her grades (despite what some prominent and highly successful members of this community have achieved).  Getting a 4.0 from any decent school in a particular major is better than a 2.5 from the best school in the country.
Undergraduate research, with published results.  Just doing research is important, but having published results will help her case significantly.

Bottom line: I suggest choosing a school where your daughter feels comfortable, and with enough of a research program that she could get involved with research as an undergraduate.

despite what some prominent — and very lucky.  I agree that good grades are cricial, but fantastic grades are not.  Speaking with my admissions-committee hat on, anything above about 3.5 is noise, especially if you have undergrad research experience.

I should add: ...unless you are applying from a lesser-known school with no opportunities for research experience, in which case you really should aim for straight A+s.

Selecting a school is a very challenging thing to do.  Just because a school has top-quality research faculty doesn't necessarily mean they have top-quality teaching faculty (brilliant researchers are not always the best communicators, unfortunately).  The best way to get one-on-one time with a professor is usually to corner them during their office hours and keep asking questions until they insist they need to leave.
Wherever your daughters ends up, encourage her to start making a connection with individual faculty members as early as possible.  Faculty are almost always happy to bring new students into their labs, and there is funding available for undergraduates who are interested in research.  Many universities offer REUs (research experience for undergraduates).  The primary issue I've come across is that these programs have difficulty finding undergraduates to give money to.
As far as grad school goes:  tell her to make good grades and get involved with a lab.  Everything else will fall into place (and that's a long way off, anyways).

"The best way to get one-on-one time with a professor is usually to corner them during their office hours and keep asking questions until they insist they need to leave." -> Not only is this bad advice, but it also gives a bad image of professors!

Have her go to the school where she would be least distracted. Princeton is better than NYU, as it is farther from Broadway (1 hr vs. half-hour). Yale is even better (3 hours). Urbana-Champaign is impossible to beat in that regard -- cornfields for hours to drive (and you can still deny her of a car), she would have nothing else to do but study.
I guess I would also want to make sure that the university's regular math program is good. If she can get a credit for non-math AP courses, that's great, as it will clear some time to do real work in college; math and CS will have to be retaken, or taken at a higher level of expectations, and/or in the honors college. Some good quantitative bridge courses like biology or psychology may be something else to pique her interest to do something CS-related that is funded by another substantive field (many of the great discoveries are being made at the disciplinary boundaries). Knowing what you are going to do for the rest of your life at 18 is incredibly boring -- sounds more like a lawyer than an academician!

here are some standard rankings/surveys that might be helpful. for very elite schools, they are all highly rigorous, and maybe unique nonacademic features  particularly appealing to your daughter (eg "culture/atmosphere", which is difficult to objectively characterize) might shift the balance.
the last 2 links are based on Shanghai Jiao Tong University's graduate school of education which recently ranked the world's best universities in computer science, based according to their academic or research performance in each subject field. it ranks 9 of the top 10 in the US. good luck!

Worlds best universities in computer science, USNews
best grad schools / computer science, USNews
Computer Science Colleges' Best Programs, As Ranked By 'Academic Ranking Of World Universities
The Best Universities: Computer Science

Vzn, thanks for the ranking list. But I guess undergrad training is different from ranking? Foe example, how about grad school placement rate of these schools? I'd be further interested in hearing insider's voice which places put more emphasis on undergrad student education/research experience by faculty. I'm not in this field, but what I hear is that profs in CS are very busy and have big numbers of grad students to deal with, so generally do not have time/interest for undergrad kids? Perhaps differ person by person, so that's why I'd like to solicit insiders' voice. Thanks.

Also, please consider registering for a StackExchange account, so that it's clear that this comment and the original post have the same author.  You can register anonymously.

Vzn, thanks again, and sharpening my query. Indeed, I am soliciting advice on (1) which place offers the best undergrad research opportunity with profs, (2) which place best prepares students for grad. School and have best grad. School placement record?

Um... I'm not vzn.

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text:
Taking courses as a PhD student
Question:
When I have a choice to take only one of two possible sequences: A theoretical one which aids my research and an applied one that aids my employability, which one should I opt for? (I must do the other on my own)
Background:
I am currently in a PhD program for Applied Math. I have finished all my core courses but am now required to take any (from a list) of courses which span Econ (Micro Econ, Time series type stuff), Management (Business Intelligence) and Statistics (Mathematical Stats, the gnarly stuff). My research is on Big Data Analytics from a Mathematical perspective.
I want to keep my options for engineering (Electrical/Industrial Engineering) and Business (Data Analytics) faculty positions open. I want to join academi and in my department, senior students have gotten jobs in all of the three quoted above.
From that standpoint, what courses should I be taking? My time is constrained and I have to choose one of the three. I know for my research, I will benefit from a more rigorous mathematical training in Stats but I don't know if this will help me get a business school job. If I choose one, I know I can (& will probably make time) do the other two on my own but I am confused which one to pick.
The way I think :

If I do stats, I will have a rigorous background in any kind of statistical inference which is gold for what I do but I will have no clue about microecon, finance or business intelligence. All three are big application areas for my research.
If I do econ/business intelligence, for my research, I might get stuck at times when I am trying to interchange an expectation with a gradient and wondering "under what conditions can I do this".

While the current version of this question, even the "global" version is too localized, I think there is a good general question, for which the answers would be helpful. Please consider editing the question and then voting to reopen.

@DanielE.Shub, done. Hopefully, this one is more general.

The edit does make the question more general, which is why I voted to re-open, but I will warn that this question is not likely to yield useful answers. The obvious answer is "it depends on your goals", which you probably already know.

Is the stats class taught in an applied way? How theoretical is it?

The question is still very localized, but as somebody with Ph.D. in Statistics and MSc in Economics, working in industry after an unsuccessful start in academia, I would suggest taking the courses in the discipline you will be aiming at. I am not sure as to who is going to hire for Big Data Analytics; I rate statisticians as unlikely to do that (except probably for Carnegie Mellon and Stanford), and I am nearly certain that economists won't (they won't hire an Applied Math Ph.D. no matter how good you are), so business schools are your best shot -- some of them may hire people with wildly different backgrounds; UPenn has a Stat department housed in the business school, although that's a legacy issue rather than something deeply profound; Chicago has a small but strong statistical group; you might be able to find statistical groups in other places, too. Thus you would want to take Management courses in the mean time. An average business school faculty won't tell expectation from the gradient, except for a tiny fraction of quantitative finance people doing high frequency financial econometrics. My feeling is that an average Big Data architecture computer scientist/engineer won't tell an expectation from a gradient, either. (The only I thing I know about it is that at least one of the limits has to be uniform :) ). I may be entirely wrong with my assumptions about business schools, and if you don't see any Math/Appl Math/Stat Ph.D.s hired in the past 10 years in the top 30 schools that you've looked at, you don't have any chance, either, and should just announce your intention to go to industry, take all the classes you can, and apply to Google asking for a $3e5 starting salary ;).
The biggest career suggestion I could give is to move to Bay Area; I don't really know how  to do Big Data if you are not there.

