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Interpretation of a PhD degree in a very broad, interdisciplinary field
Back when my older brother started his PhD degree I asked him what it meant to be a doctor in something other than medicine. I don't recall the exact wording he used, but the idea he portrayed was that you take a field, a narrow and specific field, and you specialise in it to a level at which when you are done, you have become one of the ultimate experts in that very specific field.
For instance if you are working with combustion physics, you might be one of the leading experts in efficient 2 cylinder, ultra-light engines made out of refined aluminium... Alternatively if you are into neuroscience you might be an expert on a particular neurotransmitter re-absorption in a particular zone of the brain following heavy exercise (or whatever, hopefully you get the point). It might be an opinionated view of a PhD but I feel it's a common way to look at a PhD degree; a certification of expertise.
Fast-forward 15 years... I am about half-way in my PhD studies in the highly interdisciplinary field of bioinformatics, where statistics, mathematical modeling, physics, molecular chemistry and programming boil together with cell biology, to top it all you typically have a theme spice, which in my case is cancer biology. I have a growing feeling that I am getting stretched thinner and thinner by the day, instead of becoming increasingly competent in a specific field, I become semi-competent in increasingly many fields.
That being the case I am not sure I (or others like myself) will fit the "definition" above. I would appreciate some perspective as to how one should be seeing highly interdisciplinary PhD studies and the development (as a scientist and a professional) that graduate studies entitles. Subsequently, how should one go about to profile him/her-self to future employers, seeing as there is no one natural field to pursue, but rather many different ones.

Just because you are in a highly interdisciplinary field doesn't mean you shouldn't be specializing on one problem for your PhD.  Have you found a dissertation topic yet?  Once you do, you'll be forced to specialize as you get more involved with the project.  Certainly, you'll still leverage the interdisciplinary stuff, but you'll become an expert on that one problem (and maybe it will lead to a cure for a specific type of cancer!).

@ChrisGregg I totally agree with the following statement; "Just because you are in a highly interdisciplinary field doesn't mean you shouldn't be specializing on one problem for your PhD." The reality of the matter however that my projects dont seem to follow a red line, and I feel I do not get to dive in deep to any one subject, but instead constantly need to jump from a subject to another. I suppose that's a valuable skill in itself but still frustrating to not feel the sense of accomplishment

Hmm--that does sound frustrating.  I'd suggest a concrete dissertation proposal (if you haven't done one already) which will force you to specialize to get the project done.  Good luck!

As I commented on another board just this morning, the goal of all higher education is ultimately to learn how to learn. As a PhD-level scientist, you need to be able to understand, master, and solve problems in fields which you may have never seen before you started to work in them. This means that you need to have a well-developed process for assimilating information, synthesizing it, and analyzing it. You need to be able to evaluate what is useful or not, what is correct or not, and what might work and what might not.
In an interdisciplinary field, your challenge is even harder, as you are trying to assimilate potentially disparate fields of knowledge and combine them into something more than the sum of the parts. This requires learning different jargons, different attitudes, and different approaches to problem-solving and understanding the world. This will actually be even more useful, because this means that you can be pretty good at a lot of different things—which gives you an edge over someone who's outstanding at one thing, but only one thing.

I completely understand your feeling. I can tell you that many other people in this field feel the same. This has nothing to do with how smart or how good they are. This issue also bugged me a lot, but I can offer some insights:

Bioinformatics/computational biology is really huge and you cannot be an expert in all aspects. Even if you look at senior scientists in this field, I do not think there is someone who is an expert in all subfields. You simply can't master all the physics, math, CS, chemistry and biology at an expert level - even in a much longer time than a PhD.
You can still have a huge impact without being a super-expert in every subfield. Just look at some of the research published in top journals. The reason is that you will have knowledge and a way of thinking that people restricted to a single field may not have. From personal experience, I can say that this is a significant advantage for asking certain types of questions and coming up with certain ideas that single-field specialists won't come up with.
After a while you will realize that you actually are an expert. Maybe not in the sense that you know everything about everything, but you will see that you can give good advice to other people, foresee potential problems, and so on. In addition to knowing a lot about computational biology, you will become an expert in things such as quantitative modelling, applied machine learning and "big data" analysis (I hate that term), skills which are very useful in a wide range of fields.
The fact that you cannot become an expert in everything doesn't mean you should neglect learning. On the contrary, you should constantly try to expand your knowledge in all related fields. And yes, it can be more difficult than learning only one subject.
Finally, in the end you will be working on a specific problem in a given biological problem with a given set of tools. That problem is what you really need to be an expert on.

Thank you! One comment I have regarding your #3; I have long considered the same thing, but lately I have started to doubt it, as it has become very obvious that I do not get to develop as much in those fields as what my future title would imply. I mean as a bioinformatician you are sort of expected to know your way around different ways of normalization, data mining, machine learning etc, but yet again I get practically 0 guidance in those fields, and I often do not get the chance to work on those subjects. So how exactly do I get competent in those fields if I don't get to work with them?

@posdef I agree that there is a problem with supervision and education in the field. This is mainly because the field is relatively new. This puts more responsibility on you. For example, if you want to get more training in machine learning, initiate a mini-project in that direction. You will learn a lot even without expert supervision, but you should try to actively seek some guidance as well (it doesn't have to be formal).

In my opinion, a PhD is much more than a deep expertise in a particular field.  A PhD is a certificate of the ability to do science.  That's why your PhD is more broadly applicable than in your particular expertise and that's why some people can change topics dramatically after their PhD: from particle physics to atmospheric science, from space science to ornithology¹.  In a German Habilitation, which is I think a step on becoming a professor, one has to write a review of a field that is not ones own.
The other day, I came accross a job advertisement from the British Met Office that had the following requirements:

·         Proven ability to conduct scientific research, displaying initiative, independence and analytical skills.
·         Evidence of the motivation and drive to overcome obstacles in order to solve scientific problems.
·         Evidence of the ability to write software to address scientific questions.

A PhD in any natural science proves exactly that; in any case the first two points, and in many cases the third point, too.  Of course, domain-specific knowledge is a plus, but it may not be a necessity.  Therefore, I think you should profile yourself as a scientist.
¹Scientists performing stratospheric radar measurements discovered an odd diurnal pattern in their measurements near the Antarctic coast.  It turns out a flock of birds was flying through the radar beam.  One persons noise is another persons signal; said scientist is now cooperating in ornithological research.

A PhD is a certificate of the ability to do science. — ...except, of course, for all those PhDs in fields other than science.  For example, philosophy, after which the degree is named.


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My advisor refuses to write me a recommendation for my PhD application unless I apply to his lab
I got my master’s degree in China and had worked for two years as a visiting student in the US. Although my master thesis’s supervisor promised to write me a recommendation letter, my visiting student advisor refused. He is the corresponding author of all my publications. What's more, research experience in his lab was included in my personal statement. He said he would offer me a recommendation letter only if I apply for his lab. When I asked whether he could recommend me for other universities, he did not reply to my email. Is there any possibility that I get an offer without his reference letter? How should I explain this to an admission committee?

Does the visiting student advisor make a habit of not giving recommendation letters for students he would like to keep?

This isn't an answer, though just to let you know, some people, some advisors, some professors are just jerks.  Good luck!

I don't know. But he did something worse than that to one of my coworkers who he wanted to keep in the lab.

You write "he did reply my email".  What did he say in his reply?  Or did you mean to write "he did not reply to my email"?

I mean"he did not reply to my email". Sorry for not making myself clear.

Be glad he is not writing anything, others have been known to write trashing letters to candidates they want to keep for themselves.

After you have secured yourself a PhD position elsewhere, please put in a formal complaint about your advisor's shockingly unethical and unprofessional behaviour to the authorities at the university.

Just to emphasize Jack Aidley's point - this is unethical behaviour, and you have every right to be distressed by it. (It should also be a gigantic red flag against applying for that lab - is he going to refuse you a recommendation letter after your PhD unless you do your postdoc with him?) As soon as you have the chance, do consider reporting this appropriately, to both universities, so that this doesn't happen to other students after you.

If you have his position on writing "I will recommend you for my lab" - then that itself is a recommendation ("I would hire this person"). But I agree with others - this person is behaving unethically and needs to be called out for it.

You will need to find another reference.
I recommend not keeping this supervisor up-to-date on your application status.
When asked why his reference was not included, probably you could just say factually and without sounding judgemental that the student advisor offered a reference only under condition that you would work for them, so you sought another reference [pretend that you do not realise what that means - coming from China, you can probably present it, if asked, as if you assume this may be the norm to only give out references under these conditions; of course, this is not true, but I think your best bet is to take the "naive" route].
You also have publications with this student advisor, so that already proves that your work is good enough to pass peer review - a direct reference from them would be nice, but is not anymore vital at this stage.

