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What to do when people in a research group use different programming languages for computation (e.g., Mathematica, Python, Matlab)?
I am a very happy user (in 98% of the time) of Python/Numpy/Scipy (anaconda distribution). I switched from Matlab and do not regret the decision. I have reached a level of expertise, which enables me to help others with their computational tasks and encourage people to use Python.
Unfortunately, the situation is not that easy. A senior researcher in a very closely related working group is using Mathematica. One of his students is using Mathematica, one is not sure yet but honestly it would be stupid to use a different software.
If I switch to Mathematica, everyone may benefit from it (code sharing and building up knowledge). I think you can understand that my motivation to do so is not the highest (not again another language; I use Python, Fortran and a bit C++). Additionally, the Python user community is very vibrant, and they frequently come up with interesting projects.
In order to avoid a nonsense discussion about what software to use, let me rephrase my questions as follows:
Have you ever been in a similar situation (either as student or supervisor)? And if you have, did you try to get everyone to use the same language? Did any situation occur where it was good that not everyone was using the same tool?
EDIT:
My field is biotechnology. We do calculate: ODE'S, PDE'S,fractals, system of equations (ODE's, DAE'S, algabraic). Most of the time we do some rapid prototyping (e.g calculating linear pH gradients in chromatography, some combinations of reactors etc., using/extending chromatographic models). I am a PhD student and will continue as a post doc at the same institute including occasional lab exchanges abroad.

Another avenue is to try to make everything modular, so that, for example, a high-level Python script calls more dedicated Python/Mathematica/etc. functions.  This can be done directly in a programming language, or you can try to use something sort of workflow management tool (one that I have tried minimally is called Kepler, but it doesn't have Mathematica as a native language).

Why not just learn Mathematica? I haven't had this issue, because I'm the only one writing code for my projects, but I try to write different projects in different languages - it is, in my opinion, the easiest way to pick up a new language. I guess I don't see why you have to 'switch' rather than just pick up a new language. It (presumably) isn't like you are going to forget Python while working with Mathematica.

If you do want to make your case for why Python is better though then you could focus on it being open source and having a very active community. I've run into licensing issues trying to use MATLAB on national HPC systems (I think it is harder/more expensive to license software that can be used by researchers from multiple institutions). One reason I learned R and Python (I also started with MATLAB) is that I might not have access to expensive licensed software in the future.

We decided to get around the issue by learning how to write our shared data analysis routines in C, then wrap them in Fortran, then use SWIG to wrap them into Python, Tcl, etc so everybody could use them from whatever language they wanted. And we knew we would all get the same answers because they all used the same underlying C library.

I think it worth to remark what field you are in: CS? Physics? Different fields have different cultures and level of "reasonable programming skill" also very different. In this particular situation, I also would remark that Python/scipy and Mathematica are very-very different animals, and if one is a good tool for a given problem, the other most probably not. I.e. you can have very good reasons to use both, depending on the problem. Mathematica is a far better symbolic calculator, and scipy is far better number cruncher.

This is an honest comment, not trying to make a point: I don't really understand what is the problem. I use Mathematica as my main tool while most of my colleagues use other software. It has never really been a problem. The tasks I use Mathematica for usually require working interactively, and there is little code sharing going on. It's very different from collaborating on an application. I don't write "applications", I just process data, create figures, automate running my C++ simulations, etc.  Is your situation different? Also, why not learn both tools?

@Szabolcs Considering the following scenario: "Hey, the model I'm running is producing some really weird convergence errors, can you come be an extra set of eyes?" or "Man, that analysis you did was perfect for my project, how did you do it?" Code sharing and collaboration go beyond writing an application.

Following up on @dang 's point, if there are "natural" places in your workflow to test or checkpoint-to-file or preferably both!, they should be good places to let anyone change languages (and if you make the file formats and assumptions explicit to enable this, well, needed to be done anyway).

This is very familiar to me - people come into my field from a number of different places, and each has not only their own preferred software, but the software they think "everyone" uses - which invariably isn't true.
At the moment for example, I have implementations of various bits of my work in MATLAB, Mathematica, C++, Python, Maple, R, SAS...

Have you been in a similar Situation (either as Student or Supervisor) ?

I've been in groups that successfully united everyone under the same language banner, and some groups that did not (intentionally or otherwise).

And if so, did you tried to get everyone using the same language ?

I have definitely tried, and occasionally failed. You've mentioned some of the benefits, but beyond merely code sharing, everyone using different languages makes it extremely hard to learn from others, share solutions, or collaborate really in any way. If you have a problem, and it's written in another language than what other folks are using, that problem is entirely your own to deal with - even if folks want to help, they may not be able to.

Did situations occur, at which it was good that not everyone is using the same tool ?

The only time is when the "usual tool" is somehow terrible at what's needed for someone's work. For example, a few years ago, when Python's statistics ecosystem was much worse, it was good to have people who knew R. But assuming they can all achieve roughly the same thing, I've never gone "Oh thank god we're all writing in different languages!"
The one exception is I did encounter someone whose ability to parse whitespace-based code is...less than stellar, which made me glad I could run things in MATLAB as well as Python.

What was your experience with those groups that sucessfully united everyone under the same language banner ?

@Moritz From the perspective of collaboration? Better, vastly, but not perfect (different coding styles, etc. still make things hard).

In theory, writing in different languages is good because you can write two versions of the really important stuff, run them on the same test data, and have a better chance of finding subtle bugs. In practice, who takes the time?

@cphlewis I did exactly that.

Including finding subtle bugs, @TheBlackCat? I am delighted.

@cphlewis Subtle bugs and not-so-subtle ones, I am afraid.  Unit testing is a great thing.

The one group I've been in that managed some of this had, uh, probably personal rivalry as well as different language preferences, and I couldn't get everyone to agree on sharing test cases. (Test harnesses: to get all the programmers pulling in the same direction.)

The only restrictions that I place on my group members when it comes to the software that they use in their research work are:

that they not use proprietary software for which the group doesn't own a license
that their work can be shared or reused by other members of the group in the future

Requiring strict use of one set of tools is, I think, counterproductive, as it can force people to spend a lot of time learning things that won't necessarily be helpful to them in their research or later in their careers.
If they're just getting started on the programming side of things, however, I'll ask that they start with Python and the other standard codes that we use, because it makes life simpler for everybody in the long run.

A piece of wisdom my supervisor shared with me a few months back,
when I told him about how cool Julia seemed.
Was (paraphrasing):

We (often) aren't really in a position to choice our language for the
  task. We use what ever the best tools are being developed in. Before
  that was C++, then it was Matlab, now it seems to be python. Maybe by
  the time your PhD is done we will all be using Julia.

Point being, that learning a language is easy.
You just do it, so you can use the best libraries.

One of the things I am loving about Julia is that because of its Foreign Language interface, you can call libraries written is many different languages.
(I am aware of working code to call: C, Fortran, Rust, Python, Java, Matlab, Mathematica, and C++).
Thus having maintained access to the "Best tools"
This is not to say you should convert everyone to julia.
The first point stands.
Learning a language is easy.
Getting the best tools (or in your case perhaps collaborators), is not.

That depends on the language.  Learning some languages are easier than learning others, and some languages teach you skills that are more generalizable than others.  And lots of languages have foreign function interfaces.

FFI generally refers to being able to interface with C. But indeed it is getting more and more common for wider interfacing, because it is a great idea.
I would be interested to see a answer to this question that recommends using FFI.

Yes I have been in a similar situation both as a student and as a supervisor.
As a student I was the only person in my lab to use Python (others were using Matlab or even Excel macros). Yes I tried to convince them to switch, with little success! But that was not a major problem because I did all the programming work on my own for my projects. I occasionally helped on other projects using whatever the main researcher on the project was using.
As a supervisor this was little bit more complicated, because my student was requiring a lot of micro-management and help on simple programming tasks in a language that I never used. He chose this language because he wanted to extend a program written by another research group. This was very frustrating for both of us, and I was hard for me to decide when to spend time figuring out simple things and when to tell him to RTFM!
In the future I would warn the student before starting the project: we agree that either he manages simple programming problems on its own, or he uses a language that I know well.

In my case, I'm using a mixture of R, C++ and Python whereas the rest of my lab uses Matlab. And it's going pretty fine, though I have to admit we don't need to share lots of code. Some observations:

Having implementations in two languages that are supposed to work the same way helps finding bugs in the code.
I can quickly evaluate new tools in R which weren't implemented in Matlab. Others can do the same with Matlab code that doesn't yet have an implementation in R. This already proved useful, as R is much easier to use in machine learning algorithms, and Matlab has a great library for polynomial interpolation.
If you plan for interoperability early, it's not that hard. We decided on a single file format for raw data that's parseable by all our tools, and in case we needed to make scripts in both languages to interoperate, we can do so too (so far it wasn't necessary). However I admit that having skills in polyglot programming is somewhat necessary for that to happen.

Key advice in this answer: Plan for interoperability early!! Golden.