My feeling is that an average Big Data architecture computer scientist/engineer won't tell an expectation from a gradient, either. — Them's fightin' words!

A couple of things : I have a really strong math background and that is something I hold dearly and aim to exploit whenever I can, my research is more towards statistical machine learning. Anyways, why Bay Area?

http://lanyrd.com/topics/big-data/in/usa/: California, 10 conferences; Bay Area, 6 conferences; rest of the US, 15 conferences. Are you sure you really know the landscape of this discipline?

@StasK, what I do is actually statistical learning in the Chicago area. My advisor publishes a lot in optimization and control conferences rather than analytics/big data.


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Learning new things after coursework duration of PhD
In STEM (In USA), the coursework duration of the PhD typically lasts about 1-2 years beyond that, students take 0 (or in certain cases, very few) courses in their subsequent PhD years. I work in applied math with a lot of applications in every field imaginable : Finance, Economics, Energy, Healthcare, Services etc.
During my coursework phase (owing to the breadth requirement), I was made to take courses in different departments and each time I attended a course in a new department I would think "Wow, this field could really benefit from extensions of my research". I would chalk out a few ideas and read up a few papers, find out that it's already done but be glad that I generated a new idea nonetheless.
Now, I am nearing the end of my coursework phase and I am wondering : How do I keep my ability to "see" applications in fields other than mine alive?
Global Question : After a student's coursework phase, how does he stay aware of applications of his research field besides the ones discussed in papers?
My advisor encourages me to attend as many seminar talks as possible (in all allied fields) which I do but it's not the same level of enjoyment.

http://25.media.tumblr.com/tumblr_lyl9peeoXh1r90y76o1_500.jpg  http://sjaejones.com/wp-content/uploads/2011/02/responsibility12alternate2.png

@JeffE, I naively did say that once :)

First of all, unless there is a policy against it, you should feel free to enroll in subsequent courses even though you are done with your requirements.  The caveat is that this will take time, and your primary responsibility after finishing those requirements is to do research in your specific area to make progress on your PhD.
To a first approximation, a PhD program is designed to have you focus on one particular problem until you are the only person in the world that completely understands that problem.  That is not to say that you won't find research inspiration from those other seminars, and in fact you might find that you will tailor your research based on one (probably not more) of those other fields.  But, if you continue an academic career after you get your PhD, you'll have more flexibility to collaborate outside your particular field, and that is probably a better time to do it than right now.
To answer your specific question: you're on the right track by going to seminars, and if you can justify the time, taking subsequent classes is not out of the ordinary.  You could also get on mailing lists for other fields that interest you, and nothing is stopping you from becoming a member of professional organizations outside your immediate field (and, they're cheap when you're a student!).  You could also consider collaborating with folks from other departments on projects, bearing in mind that you'll need to be able to differentiate your contributions if you want to use that work in your dissertation.

I will add and expand on Chris Gregg's good answer. I think the key to your question is "keeping up to date". What I mean is that by keeping up with what is going on in a field wil also show you the trends, needs, open key questions etc. Now, taking a course, to me, does not sound like getting to the forefront of a subject, typically courses (unless at very advanced levels) will cover core material in a field. I think this is why you find that the ideas you got already may have been solved. So, in my mind course work is not the way to research ideas, it may form a good and perhaps necessary basis for understanding research papers etc.
Today, even specialists have a hard time keeping up in their own field, I therefore think that it will be hard for you to keep up with several. Your notion that your own research could help others in other fields is most likely spot-on! But, you probably need to get to know people in some fields who have the solid basis and can jointly with you identify the research questions where your knowledge can be of use. So if you can spare the time, try to go to research seminars in other departments and even if you may not know the details, try to pick up what is going on, ask questions. Obviosuly I am not suggesting you should go to seminars at random but you can probably identify fields where you have some interests. Browse through some higher ranked journals from those fields as well to see what the research is about.
Then finally, you should not worry about getting all this done as a PhD student. I am sre opportunities will come after your PhD to broaden and find colaborations. I will say that finding colaborators in other fields is usually hard and if your knowledge is in demand you will probably get sucked in to many interesting projects if you make yourself and your expertise known. and that I do not think happens with course work.

Use StackExchange for the relevant field.


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How to use competitions to encourage students to work harder and study more
In order to encourage and motivate students to work harder and study more, it seems the teacher can use various competitions in class or after class. But on the other hand, competitions could cause jealousy and other destructive emotions among students and therefore affect the performance of some students adversely. Due to my doubts and my lack of experience, I haven't used competitions in my classes as a means of motivating students yet. But I would like to know if there is an experienced and useful method to do that. So my questions are:
Have you ever used competitions in your classes? What are the pros and cons of students compete in the class for higher grades? Which points should I consider before encouraging students to compete with each other?

See also: Conference submissions (in CS), faculty positions, and (in some places) tenure.

"real winners don't compete" is what the Finnish education expert's Sahlberg says.

I think @JeffE's real point is: only do it if you want a random unpredictable process with lots of noise :)

@Suresh — Actually, I was thinking "Destructive or not, competition is a fact of academic life." but I like your interpretation better!

I often have competitions in class. I try to use them primarily for motivation, not assessment.
Let me give an example: I was teaching an image processing class and we had some images of x-rays of "old master" canvas paintings. The goal was to create an algorithm that could count the density of the thread weave patterns. The quality of the answers could be assessed by comparing the algorithmic answers to manual counts, and I had about 200 locations where I knew the answer. I gave them 100 to train the algorithms. After about two weeks, there were 25 different algorithms submitted (most people worked in pairs) and then I ran the submitted codes on the 100 "unknown" locations.
I called it the "2010 Thread Counting Olympics" and made a big deal about giving out "medals". I created several different ways of measuring the quality of the algorithms: closest in least squares error, number of answers within +/-1 mm per thread, number within +/-2 mm per thread, closest in absolute value of error, closest on the canvases by Van Gogh and closest on the canvases by Vermeer. Then there were bronze, silver, gold, and titanium medals in each category. As I presented the results to the class, I described the various approaches and pitfalls of each of the algorithms, and often asked for clarifications and comments by the authors of the algorithms. By the end of the competition, well over half of the students had won "prizes"... plus they had the recognition of their peers.
The amount of effort that the students put into this project and into the class were amazing, and I think the "competition" aspect was a prime motivating factor.