+1 for this, especially the part about not sounding judgemental and just stating it as fact.  They will likely assume you're just not familiar with how bad that is, and rest assured, will make their own negative conclusions about it. It's a shame you're in this spot, but best to separate yourself from this person.

You gave me so much confidence. As you said, it is better to just state it as fact without making any judgment.

Yeah, this sounds like the approach to take. It might be worth stating this in a cover letter, instead of waiting to be asked (which might not happen if the lack of such a recommendation is deemed a critical flaw in the application).

@E.P. That contradicts my and djechlin's suggestion to downplay the judgement on the original referee's refusal (whichever variant - djechlin's or mine - OP wishes to use); it clearly shows that OP considers this a problem. Given that OP has published papers (more than one!) with the supervisor, the actual reference may not be critical.

@CaptainEmacs Actually, yeah, I'll back that one down. It comes down to what other references the OP can get - if it's only an old prof from three semesters ago then that's a big enough problem that the application might stall before interview stage, with the panel asking why no one from the publications put in a reference. I see now that the masters' advisor did write a reference, which mostly kills that concern.

While not illegal, the behavior of your advisor is completely unethical. The behavior is so bad, that it can tarnish the reputation of an entire department. I suggest you attempt to get his position in writing. Make sure you clearly understand that he will recommend you for a position in his lab but no where else. Not recommending someone to a particular program, or even every program, is not unethical. Limiting letters for people to only places where you will benefit is unethical.
Once you have it in writing (or at least a clear understanding), you should approach your department chair asking for a letter of recommendation. Explain that your supervisor is willing to write a letter for his lab, but not for any other labs. Then show him the email. The department chair will also likely feel guilty and read over your papers and write a reasonable letter. More importantly, the department chair can explain why you don't have a letter from your supervisor (i.e., that the chair believes the supervisor is happy with your work, but refuses to write letters because he does not want to lose you). The chair will most likely then have a private discussion with the supervisor about his behavior.

This assumes that the atmosphere in the department is generally not toxic. In general, I would assume that, but if OP does not know the precise dynamics behind what transpires, this slightly "aggressive" (not really, but you know what I mean) approach may lead to developments out of their league.

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Should a professor give students a take-home exam when the answers might be available online?
A professor at a top USA university recently assigned a take-home exam for a masters-level computer science course. One of the questions was extremely difficult, but the answer was available online. However, the exam clearly stated, "Do not look online".
Most of the students know enough to discern whether the online answer is correct. It will be practically impossible for the professor to detect any cheating, assuming there is basically only one way to answer the question.
While writing the exam, most students will assume that the answer is available online, as many answers are, and that some students will inevitably cheat. They will know that the cheaters will have an unfair advantage, and thus may obtain the highest grades. So there is pressure on all of the students to cheat, to eliminate the unfair advantage.
However, there is an extremely remote chance of getting caught, and being penalized for academic misconduct. Moreover, the honest students naturally want to be honest, because they have integrity.
I have four questions:

Is it ethical for a professor to give such a take-home exam, which tends to reward and encourage cheating?
If the professor becomes aware that one answer was available online, should he discard all answers to the extremely difficult question?
Should the Dean intervene to ensure fairness and to stop such take-home exams?
How can an honest student report that the answer was available online, without risking retaliation? (The student has no evidence that the professor or Dean care.)

The professor clearly does not care that the solution is available online: the direction to not look online means they are aware that the solution may be found there. Your assertion that there is only one way to answer the question is very wrong. If the question is so difficult, the professor is not looking for you to solve the question, but to see what you do to try to solve the question. Should you provide the online answer, I expect you will get zero marks.

By looking at the online answer, the student can learn how to approach the question. It's like reverse-engineering any existing technology. It's much easier to "re-invent" something when the solution is right before your eyes.

Plus, the prof may plant a few subtly wrong solutions online. A student copying them will indict themselves, including information where they got the solution from. It is in the students interest not to cheat, as cheater will be punished severely, I expect.

@CaptainEmacs: Reminds me of the "canary trap" idea in Tom Clancy's Patriot Games (the novel, that is).

You're right, the prof could plant some wrong solutions. But in reality, most profs don't care enough to bother with that. Due to professors' and university administrators' general lack of vigilance, cheating is common, in my experience, and the cheaters rarely get caught. This degrades the value of the degree for everyone.

"Most profs" is not a concrete person. You never know whether the concrete prof is or is not going to check. Most people I know personally, try honestly to check. With various elaborate ways to cheat nowadays, it is not serious to expect academics to spend significant time to investigate potential cheaters rather than prepare good material for those who are interested to learn...

contd.. What has devalued is the grade value of take-home coursework, as compared to exam grades, although home work is the one students learn from most. When fake gold coins are hard to detect, you will have to make do with the mint to give out silver coins, but you really can't blame the mint for this.

What you need to do is find a assignment where the first hit Google gives doesn't work. Then assign that. I did this once by accident, and got a significant fraction of wrong answers.

To answer in order:

I don't see why it's unethical for the professor to give a take-home exam. I don't dispute your (implied) assertion that this may benefit those who are willing to ignore the professor's explicit directions -- but that's unethical of them, not the professor, in my opinion.
This is entirely up to the professor. It would likely be within their right to do so, but my guess is that most professors would shrug their shoulders and make a note to themselves not to ask that question on a take-home exam again. You'll argue that this is unfair to students who follow the professor's instructions -- and you're right. Unfortunately, however, the world is not fair. That doesn't mean I -- or the professor -- condone cheating, but the professor likely knows that this risk exists with a take-home exam, and has judged it an acceptable risk.
What is the dean going to do in this situation? Force everyone to retake the exam? This may not be feasible -- for example, at my university, some classes have online sections off students who aren't physically present on the main campus. This precludes in-person exams oftentimes.
My advice would be to use a throw-away email account if you're so inclined. Keep it anonymous, but alert the professor. Understand though that they may choose not to act on the information -- and there likely isn't much you can do.

I don't mean to this be harsh -- just realistic. A better solution for the professor might be to explicitly allow online resources, but then structure the exam such that those resources don't help students any more than memorizing the material would. The easiest ways I can think of doing this are (1) opinion-based questions and (2) time limits that make accessing such resources a costly waste of the available time.

On the other hand, as a leader, the professor is surely responsible for encouraging ethical conduct, for helping to foster a culture of honesty, and for helping to maintain respect for the university's degree. If the prof prohibits cheating, but effectively allows it without any likely punishment, and rewards the cheaters with higher grades, then he is in effect encouraging cheating. This is demoralizing for the honest students, and is likely to convert the marginally honest students to dishonest students. So the professor's negligence has contributed to corruption in our society.

The Dean could stipulate that take-home exams should not prohibit online research. I assume that setting ethical and academic standards is part of the Dean's job, which makes sense since most professors do seem to "shrug their shoulders" on ethical issues such as cheating. The particular program I referred to is for students who are physically present on campus. If we limit the discussion to only the on-campus scenario, we can avoid muddling the discussing with unnecessary complexity.

A throw-away email account seems a good idea.

Re: (1) Opinion-based answers, this is not applicable to quantitative and technical subjects such as computer science, which focus on computations, procedures, and obtaining the correct answer.
Re: (2) If short time limits are desirable, why bother with a take-home exam, and its inevitable opportunities for cheating? A traditional classroom or exam-hall setting would avoid those problems.

@Photon: I agree that the professor should encourage ethical conduct, but I disagree with what I see as your (implied, at least) assertion that take home tests are unethical by design. Do they (take-home exams) open the door for unethical behavior? Yes, but I choose to believe that those who would act unethically (and copy answers online) would find a way to do so regardless of where/when the test was conducted.

@Photon: As for the dean's responsibility: yes, they could stipulate that. But my guess is that politically, most deans wouldn't see it as a worthwhile pursuit. Here's why: faculty will see that at best as a (perhaps well-intentioned) imposition on their teaching; at worst, they will see that as an undermining of their authority in the classroom (with the potential for further restrictions down the road).

@Photon: As for the opinion-based questions, I disagree that they are not applicable to subjects such as computer science. Perhaps for your course they are not, but I can easily construe a question such as "How should I design this software component? Explain what data structures and algorithms you would use, and why."  If a student could reasonably defend their design, it could lead to multiple acceptable answers.

