Do non-academic extra curricular activities matter for grad school applications? I just got into a PhD program and was asked to give a presentation to my juniors regarding grad school applications.

In my country (Asia region), people are fanatical about non-academic extra curricular activities that are totally not related to their topic (sports, debate team, run charities etc). E.g. A student with good grades and is the captain of the school's basket ball team can get picked for a mathematics PhD scholarship over the top mathematics student with zero non-academic activities. The belief is that scholars should be "all rounded".

I think the situation is different in the USA. I would like to encourage my juniors who have excellent academic records but without significant non-academic extra curricular activities to try for the USA because of this.

I understand there are scholarships like the Rhodes which do look at non-academic achievements. But is my general understanding of non-academic activities for USA PhD admissions correct?

In general. non-academic activities are not considered for admissions for schools and most fellowship programs in the US. The primary reason for this is that graduate programs are looking for people who will become excellent scholars and researchers (and sometimes even good teachers!). Success in sports and other highly non-academic activities is less likely to have significant influence in assessments of one's ability to do research, and therefore is not strongly considered.

However, there are exceptions. People can choose to fund activities however they choose, and can place whatever restrictions on the use of the money they donate. For instance, an alumnus could fund a fellowship for PhD students who play the tuba in a college marching band. While this doesn't happen often, it can be done. But typically admissions committees aren't concerned with such issues, and don't take them into account in making admissions decisions.


How common is reference/citation padding? I recently discovered a paper of mine (pure mathematics) has been cited by a paper in a very different field (an area of applied mathematics) that I have nothing to do with.  The reference to my paper is used (along with another reference) to justify some statement in the introduction, but I have never studied anything like this (I don't even understand the statement).  It's clear that this citation is wrong, and while it's possible it was an honest mistake and the author was just careless, because the topics of the papers are so different (the titles are completely unrelated) and the journal and publisher are ones I've never heard of, it occurred to me this could be a case of dishonest "citation padding" (randomly adding superfluous citations).

Here are some possible reasons for citation padding:

Trying to legitimize one's work by adding references to reputable papers.
Either directly as part of a citation cartel to say increase impact factors, or as some indirect padding to help prevent a citation cartel from getting caught.  (I don't know if the latter happens, but this is part of my question.)
"Collecting dead souls" (i.e. some other nefarious scheme I haven't thought of)

Question: While I know citation cartels a real issue, is there any evidence that citation padding, outside of superfluous self-citations/citations within a citation cartel/ring, happens in more than just a few isolated cases?  For instance, are there stories of shady journals encouraging this or authors doing this systematically, like there are about citation cartels?

Note: I am not asking for a diagnosis of my specific case, or what I should do, which is discussed in these related questions:

How to react to your work being cited incorrectly or in a misleading way?
Should I do anything if I am cited for something that wasn't in my paper?

Not in my experience, but absence of evidence is not evidence of absence. This might require a genuine literature search using various keywords to give a quantified estimate for particular fields. I read citations quite closely in my field and I have only rarely seen this practice (<1%). Much more common is slightly misrepresenting what the other authors said, or referencing something a reviewer might suspect the author hasn't read, like a tangentially related book used for a brief aside. And, of course, quasi-related self-citations.


High impact journals - Do they always guarantee high quality papers? In academia is common to hear the phrase 'publish or perish' and also that your articles have to be of high quality. So e.g. 4 articles in low impact journals worth as 1 article in a well ranked journal.

But then my questions:

Is it always guaranteed the high quality of your papers if you publish in a high impact journal?
Or there can be the possibility that your (theoretical) high quality papers, published in good journals, are actually low quality?
Is it all about number of citations?

I am new to Academia so please forgive my naivety.
Thanks

No they do not.

That is the short answer. But that is mostly due to the fact that nothing is guaranteed in this world. High impact factor journals are most likely to have a high percentage of high quality articles since rejection rates are high and the editors have the possibility to choose from a large pool of submissions what they deem worthy. In consequence, the editor's opinion about the quality of an article is of significance.

After the editor's decision, reviewers are still able to reject articles. In some journals rejection rates are still as high as 40% after the first review.

You should keep in mind that a high quality, Nobel prize level publication can be published in any journal in its field, but a low quality article might only be published in a low impact journal or be rejected altogether.

TL;DR: On average, high impact journals should have a high density of good publications.

A last note on your last bullet point: A large number of citations certainly shows that an article is significant in its field. A low number of citations could either mean that the article is insignificant or that nobody noticed its significance yet. In the end, that is why you publish in high impact factor journals: You want to get noticed.


What is the median math GRE subject score for admission to a Group 2 or 3 PhD program in applied mathematics? What are the typical (median or maybe third quartile) scores on the math subject GRE for successful applicants to a math program at the PhD level, in applied math, at a Group 2 or Group 31 school?

1This is a ranking system the American Mathematical Society uses for graduate programs. Generally, Group 1 schools are considered the best, while Group 2 and 3 schools tend to be smaller and less prestigious.

This may not exactly answer your question though... Below are "official" statistics for two group-one (?) pure math programs. Note that whether a score is "acceptable" might also depend on whether you are domestic student or not (based on the Ohio State data).

(Since my reputation is too low to add more than two links in an answer, I can't provide more information at present. But I'll definitely update this answer once my reputation grows...)

Ohio State University: http://www.math.osu.edu/graduate/apply

"There are no a-priori minimum scores for the test set by our program. However, admissions become rare below the 50th percentile. The distribution of percentiles of subject test scores of Ph.D.-applicants we admitted between 2009 and 2012 is depicted below.

The data over the four admission cycles includes 125 domestic (in red) and 129 international (in pink) applicants. The median percentile for domestic students is 67, the one for international students is 95."

University of Pennsylvania: http://www.math.upenn.edu/grad/graddata.html

"Scores on the Advanced Math Subject Test of the GRE should be at least 750, though applicants with somewhat lower scores may be admitted if the rest of their application is sufficiently strong. The average GRE scores of the students who entered our Ph.D. program in the recent past were: Verbal: 597; Quantitative: 789; Advanced Math Subject Test: 820."

Edit: More data...

Cornell: http://www.math.cornell.edu/m/Graduate/app_details.html

"Most successful applicants score 700 or above on their GRE subject test."

Georgia Tech: http://www.math.gatech.edu/academics/graduate/faqs-graduate-admissions#MINGRE

"The PhD entering class in Fall 2006 had the following averages: ... Subj 795"

UIUC: http://www.math.illinois.edu/GraduateProgram/apply-phd.html

"Mathematics subject GRE scores of entering Ph.D. students in 2013: upper quartile 850, median 790, and lower quartile 690."

Penn State: http://www.math.psu.edu/grad/phd/faq.php
("Listed below are the average scores of students accepted to our program for the last several years...")


References in supplemental material - include in main reference section? I have some supplemental material that condenses results from a couple of studies in a table (Supplemental Table 1). In the manuscript I refer to my supplemental table. My question is: where should I include the references from Supplemental Table 1? I cannot include them in the main manuscript (right?) as I do not cite these studies in the text and any journal would just list them as references that have not been cited before. I would tend to just list them right under Supplemental Table 1. Is there any correct practise?

It's common practice, however, these might differ between journals.
Likely, when you include them in the main references, they will be flagged as not being mentioned in the manuscript and removed. Unless otherwise instructed in the author guidelines of your journal of choice, simply add them to the supplementary material and see what happens.


Are My Interests More Suited for PhD in CS or Mathematics? So let me give a little info of who I am and what my interests are. I just graduated with a BA in Mathematics, concentrating almost exclusively in pure math courses (favoring analysis, algebra, topology, number theory, and combinatorics over computational/applied classes). Next semester I'm beginning a 2-year masters program in computational mathematics (at a group-1 public school, under old AMS rankings).