That's a good example of how to do them well. As you say, motivation, not assessment.

A competition is almost by definition a zero-sum game, and thus has the destructive aspects described above. But if you want to reward overachievement you can provide extra credit work.
The trick here is to use the extra credit only to improve the grade. Practically what that means is that you assign grades based on your system, and then add in the extra credit and see if that moves people. In other words, allow the extra credit to change your position in the curve, but not the curve itself.
In this way, doing extra credit will benefit the overachievers, but not doing it won't hurt the others.
Update: I want to reiterate one point, because I think it's important. As you state in your question, the goal of the competition is to motivate students to work harder and study more. Students are motivated by many things, but the goal of the competition has to be "to work harder and study more". If the way to "win" the competition is by being better than others, then you're not achieving the goal you set out to achieve, and you're vitiating the class atmosphere. Artificially placing constraints on who can win doesn't make sense, because there's no reason that ALL students can't work harder and study more and get a reward for doing so, and in fact that's a great outcome.

Assuming we have 10 overachievers (out of 30 students), if we promise extra credit to only 3 best students, then I  guess we have a competition which has no loser and hopefully motivates students too.

@VahidShirbisheh Or will it just pit the 10 best against each others trying to make the other looks bad? What is bad with offering the extra credit to all of them?

you don't offer extra credit for a small group. You offer extra credit for anyone who can achieve the task. If all do so, that's perfectly fine (it might mean though that your task was too easy, but that's a separate issue)

@Suresh: I see your point in your update. In fact, I am asking this question to see if there is any benefit in setting a competition in class? and whether has anybody ever tried this idea in a class?

@Zenon: Yes, we can give every overachiever some extra credit. But, that is not a competition anymore.

One key thing to consider is whether you are encouraging your students to do better for themselves or if you are encouraging them to harm other students to look relatively better. Clearly, you must decide how to structure the class to achieve what you want.
I've seen many teachers take the stance: I will give 10% A's, 50% B's, 20% C's, 10% D's, and 10% F's. Their rationale is that this is the way the real world works: There are only a certain number of management positions and if they want it, they must work harder and step on others to get it. However, I've found this is not great for the classroom and it is not the way the real world works either. It is clearly possible to grow a company so that there are more management positions available (indeed, growth is the goal).
Personally, I have come to the point where each student should be judged on his/her own merits so I never run the kinds of competitions discussed above. That said, I have been known to offer prizes in class which are clearly limited. Prizes might include money (I don't generally offer a lot but students do seem excited about even small things, perhaps because they simply like something to represent them winning) but could easily be something else. What I offer comes out of my own pocket (though I don't tell the students this...and I'm not sure they would care either way).

Actually I was thinking about a relatively mild competition, for example, three students who find and discuss more interesting problems related to the course get some bonus points.


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Math Major and Grad School -- Necessary?
I decided fairly late in life (21) that I feel like studying mathematics. I've always been interested in higher maths, I've just been daunted by some of the esoteric notations and theorems. But, no longer a philistine, I'm infatuated with pure mathematics. Right now I'm pursuing a Bachelor's degree in English. Is there a way I can get a Phd via an MSc?
I guess what I'm really asking is this: Is it possible to get into a Masters program without having a Bachelors in the field?

Thisis closely related. Also are you asking if it possible for a school to let you in a MSc programme in mathematics or if it reasonableto join a MSc programme (in mathematics) without a BSc in mathematics?

21 is not "late in life"!

Yes, it's possible to get a graduate degree in mathematics even if your undergraduate degree is in a completely unrelated field.  (Everything I say will be assuming you are in the U.S.; otherwise, I don't know.)  In practice, you'll need to acquire much of the knowledge from an undergraduate degree in mathematics before starting, although you can fill in a few gaps during a master's program.
If you have unlimited time and money, then it's straightforward.  You take undergraduate courses until you have completed most of a math major, either by delaying your graduation or by taking courses as a special student (i.e., not in a degree program) after your bachelor's degree.  At that point, even thought you won't have a degree in mathematics, you'll be able to make a compelling case that you have equivalent background.  You may not have a strong enough application to get into a top Ph.D. program directly, but you should be able to get into a master's program in a decent department, and if you do well enough there you can apply to even stronger departments for your Ph.D.
The drawback with this plan is that it's slow (you might spend two years or more taking courses before even applying to master's programs) and expensive (you'll be being charged tuition for these courses).  Instead, the real question isn't whether it's possible in principle, but rather how to get to a Ph.D. program as quickly as possible, since at that point you'll no longer need to pay anything.
How efficiently you can do this depends heavily on your background and experience.  If you are just starting to take college math courses, then it may take several years to prepare yourself for a master's program.  If you already have a lot of experience, then you might be ready to apply this fall.  I'd recommend consulting with faculty in your math department to see what they think of your background and what they would advise.
There exist certificate or post-baccalaureate programs designed to prepare people from other fields for math grad school.  (See, for example, http://departments.columbian.gwu.edu/math/certificates/gradmath.)  Such a program could be useful, depending on how well it fits with your background and preparation.

From my experience, it is possible to get into a masters program without a bachelor in the field. What you do need to do though display an aptitude for the subject. Also, if you were to be admitted into a masters program, you would likely be required to take undergraduate courses to get "up to speed."
Since you are still in undergrad studies, why not make the switch now by taking mathematics courses. The additional advantage to this is if it turns out that you don't like the area, you had not invested a significant amount of effort and time.

I got into MSc program in Economics having my base degree in Engineering, and then moved to get a Ph.D. in Statistics with these two degrees. But all of them are highly math-intensive. You are at about 5-8 years disadvantage compared to Chinese and Korean applicants, and at about 3-5 years disadvantage compared to US applicants (again, assuming that you are in the U.S.). While Anonymous Mathematician, obviously, has a more in depth knowledge of what kind of applicants are being admitted to his or her department, I would say that it seems very difficult to me given your non-technical background. You can take courses in math, but if you have not been trained to think as a mathematician, you won't be able to fit into math world. (A girlfriend who was majoring in math dumped me when I was an undergrad saying "You don't think like a mathematician". So be prepared that this is a different bunch than the people you are used to in your English classes.) This had to happen throughout your secondary school; if you start math in college, you could still do engineering and economics, but pure math is nearly impossible. Furthermore, you would have to seek proof-based courses, and you may not see them until the senior year even if you major in math. (I was stunned to hear from one of my students that he only saw epsilon-delta formalism in calculus as a senior in college; I had it as a junior in high school.) If you apply to a graduate math program with just three semesters of calculus, you won't be taken very seriously. I personally think that one cannot seriously call themselves mathematicians unless they know abstract algebra and complex analysis, as these keep reappearing in pretty much every field of mathematics. (Folks at math.stackexchange might be able to give you better pointers as far as specific courses go, though. Your question being moved to Academia made some sense, but it is still very much discipline-specific.)
To get a glimpse of whether you are prepared to work in a math grad program, take GRE Math subject test. If you don't get some 80+%, you are not ready yet (folks here with scores below 60% don't go anywhere; even folks with 80+% percentile don't get accepted left and right).