On second thought, having a back-to-back comparison like bullet point #1 is good too.

Have you been in a similar Situation (either as Student or Supervisor) ?

Yes, frequently - in my current department, people use (depending both on their personal preference and on external requirements) Java, C#, C++, C, JavaScript, Flash, and probably a few more.
It even varies a lot, as students may want to use yet another technology or language for their projects such as Bachelor or Master theses.

And if so, did you tried to get everyone using the same language ?

Never, unless interoperability was an explicit requirement. It may have to do with the fact that I'm in a CS field (i.e. where programming is more at the "core" than a mere tool), but there is what could be called an unwritten rule that you do not prescribe others what technologies they use. At best, it could be interpreted as an immature attempt of starting a flame-war on a "nerdy" topic, at worst, as a violation of other researchers'/developers' personal autonomy by micro-management.
Concerning the aforementioned students, we do make it clear that we cannot provide any technical support if they choose a technology that none of us has any experience with (though it should be noted that we won't provide too much support, anyway, given that Bachelor and Master theses are supposed to focus on the conceptual and methodical aspects in my place, and students are supposed to (show that they are able to) deal with low-level problems while programming their prototypical proof-of-concept on their own.)

Did situations occur, at which it was good that not everyone is using the same tool ?

To avoid making this sound overly one-sided or negative, I'm going to list perceived advantages and disadvantages here:
Disadvantages:

Artifacts by different persons won't necessarily work together.

This has even led to complete reimplementations of prototypes, just so a widget by one person could be used in the application by another person who used a different framework and/or UI toolkit.

Maintenance of existing code-base is not a given. Once a colleague leaves, their code might not be touched again on the single reason that no-one is acquainted with the technology used for that particular code.

Advantages:

There is no way to guarantee using just one language, anyway; there are just too many external factors for this. It can more or less be taken for granted that as soon as one has succeeded at bringing the whole department to one single programming language, the next project with external partners will end up in the consortium choosing a different language for one reason or another. Having a diverse department where know-how on different technologies and languages is present, on the other hand, can help when working on such a project.
As extensively described in Chris White's answer, different programming languages are often suitable for different goals, so depending on what you are doing, a switch of languages might be required.
Seeing permanent change and diversity makes it less likely to "get stuck" with one technology. Creating a growing collection of reusable code is certainly advantageous, but if that results in the use of outdated technologies because "everything so far has been written in the 1982 dialect of a proprietary language that is not updated any more" and the expectation is that a switch would require porting the entire codebase, this does not exactly increase the research output. As research departments usually do not have to produce production-level foolproof code, but just prototypes and demonstrations of concepts, absolute stability should be a lesser concern, and thus, constant "quick-and-dirty" rewrites of some components are acceptable.

EDIT: Every time I re-read this answer of mine, the developer in myself shudders in horror. Thus, let me clarify my view on the advantages: Yes, maintaining, updating and extending an existing code-base over long periods of time is great. In my opinion, an ideal mix is for small groups of people within one department to share a particular technology and thus have an option of exchanging some code (being the only one bound to a given system can be dire), while at the same time making sure there is some slow, gradual flow in which technologies get phased out and replaced over time with new ones.

Besides working out a way to use multiple programming languages (e.g. through foreign function interfaces / compiling stuff in libraries / creating scripts which can be called by other languages) I think you could eventually agree on one programming language.
I recently participated in a hackathon. We were three programmers and had a task to solve. We "filtered" the programming languages like this:

Which languages do we know which are similar appropriate for the task (in terms of ease-to-use / libraries / community stuff like tutorials / learning curve)
How well do the team members know "their" language? (It is better to have one person who is an expert in a language than two who know a little bit, because that way you can ask the expert any question.)

(The hackathon was a success and I learned a new programming language and a framework in another programming language.)

Have you ever been in a similar situation (either as student or supervisor)?

Yes, twice.  In my previous group, everyone used MATLAB, but I had to learn Python because MATLAB's multiprocessing was prohibitively expensive.  After learning Python, I preferred it and stuck to it.  In my current group, everyone besides me uses MATLAB.
For my own personal data analysis code, I use Python, but for code meant to be shared across the group, I use MATLAB.
If you have a programming background, you would think that this would lead to less shared code for data analysis.  The problem is that nobody else in the group has a programming background, and they neither know nor care about good programming practices (I haven't even had any luck convincing them to use functions rather than copying and pasting code blocks within their tens of thousands of lines scripts, not to mention adding comments).  That means there is almost no code sharing even amongst MATLAB users, and everyone just ends up writing their own data analysis code from scratch.  So due to the culture of the lab, nobody would even have realize I used Python if I hadn't told them.
So how big of an affect your choice of language has depends to a large degree on the culture of the lab, or perhaps more properly on how familiar they are with programming.

And if you have, did you tried to get everyone to use the same language?

No.  I have suggested that people learn Python in addition to MATLAB, without much success.  But people who have asked me what they should learn, I have suggested learn MATLAB first, simply because they can be sure to find someone who has at least used it before.  I am the only one with a real programming background, and there is a ton of legacy MATLAB code, so it just isn't feasible to switch at this point.  That is why I always suggest people learn Python as a second language.

Did any situation occur where it was good that not everyone is using the same tool?

Yes, two cases come to mind.
First, is the fact that I needed to write a new importer for our proprietary data format.  Due to a flaw in the format, it could cause overruns in the file, which were still readable in principle but that crashed both the native C file reader and the MATLAB-based file reader.  My Python implementation, however, was more flexible, and could handle the data.  Someone else in my group ended up routinely getting these overflows, so I wrote a simple wrapper script that would read the data in then convert it ta a MATLAB file, saving his project from disaster.
The second is the fact that the MATLAB-based tool for something we wanted to do is much, much, much more complicated, hard to use, and finicky than the Python equivalent.  This probably saved a good month of work, and resulted in something with much better perfomance.

I suggest to go with different languages: it provides cross-validation of your calculations. A software/hardware/algorithm might be wrong. The best way to check the correctness is to repeat the calculation in a completely different environment. So I think it is actually good that members of the lab use different languages.
Even if all members of the group will switch to the same language — the coding style might be different, and will not help for code transfer. It will only work if all of you code in the same langauge and also hold the same views on the coding itself. For example I prefer maximum modularity, while somebody else might prefer the fastest approach instead.


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When to use inline versus displayed equations in a publication?
On a publication (thesis, paper, other), when should I write an equation inline and when should it be separated and numbered from the text?
I've seen publications containing both styles, but I don't know if there is a rule to choose among them. My field is applied computer science.

A numbered equation always takes a separate line, so there is no question here — if you need to refer to some equation later in the text, it deserves a separate line and it needs a number.
If your equation is as long as a line, or even longer, then again — it should always be placed out-of-text.
To answer the rest of your question, we should think a little how we (e.g. your readers) read inline equations, and how we read equations on separate lines. First of all, inline equations merge into the text, and provide some smoothness (it is just like you speak and draw on a whiteboard at the same time). In contrast, equations of a separate line break the text (just like you write a long equation on a whiteboard and take a big pause to let your audience reflect on it).
If there are no pauses in the text, it is hard to comprehend. Too many pauses raise similar problems, because it becomes difficult to focus on the most important pieces then. My advice is to think about the role of each equation and put only the most important equations in a spotlight of a separate line.

The whiteboard analogy made everything much clearer, thanks for your answer

It's matter of style. But always think about the reader - what is the most convenient for her/him.
I agree with most of points raised by Dmitry.
However, when reading publications I often see too many inline equations, which make it harder to comprehend. It often happens due to space restrictions.
My personal stance is that only very short and simple things should be put as inline equations (like $x \in {1,2,3}$ or $y=Ax$). That is, ones that at the same time are too technical to deserve a separate line and short and easy, so they can be read with the sentence without any pause.

"too technical to deserve a separate line"? Not sure what that means.

@FaheemMitha I meant e.g. $x \in {1,2,3}$ or $U \in \text{SU}(n)$.

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How to integrate a paper where I am third author, but did a lot of work, into my master's thesis?
I am writing my thesis currently and I want to include papers that I am included on as an author.  I will have a couple papers where I am 1st author, but there is one where I am third but did a lot of the work.  How do I go about integrating it into my thesis?  Can I copy/paste most of the text still or do I need to rewrite it?  I don't want to plagiarize but don't want to rewrite it if I don't have to.

Make sure that you reference the paper, and make clear which part of your thesis is based on the paper. Otherwise you are committing self-plagiarism

This situation does not sound problematic to me.  Many people write theses that incorporate papers written under these circumstances.
However, you need to get official permission, rather than relying on what random people on the internet say.  Specifically, you need to check three things:

What does your thesis advisor say?
What are your university's regulations regarding reusing text from published papers, particularly with coauthors where it is difficult to identify who contributed to a given passage?
Does the publication or copyright agreement with the journal permit reusing this text in your thesis?