My research interests are currently strongest in the following areas:

Combinatorics, especially algorithmic/computational and combinatorial optimization
Cryptography, information encryption/decryption and security
Number theory, but really just for the purposes of encryption/decryption

After doing some research on the Web, it seems to be the case that my interests fall into the field of theoretical computer science and discrete mathematics.

At this point in time, my idea of an ideal career would be a professor of math or CS at a university, probably a doctoral-granting university. I might also consider working for the government in information security, data analysis, etc.

Also, I definitely want a PhD. It's just been one of the constants in my life as a goal.

So, I pose the question. Given the above information, would a PhD in Math be more appropriate, or would a PhD in CS (probably concentrating in Theoretical CS) be more appropriate?

After doing some research on the Web, it seems to be the case that my interests fall into the field of theoretical computer science and discrete mathematics.

Yes, I agree.  Moreover these fields have substantial overlap, and your interests lie safely in this intersecting region.  You could plausibly attend either program, and the post-PHD opportunities and career trajectories would be very similar.

One way to think about the decision is that the differences between a math program and a CS program will be more cultural and incidental.  In a US PhD program there are going to be a lot of required components besides your thesis work.  If you attend a math PhD program you will be required to take courses and pass qualifying exams in areas of mathematics somewhat removed from your stated research interests: e.g. I don't know any math PhD program in which you would not have to take graduate level analysis, including measure theory.  Similarly, in a CS program you're going to have to take coursework and pass exams on non-theoretical, non-cryptographic computer science.  Which of these sets of requirements sounds better to you?

If it's really a coin flip, then I would argue in favor of breadth and diversity of skills.  At a certain point you have to specialize, but all other things being equal, I find basic knowledge more useful: it is so much easier to learn more about something than to get a first, rudimentary clue.  Your undergraduate career gave you training in many theoretical areas of mathematics that are not directly related to your current research interests: great!  Now give yourself the advantage of getting some broad training in CS topics as well.

Anyway, it ought to be clear from this answer that I think there is no bad choice.  Good luck!


Avoid plagiarizing other surveying authors when describing the work of a third I'm currently writing the State of The Art chapter of my thesis.
To my advantage, there are many good surveys in my field. My views are not equal to other surveying authors, so the structure is not the same, nor the way the existing work is addressed. So far so good.

The problem is that eventually, one comes to the part of describing existing work and obviously some papers are so important that they must be present in any Survey of a given field.

I'm specifically worried about situations in which a surveying author AAAA describes the work of a third author like: "Algorithm AWESOME improves performance by statistical methods" and I'm saying something like: "Smith presented AWESOME, which uses statistics to reduce execution times". So, I'm somehow forced to paraphrase author AAAA, because AWESOME does that one thing and that's it.

So the question is: Is this somehow forced paraphrasing of a surveying author plagiarism?

I would just comment, but I can't. Building on ff524's question (in comment) "Are you citing the survey(s) (in addition to the original papers)?", I would simply say "algorithm AWESOME does this and that (AUTHOR OF ALGORITHM OR ANYONE ELSE RELEVANT, 1908; AUTHOR OF THAT GREAT REVIEW YOU THINK READERS SHOULD ALSO READ OR CHECK, 2043)", as "(BURGUER, 1908; FRIES, 2043)" for example (or format it in the same standard you're using). This gives due credit without overcredit nor plagiarism.


Include reference strictly at first occurrence, or in detailed discussion? I'm writing a paper detailing a workflow which makes use of some software tools.

I have a sentence very early on in the introduction, which says something like the following.

  The tools to use include: Tool One, Tool Two, and Tool Three.

At the moment, this is where the references to the respective papers are, like the following.

  The tools to use include: Tool One (Lorem, 2014), Tool Two (Ipsum, 2011), and Tool Three (Ipsum et al., 2015).

Each tool has "its own" section in the paper, where it is discussed in detail. I've a gut feeling that it'd make more sense to include the reference there, although I think that including the reference where the respective tool is first mentioned is the "correct" thing to do.

The editors don't give any preferences, and I think that something like this is assumed to be common knowledge (which unfortunately I don't seem to have).

Is there a documented "best practice" for when a reference needs to be included, i.e., whether it should rigorously follow the first occurrence of the referenced?

The domain is CS/linguistics, in case there are some specific practices I'm not aware of...

The best thing to do is probably to reference them in both locations.

Reference upon first mentioning is a standard convention, which helps your reader because it makes it clear that the term references something that previously exists, not something that you are introducing in this paper.
When you discuss again after a significant gap, you should cite the paper again, as discussed in this question.


What do reviewers mean by "broad readership" when rejecting paper? Our paper was rejected multiple times; several months later, another group published similar results in Nature. Though some details were different, the main logic and key points of the research were the same.

A reviewer of our paper said our work lacked "broad readership" - this critique does not make sense to me. Is this because there are no "big guys" in our paper? Or our figures were not enough to impress the editors? Or because our university is not famous enough?

Though I haven't seen this language used, if it was the editor saying "broad leadership" rather than a reviewer, I suspect what they mean is that they did not feel your paper was sufficiently revolutionary for their tier of journal. The editor would likely base this decision on lukewarm reviews, even if those reviews are not fully negative.

Your options in this situation would be to

A) publish in a lower-tier journal, to make sure your work takes precedence in the field even if it lacks some exposure, or

B) better emphasize the novel aspects of your work in a future submission.

I also like the suggestion by @Ian_Fin that "leadership" may have been a typo from "readership" which I think would make much more sense, but my conclusions and interpretation are the same: this is the editor saying your work is not sufficiently groundbreaking for the tier of journal and either belongs in a more specialty journal or you would have needed to improve the writing to clarify the significance to the broader community.


Are we focusing too much on cheating with online courses? Recently, the online calculus class I TA for took their first test of the semester and the grades were horrific. Granted, this is my first semester as a TA so my expectations might have been high. However, the average was about a 50%. While the overall stress of the pandemic is definitely a factor, I also believe the structure of the exam played a significant role.
To prevent rampant cheating, students were given fifty minutes to take the exam but were not able to scroll through questions. That is, students could not look further ahead to see what questions were coming, nor could they revisit questions to change their answer. Does this seem a bit much to anyone else? Is worrying too much about cheating on tests, especially now, counterproductive? I mean, what if this semester's grades are inflated? It's only going to negatively affect the students who passed the class without deserving it as they progress through higher-level math classes.
Ultimately, I'm just a little discouraged as it seems we're more focused on gatekeeping grades instead of instilling knowledge.

The testing situation you describe sounds like a multifactor problem with multiple possible solutions. It could be that a concern for cheating is the key concern here, but logically speaking, there are several distinct factors that could play a role. Someone can be concerned about cheating and still create a fair test. From an instructional design perspective, I'll name the most important factors I see and then list a few possible solutions.
Raw Difficulty / Learning Objectives
A math test can be easier or harder depending on what the instructor asks students to do, how much work they should show, and so on. For instance, compare solving an equation for x or finding the derivative of f(x) to interpreting a word problem, or solving a fairly simple equation with a more complex one. Compare working with separate questions with sequential questions that build off of the previous question's answer. The selection of these problems is often guided by an instructor's implicit or explicit learning objectives for a unit.
Time to Complete Test
In test design, instructors need to be very careful that students have enough time to give a fair attempt to each problem. Instructors can develop different rules of thumb. Some base completion time on how long it takes them to complete the test multiplied by a factor of two, three, or four. Others estimate the time for completing each problem and sum up a goal time, which might come out to 40 or 45 minutes.
Test Format
As you point out, many instructors don't account for how test format determines timing. In a paper test, a viable test strategy is to read the entire test and focus on easy problems first. In contrast, the testing systems in many Learning Management Systems either make scrolling through the test difficult or restrict movement between problems. So if a student is stuck on problem 3 of 9 and spends 15+ minutes on that one, they have no way of knowing when it's better to cut and run to an easier problem for them. Thus a test that might take 40 minutes for a student on paper would actually take closer to an hour.
Concern for Cheating
So the concern for cheating is a factor that affects how the instructor has implemented these other factors. You describe the time limit and test format as factors affected by a concern for cheating. In particular, students may have less time to share answers or look up information. Yet there are also other anti-cheating formats used. For instance, some professors have proctored exams, even online, which involve some kind of visual monitoring.