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Techniques to remain focused while marking examinations
Marking exams can be long, boring, and un-engaging.
It is important one remain focused though to ensure that the evaluation is fair to each student.
What are some methods one can employ to maintain focus and not zone-out while reading answers?

The question What are some ways to increase grading speed? should be helpful to you.

After I mark one question on a batch of exams (say 1/3 of the total), I often get up and stretch, use the bathroom, or get something to drink.  This shouldn't take more than a few minutes, but it can help me to refocus.

There is two issues in your question.

How to be fair to each student when it comes to this boring task of evaluating them

My own policy is the "mark-one-question-and-shuffle" : I correct the first question/problem for all the students, then I shuffle the whole stack and go for another question that I also pick at random. This way if I am tired or in a bad mood, it will impact everybody, so it will be fair.

How to stay focus for a long marking session

I cannot answer to that and I guess it depends of many personal factors. Personally, I find marking tasks boring but easy to do and easy to focus on. It's like driving, some people can drive for hours, others can't. To tell the truth, marking is somehow relaxing for me.

I use the same strategy when marking to ensure fairness to help prevent any bias' I may have and not realize (i.e. the halo effect).
Personal factors are an important consideration. Sadly, marking puts me to sleep (but then again, I am also a poor driver).

+1 for "mark one question", but -1 for "and shuffle".  Shuffling 150+ ten-page written exams is hard!

@JeffE: You can achieve the same effect with fewer papercuts: instead of picking the next exam to grade off the top of the pile, take one randomly from the middle.

I can drive for hours, no problem or browse SExchange for ages, but after 15 minutes marking, I get fidgety and easily distracted, please help...

I suspect my answer will be less applicable to math (your subject) but your question is not specific so I'll cover my subject (business management).
First, I find the more I can process in a single session the more fair my marking is overall. In my field, answers are not so clear-cut. That is, there is rarely a right and wrong answer but rather the process of application/evidence that is evaluated. Because of this, there is a risk of being inconsistent when marking in different sessions.
Second, I try to process 10 or so exams before actually marking any of them. The reason for this is that I need to understand the general level of the group. If I don't do this, I find that I am much stricter on the first few exams and get easier as I find everyone is at a lower level than I had anticipated.
Third, I try to give my eyes a break between exams. That is, stare at a point some ways off so that my eyes are not constantly focusing on a point to close (which causes strain and can cause lasting problems).

+1: I do something similar to your second point.  For each exam question, I mark up the solutions in about 1/3 of the exams before I assign any numerical scores for that question.  (And I grade all answers to one question before reading anything else.)  This usually uncovers all the common mistakes, so I can assign a fair and reasonable penalty for each.

Your own website says:

My primary area of research is the application of mathematical methods to educational testing

so I'm sure you have much more experience (first-hand or second-hand) and have given it more thought that you let appear in your question ;-)
Of course, it heavily depends on the type of examination being marked, but unless it is very short, I tend to simply split it into many short bursts, and do those at a time when I am well rested (morning) and when I am outside my regular “work” setting: public transportation, waiting room of a doctor, café, in a garden when it's sunny, etc. The mood of the place I'm in helps, and gloomy settings just get me bored faster.

I should also say that I find very long series (say, more than 2 hours straight) of oral exams, like students presenting their work on a series of projects, much more of a problem than written exams. But that would be another (worthy) question…

Haha, good call! You are right, I have given it a lot of thought and experimented with quite a bit of options.
I have yet to determine a good series of techniques; this has spurred me to ask what has worked for others.

@F'x I actually find oral exams less of a problem, mainly because of the interaction. Marking exams is a bit solitary and more likely to cause fatigue for me.

True story: a bottle of wine (well, maybe just half a bottle). Spirits are not a good choice since they go quickly to your brain.
Sorry if I hurt feelings with my answer but the truth is that this technique is more common in the academia than I would like it were.
Another technique consists of splitting the marking into several short sessions.

Now someone will surely ask what teetotaling evaluators must do! (Reference)

Which country's academia? Ireland :) ?

hey @user13107! that's not fair to us Irish, we don't drink (that much) wine, it's mostly beer and whiskey. But seriously, it's hard enough to decipher the students' scrawls, without being tipsy. And I've never heard of a colleague who grades while drinking.


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Is ignoring emails acceptable in academia?
As a grad student, I just find it tremendously frustrating when emails are ignored by faculty (both at my institution and at other places). Is this acceptable? I'd be content with a simple response with one line along the lines of "I have read this email and am busy right now, will respond in X days when I can write a more detailed email." I understand that, as a first year student in my field, I'm not really in a position to request anything of anyone, but it just seems like common decency.
Instead, I never hear back, as if my email has been jettisoned off into oblivion.

There is a profound difference between something being acceptable and commonplace. Just because something happens often does not mean everyone is OK with it.

I recent blog post on the subject: https://blog.vrypan.net/2013/04/21/vsre-very-short-reply-expected/

By whom? Be clear. By your supervisor, others from your dept and faculty, other depts at your institution, project partners from other institutions, other researchers in your field, or cold email inquiries or applications to other institutions? Those are all different things. In particular, cold inquiries rarely ever get an email response.

@posdef : Inversely, just because something does not happen often, also does not mean everyone is not OK with it.

I agree that it can be frustrating, but this  is not uncommon in a big organisation (I don't think this is specific to academia). People get a lot of e-mail, and are very busy. Answering each and every email can be a lot of work in an already fully packed day. This either leads to people forgetting, or simply ignoring their e-mail to some extent. Also remember that something might be a really high priority for you, but a relatively low priority for the person you mail. So I don't think ignoring mails is acceptable, but sometimes understandable.
I think the best way to deal with it is to try and work with the system. If you see that professor X is very unresponsive to his mail, approach him in person. If a department does not return your mails, give them a call. This kind of personal approach makes it harder for those persons to ignore you, an email is very easy to ignore.