If any one of these has a negative answer, then you cannot copy the text.  If they are all positive, then all you need to do is attribute the text properly.  For example, you could clearly state at the beginning of a chapter "This chapter is an edited version of the paper BLAH."  Your advisor, university, and publisher will have suggestions or requirements for how this attribution should be done.

This answer was merged in from Copy text from co-authored paper into thesis, so that when other posts are closed as a duplicate of this one, they'll see this answer.

If your thesis is a compilation of your published papers, then check with the institution for the rules.
If your thesis is separately written, then most likely the pieces you wrote can be copied, as that's how I've gone about in my thesis. Additionally, you can also refer to the paper itself after you've written a piece of text about it.
Most likely in this situation, copying the text would not always fit the structure of the thesis chapters, and some minor rewriting is needed. Even after thesis review, the structure might modify and sentences will eventually be different from the paper. You refer having done the most work, but check if your paper co-authors are happy with using the text directly (if they've written the text). If the paper is published, cite it, and you could specifically mentioned that it was your work published in that paper.
Also, your supervisor is there to assist you and he most likely know the rules of your department and institution better.

Check with your institution. Some universities allow collections of papers to be submitted, provided there is original material connecting them that is also submitted. See, for example, the ANU's "thesis by compilation" rules.

Right, institutional rules take precedence over any other advice you might get.  It's likely that they will require permission from some combination of: your co-authors, your advisor, your committee members, the dean, and the publisher.  They may also want a detailed statement as to what your contributions to the paper were.

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What are the rules and norms for using private student data (such as test scores) in research?
I reckon that it is common in pedagogical research that researchers would want to use data which is generated as part of the teaching process at their university (e.g. exam scores). What are the norms here regarding consent and information of the students?
A concrete scenario could be that the researchers want to see whether students who took a certain subject before do better on another subject now; or a comparison of outcomes between two modules taught using different methods. The core aspect is that the data is gathered independently of the research project, but it is not public.

Just to be clear, you're talking about research per se, not instructors evaluating decisions about their courses? I.e., work that will be submitted for publication.

@AzorAhai-him- Yes, stuff that is meant to be published.

The exempt (and "partly" exempt) categories under IRB rules are detailed at Basic HHS Policy for Protection of Human Research Subjects: §46.104 Exempt research. See part (d), specifically.
This includes quite a lot of pedagogical research, but requires that students not be disadvantaged by any such research. It also requires something like anonymity for the subjects, though it seems like a rather weak form.
Even if you aren't trying to get a specific project approved, it might be worth the effort to have a conversation with someone on the local IRB committee for their advice.
While these are US rules and stronger rules may appear elsewhere, seem logical/ethical. The goal of such proper pedagogical research is to improve education so knowing the effects of various practices is needed.

The short answer is: Talk to your Institutional Review Board (IRB).

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How to have a competitive research group in a school without a graduate program?
I'm applying to assistant professor positions and my research plan is based on three main projects. My initial idea is to have 2 PhD students and one postdoc working on each project. However, there is an opening in a new school that doesn't have a graduate program yet. I'm planning to apply to this school but don't know how to explain my need for grad students. I'm almost sure I won't have sufficient start-up to hire 3 postdocs. I really want to have undergraduate researchers, as I'm a product of undergraduate research, but I believe the research output of my 5 initial years is way too important to have only undergrads and, say, 1-2 postdocs as my researcher assistants.
EDITED:
The importance of my productivity is related mainly to my research ambitions. At the same, this school is quite attractive to me because it's new. I think my voice will be heard much more in a new school. Do you think it's a good idea to search for potential collaborators in other departments of this school that have a graduate program and state this desire in my cover letter?

I believe the research output of my 5 initial years is way too important to have only undergrads — Presumably you mean "important for your tenure case".  But schools without graduate programs generally have different research expectations for tenure than schools with graduate programs.  Or perhaps you mean "important for my own research ambitions", in which case you might want to reconsider applying to schools that don't have the resources you need.

One of the key things that this school will be looking for in your research plan, is how you will embrace your role as a faculty member at a school with no graduate program. Trying to "work around" this, rather than developing a research plan that takes advantage of this, will not work in your favor.

@ziulfer  states it is a new school, please clarify what you know of the school's or department's plans or expectations? As a newly set up(?) school or department, is it assuming that it will soon/eventually have PhD plans but it is still working on the state/government approvals for graduate programs. Or has it been set up to be primarily for a strong undergraduate and undergraduate research programs.

You should look and see how people at the school handle their research, and how other people at similar schools do their work. In general, undergrads are more common than postdocs. One prominent blogger who covers research at undergraduate institutions is Terry McGlynn (https://smallpondscience.com/2014/04/02/what-kind-of-faculty-job-do-you-want/); another is Chad Orzel (https://www.forbes.com/sites/chadorzel/2015/04/10/why-small-colleges-are-great-for-science-students/#1680bf137b9a)

Is it  now too late for an answer to be useful?

@Buffy, actually it is not. I currently have a permanent position in an undergraduate institution (not the one I was applying to at that time) and I'm struggling to do research with undergrads. Therefore, I would appreciate your advice.

I am a math professor at a university in the USA with no graduate program. In my area, supervising grad students (and certainly undergraduates) would not necessarily make me more productive. My advisor used to say "Every PhD student is a paper the advisor could have written." When I do research with undergraduates, I view it more as a form of service or teaching, rather than actually helping my research program.
What does make me more productive is a network of co-authors. They always have a lower teaching load than I do, but their emails help me make progress on research even during the busy part of the teaching semester. Another thing that helps is a nearby university with a research seminar in my area. Nowadays there are also Zoom seminars, but I still don't get much out of those.
OP is a physical chemist. My colleagues in physics and chemistry do rely heavily on undergraduates to work in their labs. This involves a huge amount of time training the students and setting up the labs. The amount of research coming out of these labs is of course a lot less than it would be at an R1 institution. But, the requirements for tenure are also lower. Those professors tend to talk up the undergrad research they supervise as a real positive for the university. Students are being trained in research and then going on to good research careers. High school students interested in research might choose our university because of the opportunity to have personal one-on-one mentorship from a faculty member. Some colleagues also co-author papers with professors at R1 universities, with facilities, grad students, and postdocs who can run the experiments. These colleagues are internationally renowned researchers who frequently win NSF grants, so it is possible to have a great research career even without grad students, but you might need co-authors.
Another point worth mentioning is that many grant agencies now have PUI grants for professors at "primarily undergraduate institutions." If you apply for these, you don't have to compete with professors who have grad students. Your odds of being grant funded might even be stronger where you are, compared to an R1 institution.
I certainly empathize with the position of wanting to do lots of research, even if it's more than your institution requires. As long as you are above the bar in each of teaching, research, and service, then it's hard to imagine having "extra" research being held against you in any way. Provosts and deans like strong research faculty, even at places without a grad program. If you win a grant, it could probably fund an extended visit at an R1 university with grad students, where you could set up experiments you want them to run, and help from a distance when you're back to teaching. With grant funding, the provost might let you out of teaching for a semester, to go and set all that up. You could also use your sabbatical to visit such a place and set up such a collaboration. Try to take the long view of your career. It's great that you have a permanent position. You've solved one of the hardest parts of academia. Now you can start to layer in the kind of research career you want, building it up over time, without all the stress of applying for jobs and being a pre-tenure faculty member. Try to go to conferences and meet people whose work you like, to establish collaborations that can drive your research program. Decide for yourself if your research program works better with or without undergrad researchers (subject to the conditions of your job, of course).

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Nationality on Academic CV in USA
Is it acceptable to put your nationality on a CV when applying for a position at an American university?
For your interest, in some countries it is customary to put your date of birth, marital status, or even your religion on your CV. As far as I understand, this gets an application binned immediately in the USA. But what about nationality?

May I ask what you intend accomplish with that?

Probably putting the country of your passport and whatever relevant visas you have would be of minor interest, but, supposedly, hiring choices at many universities are not supposed to depend on visa/passport situations...

In some countries you put your date of birth, your gender, and even your religion on your CV. I am simply asking for the convention and legal implications.

At least prior to the upcoming administration (I'm soooo sorry, I apologize to everyone...) there were very few nationalities that would be excluded at all from consideration. An example: maybe Iranians currently excluded from nuclear physics/engineering programs. (I don't necessarily endorse this...) But I think that has been the only sort of exclusionary principle, if that's the concern. About the future... well, ... >:-(

in some countries it is customary to put your [...] religion on your CV. As far as I understand, this gets an application binned immediately in the USA. I'm pretty sure that's false. Certainly it would be morally questionable to disqualify an application on those grounds, and will likely be illegal as well. The correct thing to do is to simply ignore the irrelevant information (and certainly as an employer one is prohibited from asking about something like an applicant's religion, but the applicant him/herself is free to volunteer any information they wish to share, in the CV or elsewhere).