There are more factors, but what's to be done? You can toggle any one of these factors in order to increase the pass rate:

Have fewer problems, or easier ones. In other words, adjust the total difficulty of the test so that students can complete it in the allotted time.

Make the test time longer. Giving an hour rather than 50 minutes, for example, may have enabled more students to complete problems.

Allow students to see the whole test when they start. That will let students prioritize the problems they know how to solve, rather than being at the whim of the instructor's own design or an RNG algorithm (if order is randomized).

Worry less about cheating. This may mean adjusting any of the factors above, or it may mean rethinking the format itself. Think critically about whether your summative assessment needs to be a test, or whether it could be a project, homework, or something else.

Finally, any instructor who has been in the classroom for some time knows that they assign unbalanced assessments sometimes. It happens. If the end result is an average of 50%, an instructor has other options to mitigate the effects of unbalanced assessment on student outcomes, like grade curves. So whether or not the concern about cheating - or some other factor - produced a test that was difficult for students to complete, instructors have several tools for adjusting future tests and even addressing this current situation.


Should I do exercises given in online course and accompanying textbook if I want to do research in machine learning ahead? I'm a junior year computer science undergrad just began to study machine learning a month ago. My aim is to start reading papers in my area of interest under Machine Learning and begin to do research in ML as an intern/independent project. I want to further go to grad school after a gap year and earn an MS + Ph.D. in machine learning.

I'm taking Prof. Andrew Ng's CS229 lectures online and side by side reading relevant chapters from Bishop's "Pattern Recognition and Machine Learning" book.

The mathematical problems/exercises given in both the problem sets of CS229 and PRML textbook are mathematically too sophisticated for me to solve on my own, although I can follow the solutions. How much of these exercises would an undergrad/masters student be expected to solve? And if I am considering a Ph.D., should I solve them or skip them at all?

Will only the mathematical knowledge and implementation of machine learning algorithms matter to start with research and later in grad school without spending time on these exercises?

Actually, most people require practice and reinforcement to learn much of anything. Reading and seeing isn't enough to get more that a superficial "acquaintance" with anything. Especially any thing complex.

So, yes, you should do the exercises. Following along with the given solutions isn't the same as actually doing them.

But, success won't come immediately, nor easily, if the topic is deep. You can also look for simpler exercises in a field if the ones you have elude you. But practice is essential for nearly everyone. The exceptions are very rare.

Also, you need some feedback on your solutions and this is very difficult to get in a purely online course. Look for local resources to find someone who can look at the work you do and comment on it. It is possible to develop bad habits if you don't get suitable feedback. Eventually you may be able to work through those habits to better ones, but the path will be longer.


Is it reasonable to say I'm not happy at my current position at interviews? I am working as a research fellow at a University in UK. Its a two year contract with no chance of extension or renewal. Although I have 1 year left, I have considered not staying for the second year, and I have started applying for jobs elsewhere. I have been called for an interview at another much higher ranking university.

They will most probably ask why I am leaving my current position. And I don't know how best to answer this, as I don't want to say too much at this stage.

The University I am currently employed at is not purely research targeted, so along with our research targets we are given modules to teach along with assignment/exam checking. This takes a lot of time from my research.

Also I am personally not satisfied with the quality of my work here as I have been told quantity over quality and I am producing subpar papers at least once a month and even after discussing with my PI to target better journals he still expects me to continue working and printing out papers, some of the papers that I have produced are so bad in such low ranking conferences/journals that I am ashamed to add them to my CV.

Also as mentioned above, this project has no chance of extension, but is this a valid reason? Would this not alarm my new employers that this guy might leave us as well as the project comes to an end?

The place I have applied for is known for its research excellence. And I really want to move there. So, based on the above reasons how should I answer this question.

Also I am not ashamed in admitting that I am very nervous as I am really hoping to get this job. I don't know what to expect at the interview and how to prepare for it. I have found out the name of the PI and have read his previous published work. Is there anything else I can do that would improve my chances of succeeding at the interview?

I have also read this answer, and was wondering if anything else can be added to this.

Thank you.

A traditional interview technique is to reframe such questions.  Don't focus on the fact that your current job is bad - view it as an opportunity to discuss how the new job will be better and how you're a good fit for it.

Bad: "In my current job, I have to teach too much, and good research is not appreciated."

Good: "I'm looking for a job with more opportunities to pursue research, in areas where I can make the best contribution.  I have successful experience in doing X, Y, and Z, and University A is known for its excellence in this area."


Coadvisor assigning seemingly superfluous tasks Context: I am a fourth-year graduate student in mathematics at a university in the US.

One of my colleagues in applied mathematics has two advisors, one in mathematics and one in chemistry.  He's trying to graduate this semester, and he (understandably) wants to devote the majority of his time to writing his thesis, applying to jobs, etc.

Unfortunately, his chemistry advisor seems to be taking advantage of him.  She is continuously asking that he perform all sorts of calculations for her that have nothing to do with his research.  These calculations are not particularly difficult, they just happen to be beyond the mathematical capability of his advisor.  He suspects that she does not consider them important enough that she would do them herself in the case that she could.

As he still needs her to serve as a reference, he is somewhat limited in how he can handle this situation.  His past attempts to refuse or delay working on these "projects" have usually been met with significant resistance.  Any suggestions for how he might proceed are much appreciated.

These calculations are not particularly difficult

If this is true, make this calculation more efficient by, for instance, writing a program or software macro to handle them. When the supervisor asks again, give a due date that is longer than the time he actually needs to do that task. For instance, it takes 1 hour, and after automation it'd take 15 minutes. Tell her 1.5 to 2.0 hours. The earlier stage they are in, the more he can over-estimate the required time to get some breathing room for other tasks pertinent to his study.

He can also consider teaching other people of her lab or team to do the calculation. Make a brief instruction presentation and teach all of them to do it. She may be less likely to call on him again.

The way I dealt with mine may not be the ideal for him: I usually just do the tasks even it may mean some of my research time is reduced. For instance, I spent time writing proposal, making and checking others' presentations and abstracts, training graduate students, etc. just to help my supervisor. For i) if my supervisor is not stressed, our lives are easier, and ii) after looking at my supervisor's overall workload, I just couldn't help but wanted to help. I wanted to aspire to be a graduate student who can take care of own's stuff and with some leftover effort to help. And till now I am still glad that I did.


Correcting grammatical errors versus content in post-graduate coursework submissions in the sciences During an intramural teaching forum, I was interested to learn from a Head of Department (HoD) that she didn't consider it her role to correct grammatical errors when evaluating coursework submissions (an essay, say) at the post-graduate level and that she limited her assessments to the content of the essay. I'm an HoD myself and am directly opposed to this, and have strongly recommended to academic staff in my department that the assessment of grammar should be part of the feedback provided to students. My reasons for this are:

Communications with peers, the public and policy makers are important aspects of the role.
While a number of our students are non-native English language speakers, there are a number of so-called native English language speakers with atrocious writing skills.
The students appreciate the feedback they receive and we can detect a substantial improvement in their writing skills.

The other HoD's reasons are equally cogent:

The university already has a minimum language level required for entry.
This additional task would impose a heavy burden on her already limited staffing resources.
Students need only be made aware that there are errors and can seek guidance on correcting the grammatical issues elsewhere.

This is my question to you good folks:

  For teachers, what is the practice in your department and is this practice backed by specific assessment policies?
  For students, what are your expectations about your grammar being corrected?