@Photon: And as for the short-time limits, what if a professor wants to test on a wider spread of material than would be available during the normal class time? If the average class is only an hour long (maybe 1.5 hours), that may not be sufficient time in their mind to test on all of the covered material. A 3-hour window to take the exam at home, then, may be an acceptable alternative. That's a hypothetical to an extent, but not a far-fetched one -- I took a 4 hour take-home exam last week in a course (we had 4 hours to answer the questions, type them up, and submit them online).

Your suggestion that "A better solution for the professor might be to explicitly allow online resources" makes sense. We know cheating will occur, and it will typically not be caught. Pretending otherwise just hurts the honest students. However, re: in-class exams: Cell phones can be prohibited, which prevents internet research. Also, covert team effort is much more difficult in an exam hall. Therefore, exams with restrictions should be held in exam halls. In contrast, take-home exams should not be subject to restrictions, as they are unlikely to be enforced, and only hurt the honest students.

@Photon: You seem to feel fairly strongly about this, and I've made my case about as best as I feel I can. Fundamentally, I agree with you that this restriction isn't a great one -- but I disagree strongly with your assertion that it represents unethical behavior on the part of your instructor. I hope you find an answer to your liking.

Thanks for expressing your point of view. I've been very interested to read your comments, even if I haven't agreed with them all.

as a leader, the professor is surely responsible for encouraging ethical conduct, -- And he did just that, by instructing you not to look online.

Would math.stackexchange.com be an admissible “online resource"?

It isn't good practice to set an assessment (of which a take-home exam is simply a time limited assessment) where the answer is easily available online.
This goes against one of the first principles of educational integrity, which is set to assessments which aren't easy to cheat on. Setting an assessment where the answer is easily available could even be said to be encouraging cheating.
For a programming assessment at this level, I'd expect students to look at example code fragments, to research algorithms that could be used etc. That's just normal practice. In this day and age, all that information is on the Internet by default. Many programming environments don't even have offline help documentation.
I would note that take home examinations are particularly susceptible to contract cheating (see, for instance, my recent paper on exam cheating here). They are unsupervised and third parties love to complete these for students as they can charge a premium due to the short deadlines. It's often difficult to see what a take home exam is designed to accomplish over a standard piece of coursework (or an invigilated exam).
I did note people advocating for professors to deliberately put wrong answers online to see if students use them. To me, that's a severe breach of principles of academic integrity. It might even encourage a student to cheat who would not have considered doing so otherwise. In the UK, I'd expect that to be treated as a staff disciplinary issue. With the number of law firms now who widely advertise on the Internet and represent students in such cases, the university (or professor) may also find themselves at financial risk if this breaches documented university processes, policies and regulations.

Setting an assessment where the answer is easily available could even be said to be encouraging cheating. — Similar argument suggest that driving an expensive car encourages theft, selling matches encourages arson, and walking alone at night encourages sexual assault.  No.  Assuming honesty may be naive, but people who violate that trust are not victims.

I agree totally @JeffE that students should know when they are acting dishonestly (and usually do). But current recommendations on best practice are all about removing temptations. Most academic processes are designed to protect students - generally a good thing. The same holds for academic misconduct processes. There is an alternative analogy to consider when the owner of an expensive car leaves it unattended, with the windows open and the keys in the ignition. Stealing the car is still equally wrong, but it would be less of a surprise if it ended up being stolen.

Pretty much for everything that is reasonable to ask in lower-level college math courses, materials that help can be found online. So if I follow your advice "it isn't good practice to set an assessment where the answer is easily available online" this would in practice mean only in-class assessments.

@PeterShor, I would say that it is approximately true that assessments (as opposed to drafts for critique-ing, for example) nowadays, of lower-level material, cannot easily be done outside a classroom.

@PeterShor, for formative assessment, I think it's fine if solutions are available online. For summative assessment in the maths case you mentioned, then yes, I believe that at least part of the assessment needs to be supervised. They may be exceptions where there is an original component (e.g. a statistical analysis of fresh data, or an accompanying written reflective exercise).

For the original question, I think the big problem is that for programming, class time is really too short for any reasonable assessment. And coming up with assignments where the internet won't give a lot of help is hard.

Nudge theory seems relevant here:  https://en.wikipedia.org/wiki/Nudge_theory
We should want students to behave honorably, so that they will consider themselves to be honorable. That can be accomplished to some extent by nudging them toward honorable behavior. If they consider themselves to be honorable, then they will avoid dishonorable behavior, to avoid cognitive dissonance. That would be good. The opposite is also true. If we encourage dishonorable behavior, then they might behave dishonorably. Hence, they will see themselves as dishonorable, and behave dishonorably henceforth.

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Do undergraduate students usually share poster award money with their PhD student supervisor?
I participated in an poster competition (for undergraduate students) and I won an award with a decent amount of money. My research supervisor was a PhD student at a researcher's lab. Do people usually share the money of the award with their research supervisor, with the PhD student since he helped me a lot with my poster?

Just to be clear about the circumstances: Did you create the poster out of your own research or study interests (in which case it is yours), or as a part of your work as an RA or something like that (in which case the poster, as well as the award, might formally belong to the university)?

Things are a little unclear here. SHould I assume that in an official sense a faculty member was the advisor (who gave responsibility to the grad student to work with you and be mentor)  or was the grad student mentoring you as a totally separate activity  that had nothing to do with his/her PhD/research activities in the faculty member's lab?

@O.R.Mapper I cannot think of a single scenario where the prize money for a research competition would belong to the university where the research was conducted. The only ownership the university has, if any, is over the intellectual property, not over prize money that doesn't involve transfer of intellectual property.

@ff524: The same way in some jurisdictions, bonus miles from flying during a business trip belong to the employer that paid for the trip, prize money might belong to the employer that paid for creating the poster that won the prize. I don't think it's likely, but it's something that needs to be found out before thinking about whether or not to share the money.

@O. R. Mapper At my university they offer undergrads the opportunity to work in a research lab where the undergrad is paired with the master's or PhD student working for a researcher to help them with their research. For me, the researcher paired me with a PhD student in his lab. I did most of the lab bench work but it was not my own project- because I am just a summer undergrad student.

@Carol it was a faculty member that I helped with his research project

I'm a PhD student who often supervises more "junior" students (masters students and undergrads). When I do, they keep any money they win (or if it was a group effort, it is equally divided between all the students, not including myself and faculty supervisors).

That is what I thought would be the case thanks.


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How important is GRE in Econ Phd Applications?
Does GRE play as a cut-off point in one's Economics Phd application even though s/he has a strong profile including 4.0 GPA, strong recommendation letters, good SOP, and relevant research and teaching experience?

Every department considers these factors differently.

Let's say Econ departments in US top 30 schools - Do they really auto-reject your application if the quantitative score is not above 160, without even looking at other factors?

My image (without evidence) is that economics is more likely than other disciplines to use cutoffs for things like GRE scores, GPA, etc. to simplify their jobs and have no qualms with who they might be missing out on, because they see admissions  as a benefit-cost analysis. I could of course be wrong.

Yes, it does, at a large number of, although certainly not all, top economics departments in the United States. Indeed, they have a lot of applications to read from perfect applicants (at least on paper). Why should they give any exceptions?
But they do give exceptions. I don't know entirely your circumstances, and certainly mathematics isn't economics. But from my own experiences, having 1. written letters for people with bad mathematics subject test GRE scores and 2. being swayed when I've been on committee to admit people with bad mathematics subject test GRE scores, I would encourage at least one of your letter writers to contact someone at each of the schools you applied to to keep a lookout for your application/not throw it out immediately presuming a GRE cutoff, especially if other parts of your application are quite competitive for the schools you are applying/have applied to.

In my experience with economics, it's all over the place.  Some departments do seem to use it as a cutoff, but increasingly more seem to be coming around to using them only at the margins.
This especially holds true if you have good recommendation letters and research and teaching experience; it's difficult to get those things before you start your PhD.  They likely make you stand out well above the crowd.  Heck, it's not unusual for full PhD graduates on the job market to lack teaching experience.
If a GRE quant score is going to be a problem, I anticipate it would matter more at the most highly selective institutions.  Places that only accept a tiny fraction of near-perfect students have few reasons to compromise on any attribute, and GRE scores are an incredibly convenient standardized way to compare everyone.
I've spoken with faculty on admissions committees at both large public research universities and small, selective private universities, and while you can't use my anecdotes as the whole story, the responses I get are invariably that they rely as little as possible on the GRE.