I've seen it many times on applications, and it made not a shred of a difference. We did occasionally have Iranian applicants, which is probably the most problematic case, but again it made no difference -- if we wanted to hire someone because of their qualifications, we still did not care about visa issues because that's someone else's problem. For any other nationality, it was a non-issue that wasn't even talked about.
To show you what else doesn't matter: Because I'm German, I put my nationality, birthday, and marital status on my CV for all my postdoc and assistant prof applications. It made no difference: I got invitations to interviews and offers regardless. I don't do it any more because I've learned that that's not typically done in the US. But it really made no difference one way or the other, neither legally nor as far as the hiring committee is concerned.
In summary: You're overthinking the issue :-)

No, don't include it.  Generally, for a US position, your nationality won't be directly relevant to the decision.
There are a few cases in which nationality might be indirectly relevant is if the institution wants to know if you already have authorization to work in the US, or if you would need a visa.  There may also be positions (especially postdocs) which are funded by the government and reserved for US citizens or permanent residents.  But if one of these is the case, they'll ask that question directly on the application, and you just have to answer yes or no.  Either way, the CV isn't the place to put that information.

This seems inaccurate. Aren't many postdocs funded by grants that can only support US citizens or permanent residents? (like e.g. NSF RTG grants)

Would it be harmful to include it if it's not required?

@dbluesk: For positions where it's not relevant, hiring committees will know they can't take it into consideration.  So if you list it, they will have to make an effort to disregard it and make sure it doesn't influence their decision.  That can be a distraction, and you don't want to cause them unnecessary distractions.


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Asking for teaching recommendation
I'm a postdoc and have recently taught/designed a graduate-level course. Who would be the best person to ask for a teaching recommendation?
I was thinking of our associate chair, who oversees course approvals and assignments. I want to include the syllabus, class project description, an example of homework, my teaching evaluation, sample video of my teaching from one of the lectures.
I would appreciate any input on what to attach and what to ask, should I ask for their emphasis that I also designed the course, or any other suggestions.

The associate chair would be good in this case, but ask them, or a representative they select to observe you in the classroom, possibly several times.
Along with a recommendation, they can also provide you with feedback and advice on how to improve your teaching. I suspect most new instructors will benefit from that and it is part of the evaluation process in some places.
And an observation or three can lead to a more "personal" recommendation.


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Question on Networking Etiquette
During a conference last winter, I had the opportunity to have an informal interview with a PI from "University A" in Boston. Although the position was not immediately available, there may be a potential opening for Spring 2024. After our discussion, PI-A expressed interest in staying in touch.
I have a talk scheduled with PI-B's lab at "University B" in Boston in a few weeks as part of a post-doc interview. While in town, I would like to reconnect with the PI from University A to maintain a professional network and discuss potential future opportunities. I am unsure about the best approach and would appreciate your advice on the following options:

Emailing PI-A to request a meeting over a cup of coffee during my visit to Boston. PI-A seemed open to this idea during our previous encounter, so it may be appropriate to extend the invitation.
Inviting PI-A to attend my talk at University B. While PI-A's
availability may be limited, it could provide an opportunity to
reconnect. However, I wonder if it would be better just to email
them and invite them for coffee instead.

How appropriate is it to invite PI-A to my talk at PI-B's lab? I am concerned about the implications for my opportunity with Lab-B. Should I seek approval from PI-B's lab manager first? My proposed approach would be to mention that a colleague from University A is interested in attending the talk if it suits their schedule. Subsequently, I would reach out to PI-A to gauge their interest.
Lastly, I would like to know how appropriate it is to invite someone I had an informal interview with to engage in scientific discussions over coffee.

(1) is surely OK. You tell them you will be in town on [dates) to talk at B on (date), ask to meet informally, and see what happens. Perhaps their followup will provide more informatiion.

Why not suggest both? If A can and want to come to the talk, they will come (and you can also meet at coffee later); if not, you'll meet at coffee. If you don't know whether external visitors will be allowed at the talk, just mention this, A might be better aware about how it is usually handled there.

How appropriate is it to invite PI-A to my talk at PI-B's lab? I am concerned about the implications for my opportunity with Lab-B. Should I seek approval from PI-B's lab manager first?

If this is a public talk, as I think university talks usually are, then you shouldn't need approval from PI-B's lab manager.  After all, PI-A has as much right to join as anyone.  If it's not public, I would just briefly ask PI-B if they'd be OK with inviting PI-A.  They probably know each other, so it should probably be fine if they're not mortal enemies.
Inviting PI-A to your talk at University B does not rule out meeting up with PI-A at university A later.
In the final year of my PhD, I gave a short talk at the university in Boulder (Colorado, USA), and to my surprise, a senior scientist I knew from a nearby research lab just outside town came over to listen.  He must have found out about it somehow, but not from me.  It was good for me, as my main aim with the visit was to network for the purpose of finding post-doc opportunities in the first place, and due to time issues I had not scheduled any visit to the research lab in question.

Aside from options 1 and 2, which you mentioned, there exists option 3:
you can inform PI-A that you will be in town for a seminar, and that, if he is interested, you will be happy to give the same seminar for his group.
[ As we all know, the schedule of official seminars is prepared well in advance, but it is not uncommon to hold an informal "brown-bag seminar" on an ad hoc basis. ]
Such a suggestion would leave to PI-A several oportunities to choose from: to agree to hold an informal talk, or instead to attend your talk at university B, or simply to invite you for a meeting over a cup of coffee.


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Does having a more successful professor write your letter of recommendation improve your chances of having your application accepted?
My question is about academic careers of a professor who would want to write a recommendation letter for someone. Some professors in my university have better academic career than others, for example they would have graduated from better/more well-known/higher ranked universities around the world, better resume/CV, higher GPA in MSc. and PhD, etc.
Question: Does a stronger professor's letter of recommendation raise someone chance for his/her application to be accepted?
Some basic contexts:

Apply in PhD program in computer science
Apply for US universities

Recommendation letters are all about trust: why should the person reading the recommendation letter believe the person who is writing it, when they say that they should place trust in you?
Thus, all else being equal, a professor with better qualifications provides a stronger recommendation.
Other considerations, however, can be more important, as it all boils down to the basic question of trust.  For example:

A little-known professor who knows you well and has worked together with you is a better recommender than a world-famous professor who can only say: "This student was one of 100 who got a good grade in my giant class this year."
A professor with a close colleague in the department where you are applying may be much more trusted in their recommendation than a world-famous professor who nobody in the department knows personally.

Furthermore, you probably will have more than one letter writer, and diversity in your letter-writers can be a virtue: some more prominent, others more in depth, etc.  Thus, you really need to look at this as a whole package, and say: "What is the combination of people who will, as a collective, present the most favorable and trustworthy picture of me to the particular places where I am applying?"


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What is the value to a student of a professor offering to supervise their PhD?
I am currently getting my M.A.T. in secondary mathematics. As a part of my degree, I take graduate level math courses. I am currently in a PhD level math class, and the instructor of this course has told me that if I want to get a PhD in mathematics he would want to work with me because he believes I have a "future" in his subject area.
My question is, what is the value of his offer? Is his kind of offer easy or hard to come by?
The mathematics department at this school is not renowned, but I respect this professor's work. Is his offer something I should definitely take advantage of, or should I shop around for different universities/offers?
I hope my query isn't too specific. I am feeling quite conflicted and would appreciate any and all input.

The easiest way to get into a Ph.D. program is to have a professor who knows who you are and wants to have you as a student.  In many other questions on this site, people talk about the difficulty of standing out from the crowd amongst the large number of applicants to any decent Ph.D. program.  With this professor, at least, you have stood out, and that's quite significant... if you want to do a Ph.D. with them.
First a sine qua non: don't even consider it if the program doesn't guarantee some degree of funding.  Every respectable university should be offering support for its STEM Ph.D. students through some mix of research and teaching assistantships.  It should be the department and not the professor that guarantees funding (though if the
professor has funding, they may be able to give you more time as a research assistant rather than a TA, if that is what you both want).
Beyond that, key things to ask yourself:

Do you actually want a Ph.D.?  Getting a Ph.D. is a terrible, soul-wrenching process and it renders you unfit for most employment.  If you are truly drawn to research, however, it is the best and only course to take.
Are you OK with not being at a famous institution?  There are only a few famous institutions in any field, and getting into them is a gamble. Often, however, there are a great many solidly respectable institutions that can launch you on a totally reasonable career, especially since it is often possible to "upgrade" institutions through postdocs.
Do you really want to work with this professor?  You don't know what working with this professor will actually be like. One advantage of the high-profile institutions is that if you find things aren't working with your advisor, there are often many opportunities to switch to others.  In a smaller and less renowned department, you will likely have less alternatives should things go wrong.

Ideally, if you answer yes to all of these questions, you should start doing some work together now, so that you can get a sense of whether there's a good working relationship.  If so, embrace it and be grateful that you found a good match.

Unfortunately, no one can be told what the Matrix is. You have to see it for yourself.