EDIT: I am interested in approaches from STEM fields, primarily. As @DanRomik points out in the comments, the approach in the humanities and arts may be different.

To put this in perspective, here is part of a report submitted in partial fulfillment of a basic statistics course at the Master's level that I am grading at the moment. The statistical formulae, graphs and numerical results are spot on.

  This report uses te data from the study of [redacted] about lizard to do some analysis. Graph 1 shows the survival status of lizard. The value of survival lizard are higher than that of the death lizard.

How would you approach such a submission?

Thank you for your patience.

PS. I have found the related thread here but it focused on peer-review. Nevertheless, I accept that some grammatical errors are so egregious as to make the submission unintelligible. I am not concerned about those submissions here.

I am somewhere in between physics and mathematics. My personal policy is this:

I mark any spelling, punctuation, or grammar mistake I find, but I do not explicitly search for them. However, I usually do not go at lengths to explain why something is wrong.
This does not affect the grade unless the number of mistakes severely affects the readability of the text or is particularly egregious. (Being in Germany, I may be more lenient on submissions in German by non-native speakers, depending on the programme’s main language and other factors.)

My rationale for this is:

As I have to thoroughly read the text anyway, the additional effort for marking mistakes are negligible in comparison to the reading time. In most of the cases, it’s adding a comma, crossing out a letter, or replacing a single word. This applies to analogue submissions as well as to digital ones.
Just telling students that they made language mistakes somewhere in their writings does not really help them. The effort of seeking help from a third party is unfeasible in most situations (and disproportionate in comparison to my effort). However, I expect that they are able to find out the source of a specific mistake that I marked.
The admission requirements should not and cannot be so strict that only people who completely mastered the language can be admitted. In many languages, even native speakers tend to commit some systematic spelling mistakes (in particular regarding punctuation) that can only be weeded out this way.

So in short, I think that the other HoD’s rationale is blatantly misjudging factors.

We do not have any departmental policies regarding this here, but I know many that follow a similar policy.


Effect of project coordination task on academic profile I'm soon handing in my PhD thesis, and have funding for at least a one year Post Doc position at the same institute. In my post doc I'll be working on research related, but not directly associated, with my PhD field of work.

My phd has been funded by a huge 'umbrella' project involving both academic and industry institutions, and domain specific partners. My Phd supervisor is also the project leader on this big project. The project has quite a distinct profile and has attracted a fair amount of public attention.

So...moving on to my dilemma.

Yesterday my supervisor phoned me up, and asked me if I was interested in taking over a part time position as project coordinator for this big project as the current coordinator is moving on to another job. According to him, some of the administrative tasks would be transferred to other project members, but I was offered to manage a lot of the collaboration with project partners and, I'm guessing, play an important role in the final reporting when the project finishes.

I'm uncertain to what extent taking on such a role would affect a potential academic career. Would it be beneficial in the long run to acquire experience in managing projects, or would it look more like I was 'degraded' to a secretary-'like' role?

As far as I understand, both my supervisor, and our institute director, would like me to assume the role. I guess this both gives me some leverage...but also puts me in a potential pinned down situation if I decline.

Their estimate is that the project coordination tasks would take up roughly 25% of my time. So there would still be time to do research.

In the comments above, I asked whether OP had any experience performing project coordination tasks similar to that of the position under consideration. OP's reply:

  Yes, I have five years of experience from industry, not directly as a
  project manager, but as a product manager. So it would be within my
  current skillset.

You have obtained one answer here which emphasizes the benefits of gaining this sort of experience. However, it doesn't sound like that answer is applicable to you (though, you would probably know better than us whether this experience would truly be worth it, or if you would just end up doing stuff you already know how to do).

Let's review where you are, at this critical stage in your career:

You are just now wrapping up your PhD.
You are getting ready to start a transitional postdoc.
You seem to be interested in pursuing an academic career.
You have already gained project management/coordination experience from working in industry.

To my mind, all of the above points to one conclusion:

You telling your PI/institute director "no, thanks."

Instead of taking on the coordination tasks, I recommend that you use all of your time in "postdoc mode" working on the things that will strengthen your research profile: producing high-quality research output, finishing up manuscripts, defining your research agenda, growing your network of collaborators, etc.

When you begin to apply for academic jobs at the next level, or for other postdoc positions after the transitional one ends, you will already be able to play up your ability to coordinate complex projects. So, I don't really see the benefits of playing the project coordinator role right now. The downside of taking that coordinator role on, however, is the main concern: I think it would interfere too much with all of the other important things you should be focusing on at this critical stage of your career.

(And, let's face it, spending 25% of your time on project coordination tasks for a large project, with lots of moving parts, is probably a very conservative estimate.)


Postdoc in China. Looking on advice about culture shock and pursuing a career in industry So I was recently offered a math postdoc position in China for 2 years. A bit of additional background:

I am a US citizen and have never left the US; I've hardly left my home state (except for grad school).
I intend to go into industry. It's been a good several months since I graduated with my PhD and I am getting wary that my resume is becoming more and more stale as time passes.

I had a few questions for those who know better than me:

Given that I've never left the US, how big of a culture shock with this be? The postdoc is in Shenzhen, so I'm told that it's a pretty international city. I am just concerned with coming home for Christmas and having enough time to visit my family during vacations (as I did when I was a grad student). How different would this be from working at a US university?
Given that I'm planning to spend at least part of my time on buffing up my resume for industry (particularly data science and software engineering), what does a PhD from a top US school and a postdoc at a Chinese university look like to employers (I know this is the academia stackexchange, but I just wanted to fish for some advice on this).
Lastly, do you think my plan is doable? Do you think that I will have enough free time to work on industry skills, conduct small math research projects and fulfill my postdoc responsibilities?

Some clarifications:

I have not been successful in finding an industry job; hence, my plan to pursue the post-doc so I can pay the bills while I gain some industry-relevant skills
There are no other international post-docs at this school, hence I cannot ask them about their experiences