I think this issue is not specific to academia. If person X is too busy to reply e-mail, then it's likely that you won't be able to approach him in person easily. The way I deal with it is to make an appointment via some ways such as electronic calendar or department secretary. Then go to catch him at the appointment time. This doesn't always work, but better than just show up at his office.

@scaaahu I agree that a busy person might also be busy in person, but sometimes people just tend to ignore email, and then a personal approach might yield better results. I agree that making an appointment is also a very good idea.

Another advantage of a personal approach is that you can have a lot of interaction: you talk faster than you write, you get a faster answer.

@Konerak: Unfortunately, that's also an answer that is faster forgotten, as none of the parties involved in the talk can look up the text of what was actually agreed upon.

@O.R.Mapper you can always confirm your conversation with an email. This is especially important if decisions where made.

I do think this may be more common in academia. Industry connections seem to reply to most emails, though their replies might be short and non-committal (e.g., "Thanks. We'll let you know if we can fund this."). On the other hand, some faculty members do seem to ignore virtually all emails, even from their own trainees.

One of my e-mail accounts receives 100+ spam messages a day. I just stopped checking it.

Within limits of my experience as an administrator, who regularly asks large numbers of academics for responses by email (eventually, by deadlines, or immediately with harsh consequences):

if you directly address correspondence on a topic to a person who has no competence or responsibility for that topic, they are likely to ignore your email as spam.
emails can cover both "please action X" and "please action X in a manner which requires response."  Some email cultures do not respond to the first, as a response is not implicitly or explicitly required; other email cultures explicitly respond to the first.
your email may lie within your correspondents' area of discretion, for example, in my University system requests to discuss research are normally considered to be discretionary—people are unlikely to discuss research with members of the general public, and most likely to discuss research with colleagues in coaligned fields.  Your correspondence may fall into the gap between "must answer" and "don't have to."
my experience of general society is that most cold calls fall flat; this tends to be true in academia unless you have something to give someone.
academic work is a high stress and "sweated" industry in Anglophone countries at the moment.  Out of the hundreds of things academics are obliged to do, answering emails often comes last out of the immediate obligations.  The penalties for not answering email are low and eventual.  The penalties for failing to deliver coursework or publish research are more immediate and severe.
following on from the above, one long term coping mechanism for many academics is to push deadlines and delay.  Some academics rely on these time bargaining tools.  Email is an easy victim.
"that Guy" still exists in the academy.  Your correspondent could just be that guy.
even the harshest consequences for failing to answer emails won't necessarily summon a response from someone on sabbatical or funded research relief from teaching.  An academic's line manager in the immediate chain of management can't always summon responses.

The Problem
People who are super busy don't have the time to spend minutes first reading, then processing (and/or rereading), then responding to your email. This is simply life, there is only so much time in a day, and some people have way more constraints on their time.
Spending lots of time parsing/processing/understanding/formulating responses/replying to emails from people they don't know or have reason to care about? Probably not high on their  list of priorities - which for the record is probably already completely overloaded anyways.
The Solution
Write shorter emails (or electronic content) which are easy to answer. This ability is an art, get used to practicing it if you want responses.
Make it easy for someone to respond.
Practical advice from this question
Notice that even in this question, the important part

Why is this acceptable?

was buried in a large paragraph (assuming this is even your primary question, which I'm assuming it was). Plus, it was filled with irrelevant information which suggests other things are what you are interested in.
If I'm a really busy person getting hundreds of emails a day, you just made me read, then reread the email after finishing to figure out what you want a response to. You can't do this if you want responses consistently - and this is relatively SIMPLE with minimal text.

I just find it tremendously frustrating when my emails are ignored by
faculty (both at my institution and at other places) and I don't hear
back at all.  I understand that I'm not really in a position to
request anything of anyone, but it just seems like common decency to respond rather than say nothing at all

Why is this behavior acceptable?

This is considerably more clear and makes it easier to respond to.

tl;dr
If you are not naturally able to write clear, concise, and easy to respond to emails, practice and spend time rewriting them until you feel they are.

One excellent article on how to craft emails that invite response is http://www.artofmanliness.com/2012/03/01/how-to-write-an-email-that-will-actually-get-a-response/ . It also makes the point that a sender does not create an obligation on the part of the receiver just by sending a message.

+1 I get emails all the time about the papers or statistical software that I wrote, and reply to probably 10% of these when I see how I can reply with one line. Negative replies are often the easiest ones (the most recent one: "Can I come study with you?" - "No, I don't teach at this university any more."; typically, "Can your software do this?" - "No, although that would be a reasonable feature to add; not going to happen any time soon"). In some questions, I just see the lack of homework, as in "[downvote] This question does not show research effort, it is unclear or not useful" here on SE.

Another tip that has worked well for me is to put what you want in the subject line.
Instead of -
SUBJECT: Paper X.
Put -
SUBJECT: Can you send me Appendix A listed in paper X?

E-mails are not easily ignored in all systems. In Sweden, e-mails sent to public agencies and organizations must be answered in "due time" (mostly meaning within days). Since many or most of our universities are public, we as faculty fall under the same rules and must answer all mails sent to us. In our case, this of course only concerns matters dealing with university matters, no need to worry about spam etc. We are even requested by law to file all correspondence although there is no clear indication on how this should be done with electronic correspondence.
I have kept tally of my e-mail correspondence for years and receive about 10k mails per year and send about 2-3k. If I do not respond to mails relatively quickly they may soon become forgotten even though they are marked as not read. But, I do not miss more than probably around a few tens of mails every year, a pretty ok "percentage" in my own opinion. I believe all senior staff have similar numbers regarding e-mail harvest.
In my department I have colleagues who's e-mail discipline ranges from "may occasionally answer" to "seems to use e-mail instead of a telephone". In the first case, the persons are by no means not answering out of malice. The persons in the latter category are simply annoying. So regardless of the circumstances, some people are notoriously poor regarding answering, even to relatively close colleagues.
So as was stated by Paul Hiemstra, try to catch the person who is unresponsive in person. it may turn out this is their preferred way to communicate.