You can contact the admissions department at the schools you are interested in if their website does not explicitly indicate a cut-off.  A strict cut-off is rare, but does exist.  If you are not getting a straight answer from them, your only option is to just go for it.  There is a lot of unpredictability in PhD admittance decisions.
In my case (social sciences PhD), I had a GRE score that was less strong compared to my GPA, and it was mostly a factor in whether or not I would be offered a scholarship.  At the end of the day, my GPA and recommendation letters were strong enough and I was offered the funding.


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What is the usual process for a paper after getting accepted? Can you still make edits for readability?
We have submitted a paper to a journal,
and received comments from the reviewers.
We are about to submit revised paper and response letter to the journal.
As we revise the paper,
it sometimes bugs me that the paper is not quite perfect.
There are things like minor typos, grammar,
and even some more major flaws like parts where the phrasing should be improved.
I am trying to think ahead about what happens after the paper is accepted.
Assuming that the paper gets accepted,
do we get the chance to make final edits
to correct some of these bugs in the paper
(that do affect readability but do not affect correctness)?
Note
I actually have two published papers to my name,
but in both instances,
after writing the first paper submission together,
my collaborators performed the work of
responding to the reviewers
and getting the paper into the final product,
without involving me in the process.
(I am speculating that this may be because those two papers
were done during my Master's study,
but the paper revision was done when I had moved away to do my PhD.)
While I appreciate that I didn't need to do more work,
unfortunately, this meant that I did not have any experience
with what happens after getting reviews,
and I don't know what is the process to close the loop
and get the paper published.

Generally, you're expected to have done the proofreading and language check before you first submit the manuscript. After acceptance, you're often not given the chance to do any changes to the text, other than fixing typos.

"it sometimes bugs me that the paper is not quite perfect" - I understand what you mean, but I suggest you work on this. No paper is ever perfect. When I re-read my papers from a few years back, I cringe regularly. Don't worry about this, and don't try to make your paper perfect. Make your paper good enough to be useful, and then invest your time in writing a new, better paper.

Is it normal in your country of work (I assume it is not USA or Europe) that you now hold a tenure-track position (your previous question) with only two papers published and not submitting those two papers yourself but someone else doing it for you?

@Alexandros I realized that maybe I didn't need to revise my two papers because those were papers I did during my Master's, and the revisions happened after I had moved away for my PhD. In my field the average PhD student graduates with one accepted paper and two papers that are work-in-progress (either submitted or a working paper), and most newly hired assistant professors are hired right after graduating with their PhD. Unfortunately I was a bit behind, which is why I was not able to have an accepted paper by the time I graduated with my PhD.

Depending on the journal, one of two things may happen after acceptance:

For many journals, once the paper is accepted, that's the last time you touch it: at that point, the journal staff stick it into the production queue and in a few months it appears in a new issue with page numbers and citation information added.
For some "fancier" journals, the production staff does more extensive reformatting to make the paper look pretty and copyediting the text to correct such minor errors and make sure everything is in conformance with all of the journal's preferences for style.  In this case, you will work with the production staff on the final proofs, approving the copyedits they make, and may be able to insert a few minor changes (but generally just wording, not substantive technical changes).

This is further complicated by the fact that some journals now have an "Articles ASAP" or "Just Accepted" publication, which puts a preprint online before copyediting (flaws and poor formatting and all), and only later replaces it with a final version.
Bottom line: unless you know the journal does copyediting and has no "Just Accepted" stage, you should correct all of the flaws you notice now.


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Transforming a private research project repository into an open-source repository
Our research project is ready for being shared as a preprint and submitted for peer review. What are the best practices for transforming the private research repository (which includes several pilot experiments and paths not taken) into a codebase that can be shared as supporting material?
In principle, we can create a new repository with a single cleaned-up version. The downside of this would be a split between the actual research repository and the published one, and the omission of the commit history, which provides specific credit to the different students who contributed to different parts of the code. (to make this clear, these students are also listed as authors.)
EDIT: This question originally mentioned GitHub. I edited it to remove the mention of this service. As some of the comments suggested, there are alternative platforms that can be used for the task. This is a general question on how one should transform a private codebase into something that can be shared as an open scientific code.

have a look at Zenodo.org , instead of being dependent on commercial endeavours that in theory may disappear tomorrow after a market crash.

Might be a better question for support at github (or dedicated forums).  This issue won't be unique to academia.

I am not convinced that commit history is a useful way to give credit.

@Ian I am not underestimating GitHub, if you scratch the fancy layout of that site, they are simply associating with some other institutions to provide storage, institutions that are more stable than a for-profit company.
In fact, one of the best way to preserve your GitHub is to do so through zenodo.org , but I do not see it as "look how nice they are the GitHub guys, they allow to preserve your repository somewhere else for free", rather I see it as "people at GitHub know that they may fold down any moment, so they found a way for free to provide safety to their content provider".

"Do we worry that our Excel spreadsheets will stop working?" yes, in fact while the average Joe employed in a financial company does "finance" with Excel, COBOL is used for critical applications ( http://fingfx.thomsonreuters.com/gfx/rngs/USA-BANKS-COBOL/010040KH18J/ ).
A part from being a theoretical risk, there is the exploitation factor: if a for-profit company is providing you something for free, you are the product. Isn't the peer reviewing provided to for-profit editors enough as a gift from academics to companies?

@EarlGrey Haha, that's a fair point. I'm going to clean up my comments. Cheers.

@EarlGrey Zenodo looks interesting, tho I have to admit I've heard the word before but never knew what it refers to. It seems like you can link your GitHub uploads to a Zenodo item, which is neat. However, unless Zenodo directly supports Git (not the Company GitHub, but Git: free and open source distributed version control system) it is really not suitable for a collaborative maintenance of software projects.

@EarlGrey Additionally, and more importantly, while you make good points about data storage and GitHub, to the best of my knowledge, distributing your code through GitHub is a defacto standard in Computer Science, and certainly Computer Vision. All CV papers from the last few years which have shared their code have done so through GitHub repositories, and everything else would certainly stand out.

@penelope you are mixing up things. Zenodo is (at minimum) the tool to have a permanent storage space for a DOI indexed code. Code that is permanent. Once the record has been published, you can no longer change the files in the record. How you prepared that code, on github-gitlab or using git-svn or your own custom version control it is not relevant.
If GitHub is a defacto standard in your field, I unfortunately can only point at the fact that in the cotton farming industry slavery was the defacto standard. Surely, standing out may bring some question, which also bring visibility.

@EarlGrey I wasn't arguing about whether the standard was good on bad, or that it shouldn't be challenged. Just that it is, in fact, a standard in a well-established academic field, which in my opinion makes this question on-topic (not just as a response to you but also a number of close votes). Sorry for the mix-up. And possibly putting it in the same context to slavery is pushing it a bit. Peer reviewed publications, and comparing academic profiles in terms of citations both standard practices with a number of downsides, but both on-topic on the site (with their downsides discussed often).

@penelope I am not arguing about the topic being on-question (in fact I commented it), but I wanted to make it clear the distinction between github and zenodo. The defacto comparison is unfortunately extreme, and it is the only way to show how the defacto standards are seldom neutral, rarely efficent. I comment similarly when people asks about "notorius-for-profit-ad-placement-company scholar": making any aspect of research dependable on some for-profit private tool (ditto for publishing, ditto for open-source hosted in GitHub ... Copilot® says thanks to all for your free work) is terrible.

What are the best practices for transforming the private research GitHub repository (which includes several pilot experiments and paths not taken) into a codebase that can be shared as supporting material?

For best practices, first determine where you want to host your code. You have two options, each with tradeoffs. Here are the two I could consider:

Make your GitHub repo public and create an immutable tag with the version.

Downsides: You depend upon GitHub being public forever, Some countries block GitHub, GitHub might fall out of favor with researchers.
Upsides: GitHub is the lingua franca for open science right now, having your code public would increase it's visibility, your complete workflow is open source.

Put a snapshot of the code somewhere else either as a supplement with the journal or on a long term digital archive such as Zenodo.org (thanks to EarlGrey for suggesting in a comment).

Downsides: Need to make sure you archived version matches final version, less visible, slightly more work.
Upside: Should be around for a really long time, you get a DOI minted for your code.

Personally, I would combine options 1 and 2. Specifically, if I wanted the code to be public, I would clean up the repo and then make it public. I would create a tag for the final version of code used for the paper and then put an archive on Zenodo.org. I recently did this for a paper I had published in the Journal of Open Source Softwware
Second, make sure your repository is clean.
My agency has guidance for scientists who develop code, some of which would be helpful for you.
The full page is here.
I would also look for domain specific best practices.
For example, the article, Ten Simple Rules for Taking Advantage of Git and GitHub, has been published in PLOS Computational Biology.