As someone from England who did postdocs in Thailand (for 4 years) and then taught in high schools in Shanghai (for 3 years), not so recent, but within the last ten years:
Working conditions depend a lot on the people you happen to be around, and Shenzhen is not Shanghai (although in terms of "internationalisation", they are similar), but based on my experience (the following was all TRUE for me, although everyone's experience is different):
Another factor which is sadly crucial but you haven't mentioned, is your ethnicity. If you are white then people will stare at you and you will be a target for rip off/con artists/people trying to sell you junk everywhere you go. The violent crime rate is zero (although, there are pickpockets; and the official train ticket seller in a railway station tried to overcharge me once), but you will have to have your guard up at all times.
If you have darker skin then you might have a hard time. I have heard Chinese friends say things about Africans and non-Chinese Asians which would be unbelievably racist in most western countries. However, I don't know what practical differences in behaviour/treatment might arise from this.
If you look Chinese then people will assume that you are, which means you will get pushed around more on crowded public transport, etc.
(I myself am white, but my Korean-American friend was always complaining about being shoved around on the trains, even more than me - this is just how people behave towards each other in China, and queuing is nonexistent).
Culture shock: You will find it hard to buy certain basic things you are used to in the US (although you will not know which until you are there). You will find that many products are of much lower quality than in the US, that you cannot obtain higher quality products at all.
You will also find a lot of people hawking up phlegm and spitting on the street, dropping litter, and smoking indoors (even in restaurants, even where there are non smoking signs).
Food: someone on the street tried to sell a live hedgehog to me to eat. Even in large supermarkets you will find live frogs and very strange animal meat on sale. If you do not eat such things, you will find it surprisingly hard to find restaurants which sell edible food (I don't regard KFC or McDonald's as edible either). Some people in the comments think this is an exaggeration. I have seen dog carcasses hanging outside restaurants in Shenzhen. OK, I suppose you are not likely to get served something like this accidentally, but that doesn't mean it's not there and cooked in the same kitchen, with questionable hygiene standards (food inspectors are routinely bribed). China is notoriously bad for animal rights. Remember also the poisoned baby milk powder scandal ten years ago.
Language barrier: Very few signs will be in English (let alone people who speak English). For getting on buses etc., you really should have your address or road name written down IN CHINESE CHARACTERS to check. (By English I really mean "Roman script" - if something is written in Polish or Swedish, or some other European language I don't know, at least I can read, copy and memorise things. This is also a problem in Thailand of course, although at least Thai is alphabetic).
Working conditions: make sure EVERYTHING is written down and agreed in GREAT detail. You should expect your employers to lie and cheat about everything. Do not expect any reasonable behaviour or holidays from them. Maybe you will be pleasantly surprised, but plan for the worst. "We missed Monday due to a public holiday, so therefore we will all work on Saturday". One time, both Monday AND Tuesday were Chinese public holidays, so we had to work over Saturday and Sunday (and still work the following Monday - Friday as normal). So, we were forced to work 10 days in a row!
Prices: China is nowhere near as cheap as Thailand, say, nowadays. A good meal in a restaurant will cost you >10 US dollars, easily, unless you are willing to eat strange and/or low quality food. China is fine for buying cheap, low quality junk, but even expensive products will still be low quality, you just cannot escape it. (E.g., I have had DVD players, washing machines, etc. break down within a few months).
"International" cities: absolute nonsense. People say the same about Shanghai, and it is not international at all. All the ways in which it is "international" are very superficial. Nowhere in mainland China is "international" in the proper sense of the word. Only Hong Kong is international (although I don't know about Macau).
Money/exchange: you will find it very easy to change US dollars to yuan, but very hard (within China) to go the other way when you finally leave (and international bank transfers will be very hard). China discourages you from taking foreign currency out of the country. (Yes, even staff in the Bank of China will blatantly lie and pretend not to have foreign money). For cash exchange, by far the best option is to go to Hong Kong. You will have to pay for almost everything in cash.
Freedom/internet: yes, China really does spy on you, block websites, block Hong Kong TV news broadcasts, etc. etc. You need to show your ID at internet cafes, to buy petrol for cars/motorbikes, to buy long distance bus/train tickets, etc. etc. When you first arrive, someone from your apartment building will speak to you and be very friendly. That is the communist party representative who lives in your neighbourhood (EVERY neighbourhood has at least one, who reports back everything they see, especially regarding foreigners). There really are undercover spies everywhere watching you and reporting back to the Communist party.
General evilness/legal problems: if relations go bad between you and your employer, do not expect any kind of fair treatment. They might, e.g., collude with your apartment owner to have you thrown out or overcharged; they might forge documents and try to charge you money for false compensation/refuse to pay salaries owed, etc. etc. Even though the law theoretically protects you, in practice very few people will help you (and even if you take them on and win, you will not be compensated the amount you deserve). Always have your passport handy and be prepared to run if things start to go badly downhill.
At least you are not actually at risk of imprisonment unless you do something really bad.
Shenzhen does have one advantage, that you can easily go to Hong Kong for brief escapes (unless the border is closed due to Covid etc.); if you are working in Shenzhen then you will get a multientry Chinese visa, and Hong Kong I believe allows US passport holders to enter frequently for short tourist visits without fuss.
Shenzhen is newer and less polluted than Shanghai, although it still seems about the same as London to me, which I think of as quite polluted. To be fair, I think Shenzhen is the nicest large Chinese city I've been to (and I have been to quite a few), although there is no history (unlike Guangzhou, Shanghai, Beijing and even Hong Kong).
Make sure you are not the only foreigner who works there! At least they will have dedicated staff members who will help you to find an apartment, get visas/work permits/etc. etc., because they know that most of these are basically impossible if you don't speak Chinese.
Health: they WILL test for diseases like HIV, Hepatitis, Tuberculosis, etc. etc. I don't know where to find the full list of diseases, but if you have anything like this, you might find yourself stuck in China abandoned by your employer (with hefty medical bills) if you fail the medical test. Also, doctors in China are NOT TRUSTWORTHY; some WILL overcharge, recommend dubious or unnecessary treatment, etc. (Of course this may also be true in other countries). Also, what actually will happen if you catch Covid-19 or some other disease? Make sure you ask in advance and have it written into the contract what they will do in this case.


Is there such thing as "paper dump conference"? If yes, what actually is it? A couple of weeks ago, out of the ordinary, I was in the company of a few academics from respectable universities. A graduate student mentioned that he was invited to something called "ICIT 2015" to present his Master's thesis. One of those professors said something along the line of:

  If it is your first attempt at publishing something, then go for it. However, I usually highly advise against attending such events to present your papers. They're nothing but paper dumps. Within the time frame of two days, nearly 1500 people are expected to present their papers. You're given 10-20 minutes present your work to 1-2 people and have your picture taken. These events are merely created just so you can say and put on your CV that you've spoken at a conference and published a paper. Most of the time, the review process is horrible, and the PhD-level papers can be barely accepted as Bachelor-level theses in any respectable university.

Immediately after he finished talking, two other professors agreed with him and shared a couple of anecdotes on that particular conference and another one.

I looked at the conference's website, and it seems to confirm some of what the professor had said, but I cannot find anything on the review process or the "quality" of the papers.

I spent quite a bit of time trying to find any reference to such "paper dump conferences", but I had no success. Were those people just being snobs or is there some truth to what they said?

Disclaimer: I'm very far from academia and just looking to learn more and understand this a little better, so excuse me if it seems like I have no clue what I'm talking about. Also, this "paper dump" might have another name in English as I'm providing a direct translation from another language.

I think there are two different but related kinds of conferences.

First are the conferences which are essentially bogus and shady. They do exist and run but the associations and quality they claim is fake. These are borderline fraud conferences but hard to prove so because they will come up with some bare minimum genuine-ness criteria if called out. People I know usually avoid them and their CFPs go to spam mail.

Second are the conferences which are genuine but fairly low on popularity and quality. Such conferences are often easy targets if you want to get something out in some catalog and want a speaking experience. As an anecdote, my professors used to call these second type of conferences the "paper dump" venues.


How do employers verify academic transcripts? Employers often ask job candidates for their transcripts (official or unofficial). How can employers truly verify that what you have submitted is in fact real? Will they send your transcript to the university for them to verify?

It seems to me that the only way to verify academic records would be to send the copy of the transcript they submitted to the university for verification.

This can be done in any number of ways depending on the country and the employer:

The employer might tell you to get the university to mail them a sealed envelope with the transcript
The employer might ask you to grant them guest/view access to your online student records (depending on the Student Information System at your university)
The employer might ask you to send an electronically verified copy of the transcript (through a service like the National Student Clearinghouse in the U.S.)
The employer might call the university and ask them to confirm particular information (e.g. the GPA and a couple of randomly selected grades -- this was what my former employer did)
The employer might mail a copy of the transcript to the university as you suggested

In short, unless you know an employer's procedures, assume that they will find some way of verifying the information, either directly or with your help. Not complying with a request to verify the transcript after securing an offer (when a decent chunk of money is on the line) would look extremely suspicious and be grounds for withdrawing the offer in most jurisdictions.


Tips for introducing a speaker I will introduce a well-known speaker who will give a lecture in his work in neurobiology in front of a large student audience. What is a good introduction and followup?

I have noticed people often give what I consider trivialities like the year he received his PhD degree and spend a long time listing their awards. I am planning to talk about his recent papers briefly, his areas of research, and just briefly mention his position now and who he worked with as a postdoc.

I would appreciate any input, particularly from profs on how they like to be introduced.

The long and boring introductions that you've noticed are probably due to people simply reading off the "speaker biography" paragraph that is typically included with a talk announcement.  That, in turn, is usually prepared with little thought by the speaker, often by grabbing a recent bio blurb from a proposal or their website.  Thus: boring list of dates and awards.