I like the rest of the answer but: "Getting a Ph.D. is a terrible, soul-wrenching process." C'mon. That's a bit dramatic. Getting a PhD is not always easy but it's not necessarily terrible and soul-wrenching. I know it's not everybody's experience but I found getting a PhD to be wonderful, fun, challenging and exciting and with less frustrations that my previous work in industry.

"Getting a Ph.D. is a terrible, soul-wrenching process." This reminds me of the joke that doing a Ph.D. is much like trying to take the Ring to Mordor. See: http://danny.oz.au/danny/humour/phd_lotr.html.

Also that line from the first LOTR film that explains Ph.D. students: "They were elves once. Taken by the dark powers, tortured, mutilated. A ruined and terrible form of life." I guess that makes postdocs Uruk-Hai? :)

I think 3. is the most critical point.  Your decision to work with him should also involve your interest in his area of expertise.  Note you don't have to be a grad student to work with someone on a project. Also, standing out is good because it means he could be a good reference for another program.

Whenever you get an offer, always shop around.  That is not academia-specific.
Generally professors who work in Ph.D. granting programs want to have Ph.D. students.  It may even be necessary for them to get some Ph.D. students in order to keep their jobs.  Therefore it can be easy to find a faculty member who will encourage potential Ph.D. students.  I would not put much value on this sort of offer unless it includes and offer of RA or fellowship funding.
Never get a Ph.D. to please a professor; do it only for your own benefit.

I agree with the other posts, but to directly answer your question about the value of the offer. Unless you want to get a Ph.D. in math, the value of the offer is zero.
If you are interested in doing that you should definitely explore other options.  At a minimum, it will help you better understand the plus and minuses of the program at that institution and working with this particular professor. If he's worth working with he should be encouraging you to do this as well, IMHO.  Note that most competitive Ph.D. programs not only provide funding, but also invite top candidates to interview and visit.  It's usually an eye opening experience.


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Should you thank helpful referees in the acknowledgements section of a paper?
I submitted a paper to a [science] journal and received some particularly constructive feedback from the referees. I am inclined to add something to the effect of
We are grateful to the referees for their constructive input.
to the acknowledgements, as I have seen in other papers before. But is this considered appropriate?
On the one hand, it seems polite. But on the other, it's part of the job of a referee to make suggestions. Moreover, since they are anonymous and I am not going to specify their contributions, the only information provided in this remark is that 'someone suggested something' which seems a bit pointless.

I usually try to add a line to the acknowledgements to thank anonymous referees and I try to make it honest and clear. Reviewers' time and effort invariably improves my papers and I think it's only polite to thank anybody who contributed for their time, effort, and engagement to making a manuscript better.
Will anybody care if it's missing? Will anybody even notice if it's missing? Probably not. That said, although it may be the "job" of the reviewers to give suggestions, refereeing is something that academics do as volunteers. Reviewing papers is perhaps the most thankless part of an academic job. Acknowledgement of the positive impact that referees have seems like the least an author can do.

@DanielHatton: The advice still applies. For blind review, you are required to withhold this sort of acknowledgement because it it breaks anonymity. For non-blind review, I imagine any editor will allow you to add this after the paper is accepted when you thank the reviewers of the journal in question if you are worried it will bias the reviewers against your work.

@DanielHatton If that's the entire section, it would obviously be fine. The problem is that other text that is commonly in acknowledgements sections reveal things about the authors identity (e.g., workshops, individuals, institutions, funding, and so on).

Referees typically use significant time and effort to provide their expert views on manuscripts in the review process. It is therefore never a bad idea to thank them. That said, there are a few things to keep in mind.
First, keep in mind that your revisions, based on their comments and the editor's handling is what the reader's see. It would not be fair to make it seem as if the resulting article is all due to the reviewers comments. In fact, they may end up disagreeing with some points of your final article.
Second, a bad type of behaviour is to acknowledge reviewers in a way that does not reflect their statement. I know of a case where an well respected peer was mentioned as having provided "valuable input on an earlier version of the manuscript" where the review was a "reject" of a really poor manuscript. In this case it was made to look as if the current manuscript was endorsed by the peer, which really was not the case. [to add a further explanation: one can promote ones own work by implying that someone who is a major name has provided input earlier and by doing so have provided input to the state of the manuscript under review]
So, thanking reviewers is a good way to provide acknowledgement to persons who support the process but remember to phrase it so as not to put aspects of the final paper in their mouth that they do not support.

I fail to see how "thanks for valuable input on an earlier version" implies endorsement of anything.

(1) This answer seems to suggest that you know who the referees are and thank them by name. I had assumed this questions about adding a line thanking anonymous referees. (2) A well explained decision to reject can still reflects valuable input. A "thanks for input" need not and should not not imply endorsement.

No it does not matter if they are known or not. One simply refer to the reviewers as anonymous. In my field anonymity is a choice for the reviewer and it is therefore common to refer to a specific person and an anonymous reviewer in the acknowledgement.

@JeffE I am sorry that you fail to see that one can promote ones own work by implying that someone who is a major name has provided input earlier and by doing so have provided input to the state of the manuscript under review. None of anyone I have discussed such behaviour has missed the point.

Please do not forget that the academic system for publishing original articles owes a lot to reviewers and referees, so I am sure some journal editors will suggest the autor(s) to include the acknowledgemente to them.


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How to frame incomplete previous studies when applying to new graduate school without being too negative about previous program?
I had a bit of an unfortunate experience with an academic institution where I completed the coursework for a theology Ph.D. without high enough grades to continue. There were other things that were unfortunate about that experience, but the best advice I have been given is that if I try to return to studies, I need to explain why I don't have a reference from my previous Ph.D. programs, and if I document things that were wrong, that comes across as "I am a negative person who will publicly backstab a university by criticizing it after exhausting his appeal options" rather than "XYZ happened and if you can document it, we will make accommodations." (Additionally, I've tried to document the talent I have, but documenting that I am talented, no matter what talent I document, doesn't seem to trip any light bulbs of recognizing I may be a promising student.)
In graduate school admissions, what is a convincing non-negative way of explaining "I don't have references from my prior program?" And is there any way to get connections made between "gifted" and "promising student"?

what is a convincing non-negative way of explaining "I don't have references from my prior program?"

If you dwell on it, it will sound like you're making excuses. It's not really worth spending more than a sentence describing unfavorable circumstances that made you leave this place or that place. It might even be better to not mention at all. Just make sure you have favorable references from somewhere to go with your application.

is there any way to get connections made between "gifted" and "promising student"?

Through achievements. If you say "I am good at X," no one cares, or really believes you. If you say "I did A, B, and C," it's good if you can say "I received award Y," by pointing to things that demonstrate that you are good at X, then you will look good. Talents only count to other people if you use them to achieve results.

+1 for "Talents only count to other people if you use them to achieve results"


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Interrupting a German research fellowship
I am going to accept a research fellowship in Germany for the duration of 24 months.
In the Guideline, it is written that (in English)

Interruption to take advantage of another fellowship in Germany or a third country is usually not possible.

I came from Italy and my plan is to continue there my academic career. My question is the following:
Can I interrupt the granted fellowship before the two years to take advantage of an Italian RTD-a (it is a short-term research position of the duration of 3 years)? Is an RTD-a considered a research fellowship?
Thank you!

You can quit the German fellowship to take the Italian one, but ‘interrupting’ to go elsewhere for 3 years is unlikely at best…

@JonCuster Ah ok! I misunderstood the word "interruption". Thank you!

Interrupting the German research fellowship would mean something like taking the German fellowship for a year, then being on some other fellowship, and afterwards returning to complete the second year of the German fellowship. The default assumption for any kind of academic position would be that interrupting it in this way is not possible, and the language in the rules here is just to reinforce this default assumption. In particular, this is definitely not saying that you can interrupt the German fellowship for something that does not count as a fellowship.
On the other hand, ending research fellowships early is common (as aligning end and start dates perfectly will not always be possible). Some fellowship schemes have restrictions on this, in particular if the manner of ending it early would interfere with the intended goal of the fellowship scheme. However, in absence of such language my default assumption would be that it is possible to end the fellowship early.


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Should I choose the schools that I apply to, or should I ask my advisors to do that for me?
I am applying to some PhD programs this year. If I just ask my advisors to choose the school for me, they might think I am lazy and have done no research. However if I do that on my own, I am afraid that maybe the advisors think I am arrogant for aiming for schools out of my reach. The problem is I don't know how strong my profile is and I think that my advisors should be better informed than I am. What should I do?

Fortunately, this isn't an either-or proposition!  I agree with your assessment that you shouldn't come to your advisors empty-handed and ask for some schools to apply to.  However, it would be perfectly reasonable for you come to them with a couple schools you like - probably spread out by competitiveness and such - and maybe some guidelines for what you want to focus on and where you would be willing to move to.
Ask their opinions on the schools you picked, and ask them if they have some others they would recommend, based on what they know about you.