Based on my experience working in a simulation-oriented computational science, I'd recommend simply setting the repository to visibility to public.
The crucial steps in making this work are:

Making sure that documentation accompanies the repository on a per-publication basis
Making sure that the state of the codebase used to produce each publication is captured alongside the analytical code and documentation. This includes package versions.
Adding a license

Organizationally -- particularly for projects with multiple papers -- splitting the repository into separate archival branches has been critical. Paper 1 gets a branch, with a readme explaining the layout of the project and the specifics needed to replicate the results. Links to the paper itself and other supporting documentation also belong there along with the versions of the software packages used. Leaving out the packages can destroy replicability.
Paper 2, …, Paper n get the same treatment.
We keep working branches in active development for further work when relevant.
Judging your success:
If you can take a paper, strip out all the tables and figures, and reconstruct it using only that paper’s github branch then you have a foothold (streamlining this can yield great improvements in your analytical workflow for the next project).
You'll know that you hit actual reproducibility when you can send a link to someone who was not on the project and they can do the same.

All good points. Aren't you concerned about including the entire development history of the project in the repository? files that are no longer relevant? analyses not described in the papers?

You can cull or organize files in the archival branches if they are a particularly onerous issue, but as long as the documentation is very clear it should be obvious which parts are actually used in replicating the paper. If they are not mentioned in a procedure, they can simply be ignored by the reader.
IMO these presentation concerns are secondary to simply having code publicly available and in a usable state. Papers and docs are the parts that give the code clarity.
Tidying code is vital, but I would urge you to build that into your workflow rather than as a publication step.

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


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Editor indicated that if minor changes are made, paper could be published: what are the chances of publication?
I am trying to publish a paper. This was the result of a summer's work in my spare time while working 40 hour weeks in a non-math related job. I received an email response from the journal that neither said the paper was rejected or accepted: I have been asked to revise and resubmit. I was given feedback by a reviewer to make some minor changes and the editor used VERY positive language and remarked that if the changes are made then it could be published in the latest issue.
However, at first I took this as great news, since this is my first real work. But, thinking about it more I started to worry that I had gotten my hopes up too soon.
Do I still stand a good chance of it being published?
Edit: Thanks for the answers.

Rather than writing "thanks for the answers", please express your appreciation by up-voting the answers which you found helpful, and accepting the answer you found most helpful.

Yes, if you've only been asked to make minor changes, the paper stands a very good job of being published.
Now you've got to work methodically, and be meticulous with the detail.
Go through each required change one by one. If it's not an unacceptable change, make it; and in a new, separate document - a log of the changes = write one or two sentences to describe how you've made the change (sometimes, a word or two, e.g. "spelling corrected" might be sufficient). If it would be an unacceptable change, write a few sentences in your log of changes about the basis on which you're sure it doesn't need changing.
Work through all these with any co-authors.
When you send the changed paper, add a covering note. In that, copy and paste each of their requests for a change, and after each one, add your sentences from your log of changes about either how you've done the revision, or why you haven't. Your editor may have sent you a proforma or template to fill in, that would do the equivalent job: if they have, use it.

I'm working with my sponsor to address each point that the reviewer made. Nearly all, if not all, of the reviewers comments were valid.

So wait, in the edited copy I need to write one or two sentences in the paper of the changes i've made AND include a cover letter detailing the changes? That makes no sense.

@Pubbie I've edited to clarify. Changes go into the edited copy. Comments on the changes go into a separate new document, a log of changes.

That's what I figured you meant. :)

In the journals that I deal with, even a request for major revisions usually means that a manuscript is on its way to acceptance: it is just a question of whether you are able to put in the time and additional work necessary to address the issues raised by the reviewers.
"Revise and resubmit," by contrast, generally means that the editor sees potential, but that there are too many problems to expect the manuscript to be able to move forward on the tight time schedule of a request for revision. It's a kind of (faint) compliment, actually, and you should take it as it sounds.  I recommend treating a "revise and resubmit" as a request for really major revisions.  If you get a request to revise and resubmit, take the reviewers seriously, and take your time revising until you and your advisor feel you have well addressed all of the issues that they raised.  When you resubmit, your cover letter should explicitly mention the prior version and how you have addressed key issues raised.

Being asked to revise and resubmit is very common and you should not be discouraged by this but rather make the requested revisions and resubmit your paper.

I am a peer reviewer for a journal and have more than 10 publications myself. There is very high chance your paper would be published if you address the reviewers' questions and request. Make your points more explanatory where you do not want to change; sometimes the reviewers are not directly in your field of study and this is done so that a layman can at least understand your paper. Good luck with your publication hustle.


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Are there any positives/negatives in this rejection email ? or, it is just a desk rejection?
I received the following rejection email today :

Dear Prof. XXX,
This message concerns the manuscript
XXXX by XXX
submitted to XXXXX journal.
Informal consultations with possible reviewers have persuaded me that
your article is too specialized for our journal, and therefore I am
sorry to say we cannot accept it for publication.  We have elected not
to review it fully so as not to cause undue delays in its eventual
publication.
I advise you to submit it to a journal more narrowly focused on number
theory, and I do wish you success in publishing it elsewhere.

Now, my question is:
Are there any positives/negatives that can be taken from this email ? or, it is just a desk rejection ?
Note that I received this email 20 days after the submission.

Submit it to a more specialized journal that is pertinant to this article. This journal seems to be more general and accept articles that are of sufficient interest to a more general audience. It says exactly what it says. Submit it to a specialized journal. I am telling it from experience. There are no negatives in this email. Prima facie, positive is their advice to submit to a specialized journal.

Being very specialized is good. So that's good in what they say. Just not good for publication in that journal.

This is the default desk rejection text for journals of the American Math Society. I received the exact same rejection from Transactions of the AMS in the past.

If it was from the Journal of Number Theory then I would be disheartened. Otherwise, we can call it a positive.

If I understand this correctly, your paper has now been rejected at two journals that experienced members of this site called a “top journal in the field.” My advice is to make sure you don’t ask your adviser what great journals you could submit your result to, but which journals they believe you have a realistic shot at publishing it in. Maybe you already did.

@theL yes, you are right, my paper was submitted to proceedings of the American mathematical society.

This is a desk rejection. There's not much more to say about it - I suppose you could say that they haven't outright said your paper is incorrect, which is a positive; on the other hand they did also say that they are not considering your paper and you should submit elsewhere, which is effectively the same as rejection and certainly a negative thing.
There's nothing to do but submit elsewhere.

+1, but I wouldn't claim That is effectively the same as rejection, usually considered the most negative outcome, since your article is too specialized for our journal, which is an out-of-scope desk reject. Perhaps a negative is that you shouldn't have submitted, then again, journals are rarely clear on what they want.

@user2768 I don't understand what you mean. In the event of a rejection, they are not considering the paper and one should submit elsewhere. In the event of a desk rejection,  that's the same result, except accelerated since no reviewers needed to be invited.

@Allure He is saying that being too specialized is much better than being wrong.

@Allure I meant they, I don't know user2768's gender identity.

It hasn’t got any negative implications about the quality of the work. In fact, the paper may even be above the average, it is just not in the scope of that journal.

I see what you guys mean, will edit.

From the letter, it simply seems that you did not submit to the right journal, which can happen to anybody and can be usually known only afterwards. They did not do a classical review process with reports  so nothing can be deduced about the quality of the paper.
The good new is that they replied rather quickly so that you can start the submission in an other journal without having to wait for months.

There is a great positive in this letter: they are telling you that your work is too specialized. Being specialized is good in science and in academia, and, as Thomas Kuhn indicated, is the common tendency in the sciences. You usually need to be specialized in any higher education field. Just look for a more specific journal. They even tell you which kind you should look for.
The negative aspect is obviously that it was desk rejected.

Being "too specialized" here likely means that it's just not that interesting, except to maybe a few people. Not being interesting to a wide audience is not a positive thing.

@glougloubarbaki "Wide audience" is relative, and, I think, not that important. On one extreme, 99% of academic peer-reviewed publications are not interesting to the general public. On the opposite extreme, many of the most prestigious work in science is only understandable by a handful of people.

I mean a wide portion of the journal's intended audience, i.e. in this case researchers in mathematics. A prestigious and non-specialized journal will probably not consider publishing a paper that is only of interest to a very specialized audience, as opposed to a stronger result that is relevant to a wider community. For instance, the resolution of Fermat's conjecture is interesting a much wider audience than number theorists, but there are papers in number theory that are only interesting to a small fraction of all number theorists.

@glougloubarbaki Yes, good point.