My personal preference is to ask the speaker how they would like to be introduced and to keep things quite short: any good speaker will begin their talk with a high-level perspective on their technical vision and work in any case.


How realistic it is to change to a different field of mathematics after PhD? Once I was told that in mathematics, after one gets a PhD, it is very hard to change one's field of specialization (within maths). Is this true? What are the reasons? How common are counterexamples?

In your answers please also specify what country are you talking about, if you believe it matters.

I think it's quite misleading to hold up examples of very talented mathematicians or mathematicians from the distant past.  The answer depends heavily on the field you want to switch into, hold closely related it is to the field you wrote your dissertation in, and how talented and hard-working you are.

In the most classical, long-established subfields of mathematics, there is a large amount of background one needs to learn to be able to do significant, original research.  To take the worst example I know, a graduate student who wants to work in the general area of the Langlands program needs about 18 months to 2 years of dedicated study after their second year graduate courses to get to the point where they can tackle some problem of interest to the research community, and this is with an advisor to guide their study and steer them away from pitfalls that would result from having an incomplete knowledge of the field.  (In particular, this means the graduate student likely still has some blind spots in their knowledge that would greatly slow down their research if they didn't have an advisor.)

A graduate student doesn't only have the advantage of an advisor; he or she also has a good deal more time.  Most postdocs and almost all professors have more teaching responsibilities than graduate students, and professors also have service responsibilities which increase as one gets older.  Furthermore, one also has to do enough research to write somewhere between one and two reasonably significant papers a year (depending on subfield) in order to be competitive for jobs that allow time for research and eventually to earn tenure in such a job.  If one wants to switch into a new field, then one presumably has to do this research in their old field while learning the new field.

If someone in representation theory or algebraic geometry or other parts of number theory wants to switch to working on Langlands, then he or she needs to learn the material in one second year graduate course (because they already studied the other two or three that a complete beginner needs) and another 18 months of specialized study.  It's true that some patterns of thought will be familiar, even if the specific ideas are different, so one is going to learn somewhat faster when one learns their second field, but moving into a new field still requires at least a year of dedicated study unless someone is an unusually fast learner or extraordinarily hard working.  Most people don't have the time and energy to fit an extra year of work above their other duties within any reasonable timeframe.  Fifty years ago, one could have given up a couple years of paper-writing to accomplish the switch, but someone trying that today would never get another job that allows significant time for research in today's far more competitive job market.

Most areas of research don't require as much background as Langlands, but unless one is moving into an essentially brand new field requiring minimal background, switching fields requires a substantial amount of time that one simply rarely has after obtaining a PhD.

Lack of an advisor can be an issue, but it is less likely to be one than lack of time.  Many fields do have a significant amount of "folklore" that is well-known to experts but not clearly stated in print anywhere.  These are usually ideas that are too advanced and specialized to appear in a graduate textbook, but at the same time too easy to be the subject of a research paper.  At some point this folklore is used to establish more significant results in a paper, but since "everyone" knows it, it might not be explained very clearly or be easily found by someone who needs it for some other purpose.  However, most fields have experts who are quite friendly and willing to explain the necessary folklore to new entrants to the field, and, at worst, one does things in a clumsy way in his or her first papers in a new field and has some folklore pointed out by a referee.  If one appears talented and capable, then it is not so hard to get some help.
Researchers in countries not connected to the international mathematical community (such as in Africa) generally face much more significant problems with having access to experts than people trying to switch fields.

Is it possible?  Yes, but it's very hard.


In a faculty job search, when and how should I reveal my preferences? I am currently interviewing for tenure-track faculty positions at a number of top departments in my field.  Despite getting some very positive feedback about my interviews, I have not yet received any offers.  So far I have tried to avoid any "game playing," being very explicit with each department about where and when I am interviewing.  Likewise, in follow-up discussions with hosts, I have been careful not to state any strong preferences for one school or another, mentioning that I still have additional places to visit (seems only fair!).  I am starting to wonder, however, whether this approach was a mistake, especially given that others in my field are already receiving offers.

The question is, how should I proceed from here?  Part of the issue is that I do not fully understand how and when offers are made, which leads to several questions:

Question 1: How often are offers made before the end of the interview period (i.e., before all candidates have been interviewed)?

I know it happens, of course, but how frequently?  (E.g., as a percentage of all offers made by the department over a 10-year period.)  A related question is

Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?

In fact, can expressing this kind of preference actually hurt a candidate's chances?  E.g., perhaps it makes this candidate look like a "sure thing," which frees the department to first make an offer to another, "higher-risk" candidate.  In general, when is a good time to express such a preference?  Finally,

Question 3: To what extent do different departments talk to each-other?

For instance, is there any mechanism in place to prevent candidates from "falling through the cracks?"  E.g., one can easily imagine a situation in which lower-ranked schools don't make a candidate an offer because they expect she will get an offer from a higher-ranked school; subsequently, the higher-ranked schools make her no offer and she is left without a job.  Likewise, if I express a preference for school X before visiting school Y, do I risk pissing off my hosts at Y?

Question 4: Do I just need to relax?

I am almost tempted to write an email CC'ing all the department chairs, providing a complete ordering of my preferences... they can duke it out from there.  (Or simply tell me that none of them want to hire me!)  In general, the whole game-theoretic aspect of this thing makes me a bit queasy.  Wish some brilliant economist would design a mechanism that is fair for both departments and candidates alike.  Right now, it definitely feels like a buyer's market.

I've served several years on the faculty recruiting committee for my (US, top 10) computer science department, including three years as the chair.  Protocols vary significantly between different departments, different searches, and especially different fields, so take my experience as a sample, not as a definitive answer.

Faculty hiring is best thought of as a complex multi-player game of three-dimensional chess, using invisible pieces that occasionally explode, where nobody knows who the other players are or what rules they play by, and nobody wants to reveal too much information.

  Question 1: How often are offers made before the end of the interview period (i.e., before all candidates have been interviewed)?

It happens, but normally only when one of the early candidates emerges as an overwhelming favorite, and that candidate has another offer with an inflexible (or already extended) deadline.  But nobody wants to be forced into this situation.  It's really bad form to interview someone for a position that doesn't exist.

Some universities allow limited gambling with slots.  A department might offer a position to candidate A, and then later make a second offer to candidate B for the same slot, under the assumption that at least one of them is likely to say no.  If A and B both say yes, then both A and B get jobs.  (I've seen this strategy go very "badly", with four low-probability offers made on the same slot, all of which were accepted.  Gambling was outlawed for the next n years.)

  Question 2: If a candidate expresses that a school is her top choice, does it make any difference to the hiring committee?

Especially at universities that (a) forbid gambling and (b) do not let departments roll unused slots from one year to the next, departments do balance the desirability of various candidates against the estimated probability that they will accept an offer, to minimize the risk of not hiring anyone at all.  (This scenario also tends to generate offers with very short and inflexible fuses, sometimes while interviews are still ongoing.)

But just telling us that we are your first choice probably won't help much.  We want to believe you, and we appreciate your effort in making that overture, but we don't really believe you, because lots of candidates have said that and then left us at the altar.  And even if it's true, you really don't want the rumor that that you prefer us to reach someone else.  Best to keep mum until you have actual offers.

On the other hand, evidence that we are your first choice is taken very seriously.   For example, if you receive an offer from somewhere else, especially from another top department, telling us in time to make a good-faith counter-offer is certainly better than not telling us until it's too late.

  In fact, can expressing this kind of preference actually hurt a candidate's chances?

No.

  Question 3: To what extent do different departments talk to each-other?

Not at all.  Different departments are competitors; sharing information is counterproductive.