For a grad student/young people/etc the amount or received mail counts in dozens per day (100 emails a day is something that I've never ever seen in my inbox)
However, people with larger academic networks, industry links, or just a bit older, receive thousands emails per day (this is actually common place, not strange exception). It means that just reading them all may take hours each day, not to say writing an answer. (Even hundreds emails is a bit too much to handle)
And even among those who are not flooded by emails, there are many that do not 'catch up' with technology - they have a default email address but never or seldom use it.
Some people use smart tools to help them manage the deluge (automatic filters, canned responses, secretary, etc)
Some are simply overwhelmed, and just ignore most emails, except those for a weekend beer with an old friend.
Now, you cannot blame them (you'll be in their shoes soon). What you can do about it is to follow some of Paul Hiemstra's recommendations and use some other, less busy channel to contact them.

"thousands emails per day". Are you exaggerated that?

@Ooker Thousands of emails a day would be quite a bit on the high end, but certainly within an order of magnitude of correct.

This is an old question  but one that speaks to me as a former graduate student who was puzzled and very frustrated by the same thing. Ignored emails are the norm in graduate school--unless a faculty member wants you to email something of course. Yes, it is frustrating to turn in a dissertation proposal or chapter and not hear back for months in spite of several friendly reminders. You need questions answered, problems pointed out, or just a few words of reassurance that you are going in a good direction before working six more months on what might be wrong. (And the blame for not getting finished in a timely manner will only fall on your head.) As a new student, you also probably have scores of questions about the program, policies and procedures, and many other things and you, too, have a busy schedule of classes, teaching, perhaps another job, maybe even family, and deadlines of your own. However, as others have said, answering students' email is not high on the list, even if it is possible. Sadly, many faculty do not have time (or inclination) to help you.
So my advice is to memorize the handbook. Then get friendly with other graduate students, especially those who have been there longer, for they can be valuable sources of information. If  the issue is very important and can only be answered by a faculty member then drop by during office hours and see if the person can spare a few minutes or make an appointment. It is hard not to see the blatant ignoring of one's communication as just rudeness and arrogance--and maybe it is. But that's the way it is and there is nothing to be done without risking your career so your option, until you have that diploma and job recommendations, is suck it up and not complain. Good luck with it.

From my experience in industry, one reason I think many emails go unanswered is that it's become common (though, in my opinion, not acceptable) for a lack of a reply to mean "no"/"I don't know"/"I can't help"/"I don't understand your request". If I analyse the emails I sent which never got replies, it seems that around 40% of such cases could be explained by such a phenomenon.

At my university professors are required to respond within 24 hours or they can get in trouble, especially if it is an ongoing issue.
Source: a previous professor told me this little important tid bit of information & I have had to use this information to my benefit a couple of times for lazy or asinine instructors.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Can I write an article in a reputable CS journal not with results but conjecture?
I work in industry and some interesting idea has struck me. This is a conjecture which will take a year or two of full time research work to confirm it although it looks very realistic. Unfortunately I cannot apply for post doctorate or a grant due to my work commitments but I would be glad to publish an article if a reputable CS journals would be interested. This may solve very hard practical problem but surprisingly it is difficult to monetize so I cannot do it in industry.

The only way to see if they are interested is to try. OTOH, it might be a better idea to submit this (as it isn't finished work) to a conference.

Or write a position paper and submit this to a workshop.

vague! meta! try writing it up on a blog 1st and getting feedback there, or just asking the question on stackexchange in the form "will this work?"

[Reposting a comment that got lost in the migration] See also this related question: What are examples of appropriate journals to publish new mathematical conjectures?

If we knew we could resolve the conjecture in a year or two, then it probably wouldn't be research.  More likely is that you can't and won't know whether it's possible to resolve the conjecture in a year or two until you try, so you shouldn't assume it can necessarily be proven/refuted in "a year or two of full time research work".

You can certainly publish an article based on a conjecture.  (One famous case is Subhash Khot's 2002 paper introducing the Unique Games Conjecture.)  On the other hand, you need to include some supporting information in the paper.  Why is your conjecture plausible?  Can you supply examples or applications?  What are its implications or connections with related work?  Answering these questions may be much easier than resolving the conjecture, but they can still require some serious work.
You're most likely to be able to publish the conjecture if there's no straightforward way to resolve it.  If it's clear in principle what you should try, and the only issue is that you don't have time to try it, then you're more likely to meet resistance (it may still be possible, depending on the publication venue, but this would probably rule out many of the more prestigious conferences).


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Final round of reviewing for a Program Committee
I've been recently involved in a Program Committee, and I was wondering what exactly was expected of the PC members from the PC Chair. Once all the reviews have been collected, are the reviewers expected to engage in a discussion about the paper? Or do they need to wait for specific questions from the PC Chair? Are the reviewers expected to comment on the other reviews?
In case it matters, we are using the EasyChair system, so everything is done online, and I don't know the identity of the other reviewers.

In my experience, usually the PC chair sets expectations by providing explicit instructions and guidance on the process.
In my field, the deadline for submitting all reviews is usually a week or two before the PC meeting.  That last week or two is reserved for a "online discussion phase".  During the discussion phase, reviewers are expected to read the other reviews on the papers they were assigned and discuss what to do on each paper, to try to reach consensus on the final discussion.  This might involve some discussion on points where reviewer opinion differed or on technical points of disagreement, for instance.  Each reviewer is expected to take the lead on beginning the discussion, without waiting for the PC chair to prompt you or ask you a specific question.  The goal is to try to reach a clear decision before the PC meeting in as many cases as possible, or at least reach agreement on what the strengths and weaknesses of the paper are so that a final decision can be made on an informed basis.
If there is no in-person PC meeting, the online discussion phase becomes especially important.
But that's just my personal experience and my field.  Practices may vary in other fields, for all I know.  If your PC chair did not instruct you on what he/she expected, it is completely reasonable to contact him/her and ask what he/she should like you to do.


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Mentioning Products of Companies in Technical Paper?
I am writing a technical paper for my college project. This is my first time so I don't have much experience in this arena.
I am writing about a philosophy used by Mechanical Engineers while designing a product. Now there is a situation where I have to mention a product and the company whose product it is.
I am saying this by:
... so popular that it has been incorporated by ABC Company in their XYZ Product suite ...

Now I want to ask whether I should mention that:
ABC & XYZ are registered trademark of ABC Inc.

If yes then where and in what format?

No need to mention the trademarks in a technical paper, although you could certainly cite their website if it talks about the product.
I generally cite anything that I think the reader could get more information about that is pertinent to the topic.  That said, a paper isn't a web page, and you shouldn't litter it with gratuitous cites.

If you're concerned, then you can say:
... so popular that it has been incorporated by ABC Company(R) in their XYZ(TM) Product suite ...
with appropriate glyphs for "registered" and "trademark".
But that said, I don't think it's strictly necessary to mention trademarks unless you have a compelling reason to do so.
(An example of a comeppling reason to do so would be if you had to run the paper by the company's lawyers first and they want you to refer to the product in a specific way. If so then in the best interest of collaboration you should do what their lawyers say.)