I would love to publish on Science, which is not at all a specialized journal

@carlo Another great point.

authors: عبد الرحمن رمزي محمود


text:
Where can I search for researchers in a specific field by location
Where can I search for some authors of publications or researchers in a specific filed (e.g. Computer science) and in a specific country (USA, China, ...)
For example I would like to find all people who work on Data Mining located in Iran

There is no such central database, especially not one that covers all researchers in a given area.

While it's a rather vague mapping, one of the best bets I could imagine is using DBLP (or some queryable port of it, such as Faceted DBLP), query for all publications in as many prolific venues of the field you're interested in, and then filter the linked authors based on their foaf:homepage attribute. This might at least provide you with a somewhat probable estimate of what institution (and thereby, which country) the researcher is (or was?) affiliated with. (Quite unreliable; but maybe just about better than nothing.)

I think your best bet is to find out what the major relevant institutions are, and then use their websites.  But that will be a lot of work.

I suggest that you use a variant of snowball sampling.  Start with the largest, most visible research university in that country (e.g. Iran).  Do a web search for the departments most likely associated with the topic (e.g. data mining). Look at the web pages associated with the most prominent researchers.  You will find listings of their published papers.  In those published papers, you will see co-authors, many from the same university and (importantly) from the same country.  Follow the trail of co-authors and repeat these procedures with their web pages.
In a similar fashion, find conference held in this geography.  It is likely that there will be a high concentration of local participants and conference committee members. They may or may not be important in the grand scheme, but you will find them.
Using this procedure, you should be able to enumerate 90%+ of the people involved in any one specialty in any one (small) geographic region.

Another approach to get a first set of names is to use one of the large bibliographic databases - Scopus or Web of Science will let you search by affiliation/address. Once you have identified a suitable group of papers (eg by keyword/topic searching) you can filter it to only show papers where at least one author had an Iranian affiliation. You'll then be able to work through these pulling out the relevant authors.
Unfortunately, Google Scholar does not let you search by affiliation and so isn't much use here.
(Scopus, for example, has 9500 papers published since 2014 which match a title/keyword/abstract search for 'data mining', but only 146 of these have an Iranian author)

Please provide link to the mentioned sites, especially the web of science

Added. Note that both of these are commercial subscription-only services - you will need to be coming from an institution which has a subscription. Google Scholar is free, but doesn't have the affiliation data.


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“System”, “software”, “application” or “tool” – which to use in my paper?
I am in the field of computer science, I developed some software to solve some problems and would like to write some papers about them. But I don’t know what to call the software in each of my works.
For example I developed software to extract structured data from web pages, (I called it system). In another project I developed software for foreign language learning (I called it software tool, however I may rather to call it system again).
In general, what is the difference between software and system?
When I should use the terms application or tool?

I'm voting to close this question as off-topic because it is about computing jargon, not academia

I think this could stay open since it asks a question I interpret to be about academic publication/presentation.

@EnergyNumbers thousands of publications include these terms, for example system, then it is not just about computing, other fields also may develop software for their works

In your first sentence, you write "I developed some software...", so I think you've answered your own question.

@JeffE thank you but any other word I had used, you would say the same

@Ahmad That's correct.  The first word that occurs to you to use is usually the right one.

System = not necessarily a "software", "application" or "tool". In its broadest sense, a systematic approach to solving a problem. Software = a configuration of hardware amenable to being programmed. Application = a system that is not solely of theoretical interest. Tool = a system that is mainly useful for creating other useful things rather than a system that achieves an appreciable goal of itself.

In academic writing, it is good to be precise, clear, and consistent in your use of terms and their definitions.  Unfortunately, not everyone in Computer Science follows this practice when it comes to terms like "system", "application", "software", and "tool". Following the practices of other people may lead you to follow their ambiguous or loose usage.

One useful way of thinking about each of these terms is to define them in terms of their opposite, or what distinctions they are drawing.
For example, a "system" is a set of interrelated components (modules, subsystems, etc.) that work together to form some cohesive whole, especially when the performance or functions of the whole is more than the sum of the parts.  In contrast, a "non-system" is a collection of components (parts, modules, subsystems) that do not cohere as a whole and have no significant interrelatedness.  (Look up "General Systems Theory" for more on this distinction.)
"Software" as a term is most meaningful when you use it to distinguish from "hardware" or even non-automated information processing by humans.  However, it is also generic, like "program", and so it can refer to any code that runs on digital computer.
An "application" is software that is not part of the operating system, and not part of the utilities that go with the operation system (e.g. database, compiler, networking utilities.)  By implication, "application software" is what end users use to get value from computers, as opposed to "system software" which is what computer specialists use to create/support application software.  (This terminology arose in business computing in the 1960s, and continued through the early 2000s).
A "tool" is software that doesn't provide end-user value on it's own.  It generally needs a "tool user", usually a skilled human but could be another software program in special circumstances.  A "tool" performs a set of functions that are generally useful and not tied to any particular circumstance, problem, or approach.  Tools are often are designed with general use in mind (e.g. easy interchange with other programs using standard interfaces and data formats).  In contrast, software that is not a "tool" has features, functions, and interfaces that constrain it to a particular need, context, or purpose, and it is these specifics that make it valuable.  For example, Microsoft Excel is a "tool" for math, but a sales commission calculator within a CRM system is generally not considered a "tool" even though it may perform spreadsheet-like math, because it has many specific features and functions unique to sales commissions at a particular company.
Finally, in academic papers in Computer Science, it is often the case that what is most important is not the particular implementation of software, but instead it is the algorithm or maybe the software architecture that is most important.  If so, then you should use those terms rather than the more generic "software" or "system".

In your examples, I would call "software to extract structured data from web pages" a tool, because the end-value is the structured data that some researcher will use for some purpose.  Your software is a tool for getting structured data from a wide range of web sites, and would suit a wide range of research purposes.
I would call your second example, "software for foreign language learning", a system if it includes all the functionality and usability features needed for an end user (however you define it) to use the software for some language learning purpose.  (I assume you mean "...to help people learn a foreign language" rather than "machine translation between natural languages".)  However, if your software is not a complete system from the viewpoint of some end user, and instead you want to focus on the algorithms that the software implements, then I'd call it an algorithm.  There may be other possibilities, but I would need to know more specifics about the software and its use, and your purposes in publication.

Thank you for your complete answer, my second software is focused on teaching "Spelling" and maybe "Listening" too. I can call it "a software tool for improving spelling and listening" or "A Spelling test and Tutoring System"?

@Ahmad - if the user of the software is seeking to be tutored, or is providing tutoring services, then "a tutoring system for foreign language spelling" is the best label I can think of.  "Tutoring" implies that the end-user has little expertise of their own in the subject and method and needs to be led through the process. I presume your software includes UI for end users, plus features such as saving previous scores/results, printing reports of results, etc.

Yes almost, maybe now it is in initial versions, but the ultimate goal of the software would be providing tests and reports of errors and adjusting the tests... then I go with "System"

Following the practices of other people may lead you to follow their ambiguous or loose usage. — As it should. The precise term doesn't matter to your audience, so it shouldn't matter to you, either.  For all practical purposes, the words are synonyms.  Your readers are going to pay far more attention what your software/system/application/tool/library/protocol/framework/implementation/widget/doohickey does than which specific word you use to describe it.

Software, system, framework, application, and tool, along with several other words are often used to describe computer programs that accomplish a task. Application tends to be used when it is a standalone program that accomplishes the task, whereas library is more used when the code in question is intended to be used directly by other programs through an API of some sort. Frameworks often incorporate multiple libraries and/or applications to accomplish a broader set of goals. Tools tend to be smaller programs that are sharply focused on particular tasks, though through scope creep they often lose this focus over time. System frequently implies a much larger whole and is often used to speak of hardware/software systems (like a whole computer) as well as software alone.
These words have specific meaning in some contexts, but are often used somewhat interchangeably as well. It would be best to have a native English speaker in your field look over a few sentences that use your preferred words to make sure that they are consistent with your field's use of the terms. You may also compare to similar works, especially those you reference and those in journals or conferences where you'd like to publish, to get a feel for what the norms are.

Thank you, but I think many publication in various fields use the term system while it is not about hardware, in academia hardware is less discussed. For example a learning system, teaching system, ( I mean electronic not physical). I still didn't get the general meaning and proper use of system in publications.

By interchangeable you mean that in a single article I can use for example both "application" and "tool" or "software" and "system"?

@Ahmad, I think you can switch back and forth sometimes, but I would endeavor to be consistent. I wouldn't mix application and library, for example, but application and tool are probably OK to mix. Software and system may or may not be mixable depending on context, so I'd have to read some paragraphs to be sure.

in academia hardware is less discussed — This is simply false.  Walk across the street to the EE building.