As @Jeff says, you should follow both of the paths you suggest: develop your own ideas, and then talk to your advisor. (And don't be offended if their perception of your potential versus those programs is not the same as yours. They still may be wrong...)
An important aspect both for you yourself to think about and for discussion with your advisor, is what your ambitions/goals are, and how much risk you are willing to accept, and also stress. That is, there is a genuine and large issue about what your measure of "best" is. It is important also to realize this.
Added: I forgot to mention the practical point that you should contemplate whether you'd prefer (for example) being one of the weaker students at a top place, or one of the strongest students at a less-than-the-absolute-top place. This can have a psychological effect on you while in the program, and can affect your prospects afterward: the second-best student of a famous person in a given year will take a back seat to the best student of that famous person in many (not all) job application situations. (No, this is not sensible, but, in my observation, things tend to work this way mostly. It is harder to justify a job offer that might be accepted, but to the second_best, than to make an offer, that will almost surely be declined, to "the best". The huge point is that the way hiring works (in the U.S., in math at least, at R1's...) is that "the second best" in_a_given_field will never get a chance, because hiring ops rotate through subfields...
But, I think, the hiring game outside of R1's is less nutty... but/and that is a fact that should play a role in your career planning.

I am willing to get a job in private sector. I will tell my profs two categories of school that I apply to. The first category are schools that are good at research and the second are ones that have track record in sending people to top companies. Is that a good idea?


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How can one disclaim?
How can an innocent person disclaim a plagiarized publication which he did not give consent for publication?
The paper has has been published without my consent and my name was included as a co-author but i want to disassociate myself from this paper?

Was a paper containing plagiarism published with your name on it or is it plagiarized because you did not approve of the publication?

the paper containing plagiarism was published with my name. I saw it on researchgate.

If this is a published with some legitimate publisher, then contacting the publisher and pointing out that you never consented to being named as an author on that paper should suffice. The publication record should be amended, and the paper probably be withdrawn.
If this is not published with a legitimate publisher, the strategy above might fail. You can try to threaten to sue them, but ultimately the most you can reliably do is to put a disclaimer on your homepage.
This could take a form like "It has come to my attention that the publication XXX lists me as a coauthor. I have not been involved in this project / not consented to the final form (pick as appropriate). The publisher YYY has been informed of this on DATE and is yet to take action. (you should probably give the publisher a few weeks to react before putting this up).

thank. What exactly can be in the content of such disclaimer? The paper is already on researchgate and i never gave the lead author consent to include my name or even the Publisher to publish. What do I do?

Contact ResearchGate. They seem to be trying to become legitimate source for scientists, so they should take your complaint VERY seriously.

@xmp125a Assuming that ResearchGate is just reporting that the paper has been published elsewhere, then I think elsewhere is the first point of contact.

@Arno if the journal/conference in question is obscure and uncooperative, at least he can remove it from one of the sources where it seems to reach large audience (since OP discovered it this way).


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Is it acceptable to use non-English references in a computer science paper?
I am currently reviewing an interdisciplinary computer science paper which is heavily based on previous works in logistics and process engineering that have been unfortunately published only in German (18 out of total 30 references). The overall idea is sound, but as the logistics structures are in some sense a basis of the paper, I have a strong inclination to reject the manuscript as the research cannot be followed and reconstructed by a researcher that does not understand German.
On top of that, virtually none of them are available online, or otherwise easily accessible.
I was going to hit the "Reject" button just a few moments ago, but I still have my doubts: I know that in humanities and also in mathematics people often cite publications written in other languages, but I have not yet seen something like that in computer science. Also, if it were one or two references, but 60%? The journal reviewing policy does not help me in this case.
I was thinking about proposing the following workarounds:

Extending the paper - this is probably not an option as the journal imposes quite a strong page limit, or
A supplementary report - the vital parts of the non-English text could be made available as an Technical Report or an on-line publication (I was thinking about arXiv) and this can be referenced in the manuscript.

Is it fair to reject it? Has anyone experienced something similar? What was your decision?

Comments are not for extended discussion; this conversation has been moved to chat.

Could you expand on what you mean by "virtually none of them are available online, or otherwise easily accessible"?

As the reviewer, are you fluent in German yourself?

Having many non-English references is absolutely no valid reason to reject a computer science paper.
If a reader wants to follow up on the references, they can learn some German, find a translator, etc. But this is the responsibility of the reader, not the author.

Comments are not for extended discussion; this conversation has been moved to chat.

I tend to agree with @Arno's answer that citing non-English sources is fine. But that is actually beside the point, since as far as OP's situation is concerned, I think he has much less of a dilemma than he thinks.
The reason is that whether to publish a paper that references many German-language sources should be an editorial decision. As a reviewer, OP should check that the paper is correct (including looking up the references to the extent that's necessary, which OP can do since he speaks German), and that it is novel and lives up to the standards of the journal. If those conditions hold, he should recommend acceptance. He can also point out in his report the potential issue with non-German readers not being able to fully understand the theoretical background the paper makes use of. It would then be up to the editor to decide how to handle the situation, depending on their philosophy and the policies of the journal (which may vary, for example a journal published in Germany might have a different view of such issues than one published in the United States).
To summarize, the question of whether papers like this should be published is a very interesting one, but from a practical point of view, I don't think OP really needs to concern himself with it.

I am not sure that it is only about non-english sources. I have cites tons of non-english results, but it is easy to get hands to the originals or some translations. In the case of OP we are talking about some obscure and impossible to find on-line results. Also, if we expect the readers to learn new languages to understand results, why we have preliminaries and related work where we describe on a high level the techniques/results we need?  If I am criticized that I do not explain what Gram-Schmidt Orthonormalization is (yes! it happened), why not the authors of this paper?

@PsySp sure, there are other considerations besides the language (although whether something is available online is in my opinion not a valid consideration; plenty of sources, textbooks in particular, are generally not available online, and no one thinks that this is a problem). But as I said all of those are issues for the editor to consider, and I don't think they should influence the reviewer's recommendation, as long as the reviewer is able to verify the correctness of the paper and evaluate its importance.

I agree with you that the reviewer can make suggestion and explain the issues and then is up to the editor to decide what to do. In any case everybody has focused on the "german/foreign language" issue which to me is not the real issue here. For me is pretty clear: if we cannot even find and/or reproduce the results, the paper looses a lot of credibility and in any case it doesn't help the authors increase the visibility of their result.

obscure and impossible to find on-line results — There’s this brick building down the street with a bunch of books in it, where you can find people who are actually paid to track down copies of “obscure” references like the ones you describe. I believe they’re called librarians.

Your only responsibility as a reviewer is to check that the article is scientific, relevant and original enough. When references are valid, the language should not matter, especially if - as you say - you can check them because you personally do know German.
In other words: I too am shocked that this is even an issue.

Your shock aside, I think it's good that such a question has been asked and so unanimously answered, since it's likely many reviewers out there harbour such misconceptions.

See it the other way round. Many German papers have English references, although not all readers will be fluent in English.
If you cite from a foreign book, eg. chinese it is helpful for the reader to give a (rough) translation.
If you reference to a paper from an 'exotic' language to translate the tile and give a very short synopsis of the content. Because it is helpful to know whether the reference is a paper on a specific problem or giving an overview over another topic.
If you are restricted in length in a journal, create a small website, were you provide the German original sources and make it readable to the english reader, by letting out the German citations.
Is the paper still valid with many foreign references?
As a informed reader I would ask whether the reference given are available in the language of the paper. E.g. referencing to a standard algorithm in a german book, when the same algorithm is described in many english books. If this is the fact I would be more alert concerning the validity of the paper.
However brilliant papers have been written in China, behind the iron curtain and so on, without any reference to english sources.
I'd be happy to read a such brilliant work

I'm not sure how computer science publications work, but having used quite a few non-English papers myself I have the following suggestions.
Almost every paper adds a small increment to the specific subject. Usually, authors can easily find one or several English language papers connected to the non-English paper and cite those instead to support their arguments.
In case the authors cite data from a non-English article, it quite acceptable. In this case they must reference strictly numbers that can be looked up in the article by a reader who doesn't understand the language. If there is a need to cite methods or interpretation of the data, then they should be translated and briefly summarized in English.
In any case, the burden of translating and verifying foreign texts should not fall on the reader of a journal.

From a physics point of view, careful citation of foreign-language sources is fine. Citing data is one case.  Another might be citing a major result (such as an algorithm) but in that case I prefer to see the citation of the original paper followed by a clear citation to an English source that discusses it.  That of course isn't always possible

-1 for suggesting avoidance of citation of non-English papers because they're not in Engish.

Have I understood your answer correctly as saying this: "When an paper written in English wishes to cite a result first published in a different language, it would be best to cite a paper written in English that explains the result"?  I'm pretty sure such a paper must, by necessity, cite the original source, which puts it right back into the category of "paper written in English citing a foreign language source".  Is the paper being reviewed the chicken or the egg?

@BenVoigt There's no contradiction in saying that an English-language source should be cited if one is available. Obviously, the first English-language paper to refer to a particular result fails the "if one is available" test, so there is no paradox here. (I disagree with the answer, but your claim that it leads to paradox is incorrect.)