We do, however, gather as much back-channel information as we can, for example by scouring our competitors' web pages to see who they are interviewing and when.   Sometimes I do hear rumors of the form "So-and-so is about to get an offer from X", but those rumors almost always trace back to the candidates themselves.

  one can easily imagine a situation in which lower-ranked schools don't make a candidate an offer because they expect she will get an offer from a higher-ranked school

Unfortunately, yes, this does happen, although I suspect more often at the interview stage than the offer stage.  See "minimize the risk of not hiring anyone at all".  Nothing you can do about it.  Let it go.

  Question 4: Do I just need to relax?

Yes, always.  I recommend building up an immunity to iocaine powder.


Becoming a professor at a liberal arts college with H1B visa I am an international student on an F-1 visa in the United States and planning to pursue a PhD in mathematics. I've been looking into career options after graduation, and lots of people from my current undergraduate program who have gone on to complete PhD's (especially in pure math) have become professors at liberal arts colleges after graduation, with fewer of them doing postdocs or becoming R1/R2 university professors.
Considering my visa situation, would it be possible to become a professor in the future at a liberal arts college? Do they sponsor H1B visas or is this very uncommon? Could you work as a professor at a liberal arts college on an OPT or extended OPT?

H1B visas in the United States are intended for specialty workers and are appropriate for individuals with PhDs using those skills to teach students. H1B visas are awarded through a lottery system. Fortunately, non-profit organizations, including universities, are exempt from this lottery and can obtain H1B visas much easier. This visa is the most typical visa for someone in your situation. Reputable US institutions interested in hiring you should be willing to and have the infrastructure to apply for an H1B on your behalf. H1B visas are valid for 3 years and may be extended for an additional 3 years for a total of 6 years.
Optional practical training (OPT) following an F1 visa is required to be directly related to the student's area of study. Teaching in the field of your PhD would fulfill this requirement. As an individual in a STEM field, you would be eligible for a STEM OPT extension for up to a total of 24 months. A benefit of this approach is that the application cost is lower ($410 versus up to $4500 at the time of this answer not including legal fees). Your employer may file a petition on your behalf to change status from F1 OPT to H1B.
Beware of J1 visas, as they are intended for "exchange visitors". These visas typically trigger a two year home country physical presence requirement after completion of your stay before you are again able to apply for other visas including H1B and permanent residency.
Caveat: My experience is exclusively at R1 institutions, and thus may not be fully applicable to "liberal arts colleges"


Gnuplot in thesis and articles or not? I'm doing an astrophysics thesis with a lot of programming in Python. I'm currently using gnuplot for my plots, but I wonder if this is actually looking quite professional. Are there other options which look better and are still easy to use?

Here an example of a figure in my thesis:

The vertical line I got with the following command:

set arrow from 4861.3,-1200 to 4861.3,2000 nohead lc 2

I know it reaches out of the figure, but I use this command for all of my script and I know only at the end what the upper and lower boundary of the y-axis will be. Every peak is different.

If you do the programming in Python, you could also do the plotting in Python with matplotlib. With a little adjustment of the plotting parameters, it is possible to produce publication-quality plots with this software.

Alternatively, if you need fancy annotations etc., I can recommend the pgfplots package for tikz/LaTeX. You could export data from your Python program to a csv file, and then use that as data source for plotting with pgfplots. If you are also using TeX for the main text, it allows to to produce graphics which nicely fit the formating of the text.


Refworks Bibliography Output Style Choice, for Springer? Refworks.com can output a bibliography, based on an output style list, which includes several hundred different output style choices.  Refworks Output Style List

However, the list does specifically include "Springer": see i.e.  Springer Bibliography Requirements

What is a similar Refworks output style choice/item, which is similar to the Springer requirements?

The "Springer" document that you linked contains specific instructions for how to contribute to Springer Computer Science Proceedings. It also says:

  You will find here Springer’s guidelines for the preparation of
  proceedings papers to be published in one of the following series, in
  printed and electronic form

That means that those instructions are valid for all the journals and publications listed below.

So try to look for one of those style (i.e.: Lecture Notes in Computer Science) and it should work.


Am I allowed to show properly redacted exams to a colleague to determine if cheating occurred? On an exam I recently administered, I discovered that several students had turned in essentially the same solutions for multiple questions. Before launching an academic dishonesty investigation, however, I want to make sure that it's not just "in my head" after reviewing too many exams in a row, or some other similar problem.

If I'm in the US, does the Family Educational Rights and Privacy Act (FERPA) preclude me from showing a redacted version of the exam—one in which names and ID numbers have been removed, for instance—to a departmental colleague to get a second opinion? If so, then how can someone get a second opinion on whether everything is above board or not?

FERPA permits education records to be shared with school officials who have a "legitimate educational interest" in them. Examples of a "legitimate educational interest" include (via University of Northern Iowa):

  Performing appropriate tasks that are specified in his/her position description or by a contract agreement.
  Performing a task related to a student's education.
  Performing a task related to the discipline of a student.
  Providing services for the student or the student's family, such as health care, counseling, job placement, or financial aid.

Also, if the student is not personally identifiable from the anonymized exam paper, then the papers are not protected by FERPA at all. Via Wayne State University:

  With specific exceptions, FERPA defines “an educational record” quite broadly and it is not limited to “academic” records.  “Education records” include virtually all records maintained by an educational institution, in any format, that are “directly related” to one or more of its past or present students.  A record is “directly related” to a student if it is “personally identifiable” to the student. A record is “personally identifiable” to a student if it expressly identifies the student on its face by name, address, ID number, or other such common identifier.

  A record is also personally identifiable if it includes “other information that, alone or in combination, is linked or linkable to a specific student that would allow a reasonable person in the school community, who does not have personal knowledge of the relevant circumstances, to identify the student with reasonable certainty” – in other words, if it contains enough demographic or other information that it points to a single student.


Manuscript was "unsubmitted" because the manuscript was deposited in Arxiv Preprints One of my manuscripts was "unsubmitted" and potentially rejected by the journal for the reason that it was submitted to a preprint server. Is it normal for the journal to reject a paper that was submitted in a preprint?

Most journals now allow and even encourage the use of preprint servers. Some, however, still prohibit it on the notion that it is competition with their own publication of the article, or even consider it self-plagiarism. This tends to be field-dependent as well: some fields (e.g., physics, mathematics) are very liberal in policy, while others tend to be more retrogressive (e.g., chemistry, certain portions of biology).

The only way to tell a particular journal's policy, however, is to check the specific journal (the SHERPA/RoMEO database is also highly helpful, since it's easier to find the policies there and they have been pre-interpreted by experts).

If you have, indeed, been prohibited from submission due to a journal's policy on preprints, my only advice is to find another that allows it.


PhD - unhelpful supervisor, how normal is it? My question maybe trivial but I really want the opinion of others if the problem is with me or with my supervisor/ the lab.
Half a year ago I started PhD in a small university town in Europe. I am a foreigner that does not know the local language but during the recruitment process they assured me that it shouldn't be a problem (yeah right no lab workers know English and even in the office where I am sitting everybody just ignores me and speak in the local language if they are not addressing me personally). Another problem is that I came from a similar yet different scientific background and I have no experience working with the topic that I got.
I understand that I should work independent on my topic and not rely on others yet this is kinda ridiculous in my opinion that everybody just assumes that I should develop my protocols, starts working and ordering the lab equipment without any supervisors straight away. Of course I try to adapt and I am starting to do research yet as my only help are articles and google. As my daily supervisor just insists that I should be independent from the start. What is even more funny I am working for almost half a year but I haven't even met my "official, main supervisor" and I don't even know what is my project timescheldue. I am constantly just left out of the information loop and get angry or confused stares if I try to ask these questions.
Is it normal? I am not expecting guiding by the hand on every step of the PhD but at least at the start when they know that I have 0 expertise in the topic, would be helpful. Basically, I am almost on the verge of nervous breakdown and feeling like a moron that is wasting time.