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Master of Engineering vs Master of Science?
I am a Final Year Mechanical Engineering student.
I want to do my Masters in the Design Engineering field.
Currently I can see 2 options:

Master of Science - offered in many Universities ex: GeorgiaTech.
It deals more with research. It requires a research thesis most of the times.
It gets completed in about 2 years.
Master of Engineering - offered in few Universities ex: Cornell University.
It deals more with developing your skills required for doing a job in that field.
It does not require a research thesis. It gets completed in a year.

So, my question is:
1. What exactly do we learn/develop skills/improve/do, etc in each of these programs.

I am unable to get a clear picture as to what exactly will be the change in me brought by each of these programs?
What distinguishes a M.S. Graduate from a M.Eng. Graduate & vice versa?
And which one of these Graduates get jobs in Companies easily in the related field?

How did the recruiters you talked to answer this question?  You did ask some recruiters this question, didn't you?

which recruiters are you talking about @JeffE?

Any recruiters.  The ones who regularly visit the school where you are getting your MechE degree, at career fairs and the like.

The main practical difference between the two degrees, as you point out, is the requirement of a research thesis for the MS degree.  Generally, if you have aspirations of eventually getting a PhD, you should strongly consider the MS, as research experience or potential is a large factor in being admitted to a PhD program.
To answer your specific question, you should be a better researcher after completing an MS, and you will be better prepared for further graduate work.  With an ME degree (considered a "terminal" degree), you'll simply have a Master's degree and (potentially) may have spent more time on your coursework.  Whether or not this prepares you better for a position in industry is debatable -- as you say, many ME programs are one year, which may actually include fewer classes than an equivalent MS (although I've generally seen ME programs that have one or two more classes as a requirement than the equivalent MS degree).
As to which degree leads to more jobs in industry, I'd say it's probably about the same.  Getting an MS will certainly not limit your competitiveness for industry jobs, while (as I already mentioned), an ME may limit your competitiveness for PhD programs.

I absolutely do not aspire to acquire a PhD degree :)

What you say I have already read on the Internet.
Can you please give some information from your personal experience?
Thanks for answering my question.

If you don't want to get a PhD, then I'd suggest finding a program that best meets your particular industry goals -- e.g., if you want to design cars, find a program that focuses on that.  Your goal should probably be to learn as many of the technical details as you can.  The only trouble with that plan is that in most engineering jobs you end up learning the specifics for each job once you are employed.

From my personal experience: I got an ME degree on my way to a PhD :) (but I was also already enrolled in the PhD program and it didn't make sense to put together a thesis at that point).  Friends who got terminal ME degrees went straight into industry and were competitive for the positions.  They do not intend to get any more degrees.  I've had friends who got MS degrees also went into industry, and others who went on to get their PhDs at other schools.

One additional comment: in MechE, learning how to use real tools (both physical and software) is important, so I might suggest taking classes where you do a lot of hands-on work in addition to the theoretical work.

I do not understand how a PhD degree can help engineers in their jobs. Its fine for scientists/physicists, etc but how is a PhD degree going to be of any use while working for a company?
Until & unless for example, you work with Shell & have done a PhD on various types of lubricants. Then its fine.
But on a broader perspective, lets say for a Design Engineer how will the company benefit from the research study of a prospective employee?
I am a bit confused on this aspect, so please bear with me if I may have been a bit incorrect here, Sorry.

A PhD degree is useful for working in research and development operations, where you're more likely to be working on "leading edge" stuff. A master's degree encompasses some of that (especially if you do a research thesis).

I never understood why a Masters in Engineering would limit your ability to get into a PhD program, undergraduates do not have to do a thesis and their coursework is much easier. Wouldn't having an M.E. be better than a B.S. but worse than a M.S.?

I have studied a MEng which is accredited by the engineering Council UK for chartered status. I disagree that in a MEng you don't do research, as I recall I did two group projects and a Thesis. With varied coursework and subject matter and examinations. You can do a PhD from both a MEng and MSc, it does not matter how you start, it's how you finish is the old saying.

MSc, MEng and a PhD are all high level degrees, in the UK the highest you can be in industry from the engineering council Uk is a chartered engineer. Minimum qualification for this is a MEng or a Msc accedited by the engineering council. Even with a PhD the maxium in industry is a chartered engineer, unless you intend to go into high level research or goverment, or a big multinational or a Research and Development role then a Phd is usefull. Saying this you dont learn any new core subjects as such on a PhD program rather you research it and draw from you exsposure, experiance, and academic knowlege. After all what can they teach you academia after you get a master.., it say's what it is on the tin if you like .., you have mastered your trade.
'Chartered Engineers develop appropriate solutions to engineering problems. They may develop and apply new technologies, promote advanced designs and design methods and introduce new and more efficient production techniques, or pioneer new engineering services and management methods. The title CEng is protected by civil law and is one of the most recognisable international engineering qualifications'.
http://www.engc.org.uk/engcdocuments/internet/Website/CEng%20Leaflet.pdf

MSc - focuses on theoretical work, research and is thesis based
MEng - focuses on practical applications of theories, less research compared to MSc, mostly course based work.


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My paper was accepted in Springer International Conference and National conference. What to do?
We had prepared the paper and applied for National Conference. After some days came to know about the International Conference and improved the paper and applied for it. After a month we got an accept mail from Springer Conference(Not expected as we are beginners). Today we presented our paper in the National Conference and our paper was selected as the Best Paper as well as got shortlisted for the International Journal. Now we are totally confused what to do ? Can we accept for publishing in the Journal but the Slight Modified (Improved) paper will be getting published in Springer Conference in July this year. Will this lead to any problem ?
This would help a lot in boosting our resume and also getting an Admit from Good University for my Masters.

This is why you NEVER simultaneously submit a paper!

We thought our paper might get rejected from International Conference. So applied for National Conference as we are final year Undergrad students. We may not get time(Or everyone will be busy with their corporate jobs ) to apply and publish in the next conferences.

@DanielE.Shub: That's true in fields where conferences and papers are "tightly bound"; where this isn't so, it's not so big a deal.

I am surprised that this question has not got any up votes besides mine. While it is not a good situation to be in, I think it is an important question, that is reasonably well asked.

The only thing you can really do here is to contact the organizers and publishers of both journals, and indicate what is going on. More likely than not, you will need to withdraw one of the papers, as publishing both papers under very similar titles with identical scientific content (or very nearly so) is considered inappropriate.