@DavidRicherby: You misunderstood me -- I'm saying that unavailability of an English-language source is not as rare an event as the answer suggests, as it must happen at least once for each foreign language paper.  (Alternatively, "if the set of English papers citing a result first published in another language is non-empty, at least one of these papers is reviewed before any of them are published")  Sure you can use  circular citation to ensure all papers written in English cite another paper written in English using the same result, but that doesn't help the reviewers.

I like your idea to propose the mandatory provision of a supplementary report.
At the cost of some extra effort for the authors, this would be a good compromise between the interests of the authors (getting a fair evaluation of their actual work) and those of the readers (being able to reconstruct and extend the research).
An included benefit for the authors would be the possibility to disseminate the underlying ideas to a wider audience.

We agree (see my answer): it is the responsibility of the authors to convince the audience that their techniques are sound. Readers cannot invest time to learn new languages to understand a paper. Also, this can be done like a conditional accept: provide the neccessary info and then we may accept your paper but in its current form it cannot be possibly published.

I would not call that "some" extra effort.

@PsySp "Readers cannot invest time to learn new languages to understand a paper." That is the fault of dumbed-down modern education systems. When I was a kid (in the UK) learning two foreign languages (and sitting nationally standardized exams in them) before the age of 16 was considered perfectly normal for anyone likely to be educated to degree level. We also learned a third foreign language in a less formal way from age 16 until starting university. And I don't recall any of the kids complaining that "it was too hard" or "it wasn't fair".

@alephzero the dumbed-down educational system in my country? You do not even know how many languages I speak, yet you make assumptions.

@PsySp Apologies. You replied to my comment before I had finished editing it.

@alephzero You completely miss the point. It's not about how many languages I speak or I learned in my dumbed-down educational system (sic). It's about being able to verify something. These references cannot even be found, and besides, what the fact that you speak 100 languages has to do with the fact that a casual reader would need a translator if he even finds the references.

@alephzero PsySp talks about a situation where you must learn arbitrary new languages on the spot to understand a paper, while you talk about learning two or three specific languages in school. Since you grew up in the education system before it was dumbed down, you should have the logical tools to find the flaw in your argument.

no  no, no, the responsibility is the READERS, not the authors. Rejecting science based on the INCOMPETENCE of the reader is always wrong.

@GwenKillerby: So if I submit a CS paper written in Latin, is it my readers' responsibility to accommodate that by learning Latin?

@PsySp The references cannot be found online, which is not the same as cannot be found. Libraries are there for a reason.

@MassimoOrtolano Actually, we do not even know if they can be found even through library systems. Anyway, as I outline in my answer, rejecting a paper for such a reason is far from advisable. What would be advisable in this case is the authors to help the readers by providing a summary/whatever of these hard to find references.

Rejecting a paper because you do not understand the language doesn't sound like a good excuse and people will get frustrated.
On the other hand, since it is not some standard and well known/used publication that has been scrutinized and/or translated, and it cannot even be found online
 it is up to the authors to make every possible effort and convince the readership that their techniques and relevant results are sound.
I suggest to give them the chance to enhance and update their manuscript with all the necessary details in order to judge the soundness of the paper. Failing to do so would (and should and a fair warning) lead to a regretful rejection.

This, I think, is the crux of the problem: If the sources were available online, then at a pinch an interested reader could hack their way through with Google Translate or similar. But most non-German researchers are going to have a very difficult time getting hold of print-only, German language articles, let alone getting them translated. My (US) institution's library would probably not even ILL a physical document that is only available from libraries in Germany. And if the sources aren't discoverable in any way, then they might as well not exist.

@1006a apparently, it is considered easier for readers to find the hard-copies and then find translators/learn new languages that the authors to include a discussion of the used results. I extensively cite non-English material in my papers but the huge difference is that the reader can find easily the texts, and/or their translations. I could not possibly ask the readers to learn Ancient Greek to understand Diophantine approximations

"Some references cannot even be found online" is an absolutely ridiculous reason for rejecting a paper or suggest the kind of radical changes you're proposing. A huge fraction of the scientific literature, covering the first 90% of the history of science, is unavailable online, but it can easily be obtained by getting up and going to a library, or mechanisms like inter-library loan that were how science did its business for much of its history (and which seem to have worked perfectly in OP's case). Does that mean that all of that archive is now off-limits to citations?

@E.P. As I said, rejecting the paper because the references are foreign is radical thing to do. Having said that, I do not see where is the problem the authors to make their, and our life easier, and explain the relevant techniques used. When you use a technique, don't you give a high level explanation of it? Don't you have a Relevant Work section?  Do you exclusively use pointers to relevant results without any attempt to explain them? Why can't we ask the authors to include something similar? It will be win-win situation for everyone.

@PsySp Did you actually read my comment?

@E.P. I did, and I was trying to understand why you think it is a radical change I am proposing. Have you read my comments?

You're proposing that the authors spend a significant amount of work, thereby taking time away from useful research, to make up for a perceived inability of the readers to use inter-library loans in the same way it's worked for decades, and I don't see how you can think that that's a minor change. It feels like you expect readers of scientific literature to have everything spoon-fed to them, from language to availability, but that's not how the research literature works.

@E.P. I am simply inverting your argument: You are proposing that every reader of the paper spends significant amount of work, thereby taking time away from useful research, to make up for a perceived inability of the authors to use inter-library loans in the same way it's worked for decades. How is the time utilized better? by the authors doing the proposed job? Or by every reader does the same job again and again?

Reading the scientific literature has always entailed a certain amount of work. You're entitled to your opinions, but I will just note that if I got a journal rejection based on the kinds of opinions you've expressed on this thread, I would take it as a good reason to take my publications to some other journal that does understand how science and its literature is structured.

@E.P. I completely understand your point. My only objection is that as an author, if you value your work, you should make every effort possible to make it accessible. I honestly fail to see how this is radical.

That is the authors' concern, and possibly the journal's, if they really do have a consistently high standard of accessibility to maintain. It is definitely not the reviewer's role to reject papers on this basis.

@E.P. Reading the scientific literature and, I would add, _transmitting your ideas in the most efficient way, requires time, talent and dedication. I do not mind searching in libraries. But I mind if the authors do not do their scientific job.

Let's not. As I said, you're entitled to your opinions, ridiculous as they are, but thankfully if you chose to act on them to reject papers, most sensible editors would recognize you're overstepping your boundaries and dismiss that report. I don't see the point in further discussion.

@E.P. I do not see either (was a mistake). I respect your opinion, and I won't ever call any other opinion that I disagree, or find excessive, ridiculous.

@E.P. The OP is talking about 18 out of 30 references, and states that "virtually none of them are available online, or otherwise easily accessible." To me, that suggests that fully half of the references in the paper are unverifiable. That's a problem, and not at all usual. Even old journals that were originally only in print are now largely available electronically; my library recently decommissioned 90% of our bound periodicals because they were all duplicated in electronic format. Older stuff, in particular, is likely to be freely available online because it is out of copyright.

Note that I am assuming that "not available online" means not even available behind a paywall.

@1006a OP's first comment on the question confirms he was able to obtain offline all the references required to verify the paper. That is not what "unverifiable" means. Your position would imply that references that are that easily accessible, comprising a large fraction of the literature, are off-bounds to further use.

@E.P. No, the OP's comment is "I did read one of the references and I could read the remaining ones once I get hold of them (virtually none of them is available online even if they are fairly recent -- this is also something that is bothering me, maybe I am just paranoid)." In other words, the OP has so far only been able to obtain (and verify) one out of eighteen of these references.

@E.P. Your position would imply that references that are that easily accessible, comprising a large fraction of the literature, are off-bounds to further use.  Please, do not use straw man arguments.  Nobody said or implied that and by assuming so, doesn't mean it's true.

@1006a I am not sure it's a good allocation of one's time to try have a conversation with people that attack a strawman and declare different opinions as "ridiculous".

What is the purpose of references? Certainly allowing the average reader to follow the research is a part of it, but the more important part is giving appropriate credit to where the authors got their ideas, which may well include papers in the authors’ native language or which happened to available to them but not the wider internet.
In itself, definitely not a reason to reject.
That said, the paper should stand reasonably well on its own - the text should include sufficient summary that only those particularly interested in the details need look for translated versions of the citations. Also, a qualified reviewer should be able to confirm that the cited paper says what the authors claim it does.

I would recommend rejecting any paper that is incomprehensible to somebody in the field without following its references.
The references not being in English isn't the problem. Leaning on the references too much is.

I would add: leaning on references that you cannot even find online!!

@PsySp Get thee to a library already. Complaining about references not being available online is pure laziness.