@Ahmad I must agree with JeffE. How do you have computer software without hardware?

@scaaahu maybe I can say in computer science (or in theoretical sciences) the software and algorithms are more focused.


text:
How to ignite your research career when your advisor is so disappointing?
How can I ignite my research career when my advisor is so disappointing and I can learn nothing from him?
He rarely publishes academic papers, but he has his fingers in many pies(engineering projects) and has no time to give any suggestions and directions for my MS project. I think nothing can be learnt from him. How can I startup my own research career under such a condition?

Given that the obvious first answer is "change your advisor", please can you tell us, having considered that, what the situation is, and the opportunities are, with regard to doing it?

...He rarely publish academic papers. Then why you chose him? Also "...He has his hands on many pies (engineering projects)" and "nothing can be learnt from him" are contradictory, since for him to be involved in many projects (even if it is not research) shows that he is good at what he does.

Side comment: I think it should be "has his fingers in many pies."

As mentioned in the comments, if you are not happy with your advisor, find a new one.
I think there are some misconceptions underlying this question.  Typically graduate students write papers, not faculty members.  Publishing is up to you, not your advisor.  Faculty are typically not trained as managers.  Therefore it is up to you to give yourself direction.  I think you should consider these features important in an advisor:

Can obtain funding you need to complete your research.
Can add to your reputation and connection to other researchers.
Knowledge of the discipline (less important because it's easier to get this elsewhere)

From a faculty member's perspective, the best way to achieve all of these things is to be involved in as many projects as possible.

Among all the three points you mentioned, only the last one does he have. And the "projects" are commercial projects for money, far from the research projects in your sense. After all, thank you for your sincere comments!


text:
PhD supervisor hesitating to give postdoc recommendation for issues with the host country
I was applying for postdoctoral position in a reputed lab in a foreign country and they have asked for recommendation from my PhD supervisor. Although my PhD supervisor has given an informal recommendation by email, he has not given formal recommendation yet.
When I asked, he said that our country has some diplomatic problems with the host country (nothing serious  in reality), so he cannot give a formal recommendation unless he knows the exact potential job description in that country.
Now, if I have to ask the host lab, I cannot tell all these 'diplomatic' stuff (which I also believe is pointless and my supervisor is just being paranoid). So, is it good if I just ask them the exact project I would be working on and tell them that my PhD supervisor will only give recommendations after getting such information?

Actually, I think you need to see an "exact potential job description" before you even consider a job. If the employer is unwilling to give that then there are all sorts of red flags, especially for foreign nationals. I suggest you ask for a complete description and see no reason why you shouldn't share it with your advisor.
Perhaps they are being paranoid, but perhaps they are trying to either protect you or to write the most appropriate letter that they can. Such knowledge is useful to both you and your advisor.

Thank you for your suggestion. But I am worried that I can't simply ask an esteemed professor something like "please give  me an exact job/ project description now, or my PhD supervisor will not give recommendation letter"- It might show that I am somehow   suspecting them. And also  as my PhD supervisor only told me these things on phone-there is no proof that he even asked for such thing! So the entire burden would be on me.So,what to do now?

You don't need to mention your supervisor at all. Just ask for a complete job description to help you decide on your future. It is your right to know that before you take any job. An honorable person would be glad to oblige. There should be no negative implications at all.

Thank you  for your suggestion

@Buffy: "An honorable person would be glad to oblige" - I know many honorable profs who are chaotic and would probably just reply "well, anything a postdoc is supposed to do";)

@user111388 than you know. Knowing that your potential supervisor is not the most organized person in the world is important information too...

@MaartenBuis: In the case of the people I think about, I would absolutely recommend to do a postdoc with them even if they are not the most organized person. So I don't think the information they are not the most organized person is going to tell you much;)

You will likely need this formal job description anyway for a visa. Any university should be able to provide you with this.

Here's my general approach to dealing with these sorts of situations:
You are interacting with two people whose intentions you do not fully understand and with whom you apparently don't feel at ease just being honest with. (For example, you don't want to tell the host lab person about the 'diplomatic' stuff.) Let them figure it out themselves in an email to everyone:

Dear Lab Head and Host Person,
I asked Lab Head about a letter of recommendation, and he suggested first seeing a complete job description in order to tailor his letter to the purpose. @LabHead: Is this what you were asking for? @HostPerson: Would you be so kind to provide what LabHead is looking for?
Sincerely
Possible future postdoc

My reading from your post is that you are confused what everyone wants and why. But these people know, and they've got experience with how these things work. Let them sort it out!


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How exactly does a conference abstract differ from an article abstract?
I am currently taking a brief course in Technical/Academic Writing. At one point, in passing, the lecturer (who's a researcher in linguistics himself) mentioned that one should not confuse a conference abstract with an article abstract, with the exact phrasing "... that's a whole different story."
Unfortunately, at that moment in time I did not reflect on what those differences might be, but now I am writing a conference abstract I realize that I have never really paid much attention to the fact that I am not writing to a journal. Besides the fact that a conference abstract is preamble to a primarily spoken form presentation (poster/oral) instead of a written one, I don't really see why it would be "a whole different story".
Assuming that there are no differences in requirements and limitations, what are the fundamental differences, between a conference abstract and an article abstract, that one should be aware of?
PS: if it matters, the field I'm mostly concerned about is medical research

To me an article abstract summarizes the entire article including the overarching questions through methods, results to the major conclusions.
A conference abstract will of course also summarize whatever is presented at the conference. The differences lie in several aspects of variable weight:

Conferences are often focused on a specific topic so one can be less stringent with the background
Conference presentations may involve work in progress and as such the final conclusions maybe quite hazy.
The conference abstract may be written before most of the work has actually been done (this is quite common with some conferences in my field) and becomes an "advertisement" for what might come.
The conference contribution may in some cases involve a paper but can also be a poster or an oral presentation. depending on which abstracts may contain varying levels of finalized conclusions.

I think your professor was talking about extended abstracts (see this question for more discussion). For many conferences, especially those that don't publish their proceedings, people submit an extended abstract instead of a paper. Thus, in that case the 'abstract' is basically a short paper that summarizes results you are working on or planning to publish soon. It is much more detailed that an abstract for a paper, but less detailed than a whole paper would be.
If your conference publishes its proceedings though (as many in computer science, do) then you should treat your conference submission like a journal one and write the abstract accordingly.


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How to politely ask for recommendation letters to professors
I am applying to a few different masters' programs this fall after having applied to a different program last year. In the end, I decided not to pursue that option due to financial reasons. I graduated from my university in May 2014, and I have visited many of my professors during their office hours while I was a student there. Of course, I only made recommendation letter requests to professors in courses that I did well in. Last year, when I was applying to another program, it was relatively easy to obtain recommendation letters from the professors I made requests to. However, this year is different. I explained my change of direction to the professors who wrote my recommendation letters last year. Except for one professor, the other professors don't even bother responding to my emails. In cases when I am requesting recommendation letters after graduation, do I have visit professors directly and have a conversation with them? If that is the case, I am unable to do that because I am currently outside of the US. Also, am I expected to give them a gift at the time I am making such request? I want to know what I may be doing incorrectly.

am I expected to give them a gift at the time I am making such request? No, absolutely not. It's their job to write the recommendation letters for you.

@scaaahu - moreover, a gift could be construed as a bribe of sorts. I know I'd feel very uncomfortable accepting a gift in conjunction with a request to write a recommendation letter. A simple thank-you is quite sufficient.

Definitely do not send gifts! That is wildly inappropriate.
tl; dr - Send them a gentle reminder.
When I was in undergrad, I intended to go to medical school. I took the MCAT, applied (with letters of recommendation), got interviews and then I had a change of heart. I had a realization that I never wanted to tell a parent that their child had died (e.g. in a car accident / overdose / aneurysm / etc). It was just too heavy for my 22 year old self. Instead, I entered the workforce as a software engineer. I liked parts of the job and learned a lot, but I wanted to ask my own questions and pursue my own interests. After some thought I decided to apply for PhD programs in neuroscience.
When I recontacted one of my important letter writers to ask for a new and different letter, he questioned my commitment to the PhD, remarking that I had had a change of heart before. I was pretty surprised and a bit hurt, but I responded thoughtfully to him, explaining the process that I went through, and that I was sure this time. He ended up apologizing to me (!) for forgetting what it was like to be a 22 year old. He not only wrote me a great letter, but personally called my future PhD advisor to put in a good word for me. We remain friends to this day.
In summary, young people are still finding themselves. Many successful academics change direction in their careers. Many great computational neuroscientists were physics or math PhDs that reinvented themselves.
So, send them a gentle reminder. Include a short explanation of your change of mind and why you are sure you are committed to this new path.