At least in computer science, the most likely outcome — and the correct one — is that both submissions would be rejected.  (Or at least that would be the outcome if one of the conferences hadn't already happened.)

You must withdraw the second conference submission.
Simultaneous submission of the same paper to multiple conferences or multiple journals is completely inappropriate.  If you do not withdraw, you run the very serious risk of having both submissions rejected and your invitation to the International Journal rescinded

This would help a lot in boosting our resume and also getting an Admit from Good University for my Masters.

No, it wouldn't.  In the long run, publishing the same paper in multiple equivalent venues will only hurt you.  To put it bluntly, that's a form of academic fraud.  If I discovered that a graduate student in my department had done this, even before they were admitted, I would recommend immediate dismissal.

Oh ok ! I'm a beginner I didn't knew all these stuff thanks a lot. I will withdraw the national conference one.

@PradeepG How do you propose to withdraw a paper that has already been presented?

@David This was before presenting the paper. I had applied for 2 conferences and I got this doubt while deciding to select one conference.

@PradeepG I'm confused: your question says, "Today we presented our paper."

@David Hmmn :) My bad that was a long back ago. We had presented our paper but in that conference proceedings they did not publish the paper. Later they offered us to get the paper published in one of the International Journal which didn't happen.

@RameshSuresh It is excusable that you as a beginner did not know this, but it is inexcusable that your supervisor/mentor did not prevent this situation from happening. Duplicate submissions are considered a fraud at expense of others, since you wasted time of two sets of reviewers to get essentially the same answer (positive=your research is good). Reviewers are in high demand and the work is tedious so, yea, people have a reason to be angry about this.


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Is it ethical for an author to cite their own work with themselves as first author when they are not first author?
I was reading through a journal article by an author. Let's call him Author X. The author while referring to some of his own journal articles cite them as Author X et al., even though Author X is not the first author in the cited article. Is this allowed or should it be treated as academic dishonesty?

Assuming there is no citation style would appear it as "Author X et al." then I believe YES; it is dishonest. Reviewers/Editors supposed to detect this before publishing.

Could the answer to this depend to some degree on the author-order-convention in the field? In my field authors are listed in alphabetical order, so listing a different one first would be somewhat odd, but wouldn't really amount to claiming a more important role in the paper. Also, it might make some sense in the case of undergrad research where the supervising researcher of a larger group doesn't have the earliest surname.

The only reason I would use a formulation such as this is if the work being "cited" were multiple works performed by a changing group of members with a "constant" member who was probably the group leader. And, even in that case, I would use the formulation "X and coworkers," rather than "X et al.," to indicate that the it's not a "direct" citation, but a matter of convenience. The reason for this is that it's quite distracting to have to write:

as discussed in A et al. [cite], B et al. [cite], C et al. [cite], A et al. #2 [cite], . . .

when there's a bunch of different references that are all part of the same research effort.

I have seen "X and coworkers" a couple of times and would also recommend its use.

It depends on how literally you are using the word "cite".  If you mean the articles are listed in the bibliography with the authors in a different order from how they were published, or the author order is changed in a formal citation such as "(Author X et al. 1994)" even if the bibliography is correct, then yes, it would be considered dishonesty, because it misrepresents the author listing.
On the other hand, it's possible to give correct formal citations to some papers and then go on to talk about "Author X et al." without actually implying that this represents author order at all; instead, you are just highlighting X among the researchers who have worked on these problems.  Overemphasizing a particular author's role could be offensive, but it's not necessarily dishonest in the same sense as misrepresenting the author order on a specific paper.  (And it might even be appropriate in some unusual cases.  For example, imagine that X has been working in this subfield for many years and has published a dozen papers, each with a different student as first author.  If you need a brief way to refer to this group of researchers as a whole, then "X et al." might not be crazy.)

Even in the case you describe, I'd be leery of using the "X et al formulation". It seems unfair to whoever the first author really is.

@Suresh what if you are in a field where authorship is alphabetical and the name starts with Z?

I'm not sure why that makes a difference. I agree that in alphabetical ordering the "first" author gets unreasonably prominence, but listing the authors as "Z et al" doesn't solve the problem.

I have a hard time seing any other answer than NO, it is not ethical. If the paper referenced is published it is very clear. If one neds to reference an individual other than the first author, it is always possible to quote the name followed by the refeence for (a very hypothetical) example

... X made the Y analysis (Z et al., yyyy)  ...

If the work is unpublished, it typicaly should not be referenced using typical references so then the "personal communication" or whatever for would be pertinent could be given in any way relavant to the particular case.
The main point is of course to give credit where credit is due. so,if it is clear that someone has performed a very specific task (indicated in the paper referenced) then it might be ok to point that out but never to change the original citation which has to match the reference in the reference list, which in turn has to match the published article. So for me exceptions to the general rule are vanishingly few and I have never encountered a case where this has happened either as a reader of journals or as an editor.

It is definitely misrepresenting the situation, but I am not sure it is intentional. I met several (where several means a large number) researchers who were not aware that the "et al." phrase can only be used with first authors, and they used it in the meaning of "and his/her coworkers". If the given person's mother tongue is not English, I would say it is more of a mistake than intentional dischonesty.


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Going for PhD or MS in research right after under graduation?
I have a bachelors degree in computer science and am going for PhD or research MS, but I do not have research experience.  Can I expect to successfully obtain a PhD?  What are the major problems faced by a student who has no prior research experience but has good technical knowledge in computer science (but perhaps less so in mathematics)?

I think removing the "in India" part might make this sufficiently general to be of value to all.

If you don't have any research experience, how do you know you want to become a researcher?

@Paul Hiemstra Inspiration from lot of other people and Interest towards research are the two factors that motivated me.

In certain disciplines it's very common to enter a Ph.D/MS+thesis program straight out of an undergraduate degree. Computer science is one such discipline. Usually you spend the first year or two in the Ph.D program getting up to speed and doing research. For an MS+Thesis program, things are more compressed, but you also aren't expected to produce research of the same scope.
While it's always better to have some research experience as an undergraduate (and this helps your grad application) it's not a requirement for success at the graduate level.

I want some more in depth information. General explanation is found everywhere even in university websites.

@PradeepG Suresh gives you the information that is available given the limited details you provided in your question. Bottom line, it will be a bit harder to get in, but not impossible. You'll have to work hard, but every PhD has to.

The short answer to your first question is: yes, you can expect to successfully complete a Ph.D. For the second, you'll need maybe a little "catchup time", but nothing seriously bad.