I would not go for a reject for this reason.
As a reviewer, wishing that authors provide more background from foreign language papers is acceptable. I would do so in this case.
Like, in normal case it is straightforward to assume that the reader can inform herself on previous techniques from earlier papers and you present the state of the art more to highlight what you have done differently.
Here it is not like this. So, the authors might be required to present a better/broader overview of the related work and state of the art. As a reviewer I would basically ask them to retell the essence of the foreign-language papers, so their paper is understandable and makes sense even if the reader cannot read the foreign language references.
As a side note: where it mattered, translations were published. You paper authors might not be aware of them, but they might be out there. I know that some Russian math journals were routinely translated in English during the Cold war. It's another issue how to cite such works in an English paper...


text:
Advisor publishing students' work as sole author - ethics and motivation
This is a question about my advisor (supervisor, professor) in a lab, where I am a graduate research assistant, and had done research together with a PhD student, as a part of his dissertation. The student happened to be one of my close friends. The professor wanted to write a journal paper based on the results of his dissertation with that candidate. This was kind of near the end of his PhD program (three weeks before final defense). At that time he said that he was already stressed out about defense and will write the paper after the event as it won't take him more than a week.
After he graduated, he had asked the professor about the journal paper but the professor kind of brushed it under the carpet saying he is looking for CFPs (call for papers) where they can write and never got back to him, despite his constant inquiries.
For his research on human-computer interaction, I had developed applications which formed the core of his project. So my advisor asked me if I was interested in writing the paper and she convinced me that since I developed the applications (that formed basis of the research) it was fair enough that I write it. But after a week, she ignored me and wrote the paper herself and submitted it to the journal.
I came to know last week that my advisor wrote the paper herself and got it published. This professor is an assistant professor trying to get tenure. I am trying to understand the motivation behind this behavior.
My questions:

The journal paper was published by my professor as sole author. Won't the paper count towards her tenure if she wrote it with a graduate student or will it count towards higher credit if she is the sole author?
Is it ethical to publish the paper based on my friend's dissertation? (I mean it is legal, because she will be referencing his PhD dissertation, but is it ethical or common in academia to sidestep the original author?)
Should I be listed as co-author for all papers coming out of this research because I developed the applications that formed basis for this research? I mean the concept for them was not mine, but I did program them.

There are multiple important questions here I think. Could you possibly edit your question to clearly enumerate the questions you want answered?

It's not clear from the description whether the journal paper was published with the professor as sole author or not.

@Suresh my prof. listed herself as sole author

As a side note, how are you people writing papers in such a short period of time? A journal paper in a week???

@AustinHenley the journal was just rephrasing his research questions and compiling his test results

Crucial missing information: does the PhD student agree with this statement of events and will they back you up? Do they also strongly object to not getting the author credit? Are they still at this institution or have they moved elsewhere? And are there are any other such cases?

Before anything else: Don't walk.  Run.
There are almost certainly details of this story that you have omitted, or that you have unintentionally embellished, or that you are unaware of, and clarifying those details here would be inappropriate.  What is clear is that your relationship with your advisor is completely broken.  Get help, and get out.

Q1) Wont the paper count towards her tenure if she wrote it with a graduated student or will it count towards higher credit if she is the sole author?

All publications count toward tenure, whether solo, with colleagues, with current students, with former students, or with strangers from Zanzibar.

Q2) Is it ethical to publish the paper based on my friend's dissertation?  (i mean it is legal, because she will be referencing his phd dissertation but is it ethical to sideshaft the original author)

There are a few different possibilities here:

Your advisor's submission does not report your friend's thesis work as her own, but rather builds on your friend's work in a novel direction.  In this case, your advisor's submission is ethical, but perhaps a bit unfriendly.  After all, the success of her students is a significant component of her upcoming tenure case.
The results in your friend's dissertation are the main topic of your advisor's submission, but your friend did not make a significant and novel contribution, and therefore does not deserve coauthorship.  But in this case, your friend also does not deserve a PhD, and your advisor's signing his thesis was unethical.  This possibility seems highly unlikely; passing a thesis defense generally requires the unanimous approval of the entire thesis committee.
Your friend made a significant and novel contribution, which is the main topic of your advisor's paper.  In this case, your advisor is being grossly unethical.  Fortunately, since your friend's dissertation is easily accessible online (Isn't it?), any competent referee or editor should quickly spot the intellectual theft.  That would just be stupid.

I came to know last week that my advisor wrote the paper herself and got it published.

If you believe that your advisor has stolen credit for another person's work—your friend, her former student, or a stranger from Zanzibar—it would be appropriate for you (or better yet, your friend) to speak discreetly to your department head or another trusted senior faculty member, with both the original dissertation and your advisor's publication in hand, asking them to clarify the ethical boundaries.  Do not accuse; such accusations are very serious, and your advisor's colleagues may react defensively on her behalf.  Instead, explain the delicacy of the situation and ask for guidance.  And then listen.
They may react badly anyway, but then you have your answer.
If they agree that your advisor has acted unethically, get out of the way.  This is not your fight.

Is it common in academia to do this?

No.  I won't claim they never happen, obviously, but serious breaches of ethical behavior, at the level you are accusing, are extremely rare.

Q3 One more question i have is should i be listed as co-author for all papers coming out of this research because i developed the apps that formed basis for this research. I mean the concept for them was not mine but i did program them.

That is a more subtle question.  As a general rule, I would say no.  Of course you deserve credit for your contributions, but only once for each contribution.  If your contribution is a key piece of software, then the first paper that uses that software should describe that software in detail and include you as a coauthor.  If you walk away after that first paper, later work that relies on your software—by your advisor or anyone else—need not list you as a coauthor; you already got credit.  With good reason, Stephen Wolfram is not a coauthor on every paper that uses Mathematica.  You should of course be cited in any paper that uses, builds on, or improves your work, but that's a separate issue from coauthorship.
But reality is rarely so cut and dried.  Is moving the software to a new platform a sufficient contribution?  Optimizing the underlying algorithms?  Adding a new, easy-to-implement feature suggested by your advisor?  Adding a new, hard-to-implement feature suggested by your advisor?  Adding support for a new input device?  I have no idea.  You and your advisor should have agreed in advance on the contribution required for you to be a coauthor.
Normally, if you had not had this conversation already, I would recommend having it now, but it sounds like it may be too late for that.  You may be better off simply walking away and finding a new advisor that you can trust.

well at that time i didn't knew that i could be listed as co author.I am new to research ,so i assumed since i was paid assistantship ,it was my job to develop apps for research .So i never asked my advisor about this .But right now i feel cheated out of my contribution .The research involved 3 different interfaces for an app and figuring out which interface was most convenient and useful for one professional community. Without me programming these apps ,there would have been nothing to do research on.I guess my advisor knew about it but just simply didn't care.

As a further comment on the third question, while it's not expected for a paper using software to name the software author as a co-author, it is very common to expect citation of the paper in which the software was described, and some software packages explicitly state that you should do this in their license agreements.

In physics, no more than a few decades ago, it was quite common for papers that made extensive use of computer simulations to thank the lowly peon who wrote and ran the code in the acknowledgements. Co-authorship is more liberally granted these days, but it's worth being really honest with yourself before claiming that "Without me programming these apps, there would have been nothing to do research on."

@wsc The dissertation research was delayed by 2 months because i couldnt deliver the apps on time as our initial goals were unrealistic. So yes ,the apps were critical to research.

@wsc: Unless you are doing code-by-spec (i.e., you literally shop out a project, with no intersection with the actual research), programming and gathering specs on research projects is research.  Often, picking a specific implementation requires a number of novel leaps.  If grad students are making software for research in-house, they should be listed as co-authors.  Not necessarily high co-authors (it's far lower than formulating research questions and usually writing/analysis), but listed.  It is a novel contribution.

"All publications count toward tenure, whether solo, with colleagues, with current students, with former students, or with strangers from Zanzibar."
Yes, but do they count equally? By publishing as sole author, this advisor might be trying to get all the credit by himself.

@Blaisorblade How they're counted depends on the department, probably.  For a single data point: when an old friend of mine from grad school got a tenure track appointment, he said that he was informed that one single-author paper was worth about twice a multi-author paper when promotion considerations came up.  His intent at the time was to focus on multi-author papers, figuring they could be done at least twice as easily, though I have no idea how reality has panned out for him since then.

@james234 "Without me programming these apps ,there would have been nothing to do research on" That's not an argument for authorship. For example, in an interview study, the interviewees usually don't become co-authors, even though without them there would be nothing to do research on. The question is whether you contributed to the actual research.

I'm not really qualified to assess how other departments would treat single- versus co-authored papers. As for the other points:
[2] It is completely unethical for the advisor to submit a journal article based on work done by a student as solely her own, even if she were entirely responsible for writing the paper. Being a single author implies that the author is responsible for the entire content of the work described, referring to both research and preparation of the manuscript.
[3] Your rights to being credited for this work depend on the nature and scope of the work that you individually did. If you simply built the apps once, and then did no subsequent work on the project, then you are entitled to a paper credit for a work describing the tools and how they were used (in part or in whole). However, unless you have been doing ongoing development on these tools, you would not be entitled to receive authorship credit whenever the work is used. (You would, however, be entitled to a citation on the use of your work in future publications!)