I don't think you're doing anything incorrectly.  Sometimes people get busy, sometimes people are thoughtless and inconsiderate.  I'm afraid you're going to have to use a combination of persistence and politeness.  The tricky thing with the politeness is that you don't want to lay it on too thick -- as that in itself can get annoying.
Please consider using a combination of email and phone.
If things are still going badly after about two weeks, then I think it's time to contact a department secretary, dean, assistant chair or assistant chair.
I can see that in some departments it might be easier to pester someone by knocking on their door, but that really shouldn't be necessary; and you can use the department administration to accomplish the same thing.
(As mentioned in a comment -- please, no gifts.  It's not the custom in the U.S. and therefore would be too weird.)


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What questions can I ask the search committee for math tenure-track interviews?
I am in the job market this year for tenure-track positions in math. I have a Zoom interview coming up for a 4-year college position. What questions can I ask to the search committee?

The questions period in a job interview is often used by people to show their genuine interest in the position and the institution, but please try to avoid brown-nosing and only ask things that are genuinely of interest to you.  There is an expectation that you will already have read the institution/department website/reports so you should already have a strong command of information in these materials and only ask about things that go beyond this information.  Here are some potential questions that might (or might not) be of interest to you:

Can you tell me a little about the culture of your department?

How collegial have you tended to find the allocation of teaching responsibilities in your department?

For an academic coming in at my level, what kind of service appointments would be typical in the department?  Do you have any particular committees/positions in mind for the appointed candidate?

Does your department have any emerging research interests on the horizon that are not reflected in your existing research reports?

In your experience, what are the main things that have determined the success or failure of your other tenure-track academics in gaining tenure?

These are just some examples of things that might affect your work enjoyment at a new institution, and which are things that are hard to determine from reading reports from the institution.  There are many other things that might be of interest but hopefully this gives you a flavour of the kinds of questions you might fruitfully ask.


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Should a research presentation make use of suspense to engage the audience?
Suspense is a powerful tool. In story-telling, not knowing what is going to happen or how the story is going to end can grab attention and sustain interest. In giving a research presentation, one is often encouraged to "tell a story". One could certainly make use of suspense to do so.

We are interested in how best to predict X. Previous research has indicated that P Q and R could be crucial here. [much later] It turned out that... [pause for drama]... variable K was surprisingly the strongest predictor of X!

However, most presentations take a more up-front approach.

Welcome to my presentation entitled "How K can be used to predict X"...

The latter approach follows the advice that I have often received, which can be summarised by the maxim:

Tell them what you are going to tell them, then tell them, then tell them what you have told them.

So, is it a bad idea to use suspense with the intention of making the "story" of your presentation more engaging?
[This question was inspired by an answer given elsewhere on Academia.SE.]

I think it's highly dependent on the presenter's skill level. Suspense... is just like clothes... sometimes you are excited to see them being taken off, sometimes you wonder why they are even on, and sometimes you just wish they were still on.

Another effective alternative is quizzing the audience: "So, which predictor do you think is the strongest? Any guesses?"

It depends also a lot on the venue: if you are going to give a talk in a conference where you have just 15 min to talk, it might not be easy to add the suspense in the right way.

I think, we all do similar kind of suspense to highlight the proposed scheme or approach compared to previous related work. This 'suspense' is highly related to the background knowledge. The presenter must mention the specific topic to narrow down audience number if the talk is not very general.

Should you do this, please adhere to the rules of writing detective fiction, in particular, "The criminal must be someone mentioned in the early part of the story". Introduce variable K before outing her as the strongest predictor.

I think if you need to ask this, the answer is No. Maybe as your career unfolds things will become clearer.

I believe that using suspense in a talk is a terrible idea on any but the shortest rhetorical time scales.
The reason is that, at any given time, a significant fraction of your audience will not be paying attention.  It doesn't matter whether they're twiddling with their phone or just thinking about what you said two slides ago: the point is, it's terribly easy for people to miss bits of a talk.  As a result, if you build your talk as a suspenseful mystery where somebody has to be paying attention at the right times, then you'll probably fail to convey key information to a significant fraction of your audience.
Now, there's nothing wrong with using it in the short range as a bit of rhetorical flourish, e.g., "And what did we find? The wires were covered with purple spots!"  Once you start putting long-range dependencies in your talk, however, you're gambling with attention.  Likewise, even without putting in a dependency, if you say your key idea only once in your talk, you're decreasing the number of people who will hear and remember it, compared to if you say it in "preview" and again when you get to it in detail.
In short: don't hide information from your audience.  There's plenty of other, more effective ways to make a scientific presentation interesting.

To add to your last point, there are plenty of other, involuntary ways to instill confusion in your audience.

Have you ever read a badly written book or short story, where the author had a fine idea, but just didn't manage to pull it off?
You'll just have to try this out and see if you can pull it off.
Note, when I say "try it out", I mean on your friends.  Practice talks.

I predict that this will be a growing trend.  Cooking magazines and DIY magazines now often use a story-telling format.  Instead of just plunking down on the page the recipe for roasting a chicken that was found to give the best results in the testing labs, nowadays the author tells a story -- and it's a personal story, told in the first person.  It's a journey of discovery... to arrive at the best recipe for roasting chicken!  It sounds funny, but actually you do get drawn in.
Also, consider the new field of creative nonfiction.  Wikipedia defines it: "Creative nonfiction (also known as literary nonfiction or narrative nonfiction) is a genre of writing that uses literary styles and techniques to create factually accurate narratives."
You can laugh at this too, and see it as part of the general shift toward egocentrism, where the researcher-author has to be at the center of everything.  The author can't just expound about the material, making it interesting and understandable.  Nooo, he has to make everything about himself!
But if you've read any good creative nonfiction, you'll see that when the author can pull it off, it's wonderful.

Jake was concerned about a distracted member of the audience missing a key bit and therefore being confused for the whole rest of the talk.  That can easily happen in a traditional talk structure as well.
Hopefully, if you are a researcher who is interested in experimenting with more novel structures, you are also someone who knows how to use, or can learn how to use, techniques performers in the fine arts have learned, of getting the audience's attention before the critical point that must not be missed.  For example, a small joke to wake everybody up.  Sometimes reducing your volume at a certain place can have a mesmerizing effect.  Etc.

Personally I think the key to not overdoing the novel stuff is to make sure that it doesn't detract from the science.  The takeaway message needs to be "the science that was presented is fascinating", not "the scientist put on a great performance".  In other words, the science needs to take center stage, as opposed to you taking center stage.

+1 for "takeaway message needs to be the science presented is fascinating".

I would back up what @aparente001 said above.
Basic human psychology is geared towards engaging with stories, and this is no different from the humans who will be listening to your talk. If you want them to remember your presentation, you must include aspects of storytelling, but suspense is one of them. Simply giving them the facts defeats the point of giving a talk.

Note that there are a lot of factors leading hiding recipes, in particular, at the end of a long essay:  recipes cannot be copyrighted (so the narrative becomes "protectable" creative work), ad revenue is often driven by the number of ads you can insert (which depends on length), increasing readership can be driven by the creation of parasocial relationships through personal narrative (which further drives ad revenue), and so on.  A recipe blog is a very different beast from a presentation at an academic conference.

I think that building up suspense is acceptable as long as it accompanies clear progress in the topic to be presented.
The "milestones" could be key ideas that led to the solution. If the ideas were the outcome of some effort, then a little more time can be spent on them; if the ideas were however to try various known things of which some happened to prove useful for the problem, then they should just be mentioned without going into details.
Negative examples of building up "suspense" can be found in some contributions to certain platforms whose mission is to "make a story" out of simple things, mostly starting with a big image to catch attention and then dwelling on trivia like "a point is..."


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How to organize a session at a conference?
I was recently asked by the cluster chair
to organize a session at a conference on topic X.
How does one go about organizing a conference session?

I imagine that depends a lot on the conference.

It also depends strongly on the academic discipline.

In my field, applied mathematics, this would mean find 4-8 people who are willing to participate in the conference and give a talk in your session. Small print: they are going to have to pay their own conference fee, and we do not reimburse any expense to them or give financial support of any kind.
Typically you find these people by asking them in person or sending them an e-mail. Do not overbook, as people accept more often than not, if it is a good conference.
This is how most conference sessions are organized -- if the conference itself is respectable, there is nothing suspicious about it.