This is mostly advice beyond the scope of the question, but to try to answer the question itself, the entire situation seems horrific and unsustainable.
I don't think it is literally "normal", but I do think the situation is far too common. It isn't really you and it isn't really the PI,  but the entire set up from top to bottom. Only a few (and there are a few) doctoral students could thrive in such a situation.
However, along with the bad, there seems to be something good about the current situation or you would have fled by now. A salary is good and avoiding pandemic chaos is good, but I'm not seeing an obvious path, here, to a doctorate.
But, you are early in your studies (half a year). I'd suggest that you spend some effort looking for a better situation, preferably in the English speaking world unless you are fluent in some other language. Even if you were to learn the local language fairly fluently in the next few months, the time to completion in Europe is normally expected to be quite short.
Look at all the options. It would be hard to find a worse one, I think.


Advisor associated with the U.S. Army want their name removed from the text of a published article I have been contacted by an individual with a request to remove their name from an article our journal published two years ago. The individual was identified as a Culture and Foreign Language Advisor of the U.S. Army; their post location (city) was also mentioned. This person claims that the author of this article did not asked their permission to include their name in the article, and did not give informed consent to do so.

Is this a valid request? I mean, it may be valid ethically as it may put this person and their relatives at risk, by associating their name with a military program, but since two years have passed since publication and our journal is open-access, this article has been archived on a number of other sites we do not control. So, the info is already out there, no matter how we proceed. Do you think this is also a legal problem? (The journal is located in Central Europe)

This seems like an unreasonable request to me. The copyright to the text rests with the publisher, and the "moral rights" with the authors of the paper. I don't think anyone who is mentioned in the article has a legal right to request removal from the article. Certainly, this would morally require consent from the authors.

In general, I do not think that there is a legal right to not have one's name mentioned unless that violates state secrecy rights (think, the name "Valerie Plame" appearing in newspaper articles about the CIA). If the local newspaper mentioned my name in the context of the local cycling club, then this seems to me to be a fair use of their journalistic priviledge that I can not reasonably challenge.


My paper was accepted, but I found an error affecting all of the figures. What will happen next? I submitted a paper to a journal, and the decision was "accept with minor revisions."  As I was addressing the reviewer questions to submit a final copy, I realized that I may have misrepresented the data.

Specifically, I may have over-reached with a statistical model.  The model involved repeated measures of individuals who were initially one group (let's call it condition A), but were later split into two groups (B and C).  The model gives me differences between conditions.  My mistake was to calculate the actual values at each condition based on these differences, which was wrong because by dumb luck the 2 groups had a systematic offset at A before they were split (even though the members of each group were chosen randomly).  Hopefully that explanation makes some sense.  I presented the data in terms of "actual" values rather than differences because I thought this would be more informative for the reader.  So, basically, all the numbers are wrong.  It's a stupid mistake in hindsight, since I could find this information in the raw data.

The conclusions of the paper and the statistically significant relationships would still be the same in the corrected version, because I believe the model to be the correct one.  However, almost all of the numbers, tables, and figures would need modification.  And of course the strange systematic offset between randomized groups will raise eyebrows.

I'm certainly going to notify the editor and attempt to submit a corrected version of the paper.  I'm wondering what I should expect to happen, though.  Are journals understanding of this type of error, or does it represent something so egregious that the paper would be rejected and my credibility would be damaged?  Or would it simply be reviewed again?  I understand that it's largely up to the editor to decide, but I'm wondering if anyone with similar experience might give me an idea of what I'm dealing with.  Thanks!

Though I don't have any prior experience with this, I agree that you should notify the editor and should explain to them how and why this mess happened. Also let then know that it was a mistake and as soon as you realized it, you let them know. Also let them know that you are ready if they want to have the paper reviewed again. I believe that they would understand the mistake and would not make a scene out of it. But yes, you have to choose your words carefully and should politely explain them the point and admit your mistake.


Applying to Social Psych Programs: How important are grades in statistics? I'm preparing to apply to Social Psych programs this fall and I'm wondering how much a mediocre grade in an Advanced Stats course (B-) would weight down my application. Barring this course, my transcript is fine, with a general GPA of 82% (don't know how to convert Canadian GPA to American GPA, but it's good).

I still have a chance of taking a stats course this summer at my University as a returning student. But which is a better idea? A) Taking the stats course and doing really well or B) not take the course and use that time to focus on getting very good quant score on the GRE instead?

Social psych is my field! (Well, one of them.) It's impossible to answer how much a specific grade in advanced stats will affect your application, but you can still get into some top programs with a B- in advanced stats. FWIW, I failed an important psych class one year in college and still got into top PhD programs before I retook the class, including the one I graduated from.

Do you understand stats well enough to take a graduate-level statistics course and do the kind of research you need to do for now? If so, don't retake the course, and focus on studying for the GRE and more importantly writing a great statement of purpose. One B- is unlikely to tank your chances if you are otherwise an outstanding student.


Is a journal that is on Beall's list but is also in Scopus a predatory journal? I have seen a journal, in the Computer Science field, that is predatory according to the Beall list (sorry if its not well written), but I see that this journal appears indexed in Scopus and Scimago; so I was wondering how to determine if a journal is predatory or not?

For example, I know that even some journals from Elsevier or Springer charge different prices for publishing an accepted article, and according to some colleagues if a journal charges for publication then it could be a predatory one, but the aforementioned editorials charge also so to whom believe?

I was also wondering if the B list is also accurate, I am starting to have my doubts about it.

Indexing in Scopus does not necessarily mean that a journal is not predatory. From the guidelines for being indexed in Scopus:

  -The Journal should consist of peer‐reviewed content

  -The Journal should be published on a regular basis (have an ISSN number that has been
  registered with the International ISSN Centre)

  -Content should be relevant and readable for an international audience (at minimum
  have references in Roman script and English language abstracts and article titles)

  -The Journal should have a publication ethics and publication malpractice statement

These guidelines could potentially be satisfied by a journal that Beall's list considers predatory. Many pay-to-publish journals advertise "peer review", but it may not even be solicited/may not matter in the "decision" to accept the manuscript.

There also can be information on why the specific journal or publisher is considered predatory on https://scholarlyoa.com. I generally have high confidence in Beall's list--predatory journals do not have a great incentive to turn legitimate.


Where to find curriculum for a specific program? I have an assignment for preparing the first draft of curriculum for a new program in my university. To include international experiences, I tried to get the curriculum of other universities, but I was unable to find a university website sharing the full curriculum. Department websites just put the title of courses, and professors post syllabus for their courses.

Each department should have its curriculum (description of the program, courses and credit details, course descriptions, etc), and this should be a public document.

When I searched general or visited top university websites, I expected to find such documents.

Do you have any idea where I can find documented curriculum?

At many US institutions I believe what you are looking for is often called a "course catalog". This generally lists degree programs, what courses are required for each major/minor, as well as a description of each course and their associated credit load.

With this phrase in mind a quick Googling returned a variety of listings for top Universities:

Carnegie Mellon Undergraduate Catalog
MIT Course catalog
Undergraduate and Graduate catalogs for University of Wisconsin-Madison

If that's what you were looking for, just the magic phrase "course catalog" will help in the US. But in other countries? Well, a search for a course catalog for University of Cape Town in South Africa produced a link to the student "handbooks", which appear to be the same thing as the US course catalog.

It appears each country has their own preferred term for what to call this, so finding the magic words for each country might be a bit of a trick.


Other evaluation systems than exams I live in a country where the quality of education is poor.
The primary goal seems only to be to teach us how to pass exams and not to learn the material for knowledge sake. It appears that their sole focus is for us to score well on tests so that we can get into a better college an maybe get a good job.

It is only about exams and I feel like I am being deprived of an education.

As I am not familiar with other education systems, I would like to know if there are education system where there are evaluation systems other than exams or where there is less of an emphasis on teaching to the exam?

Are there systems that evaluate a student's performance based on writing papers of doing projects?

As Gnometorule mentions in the comments, you'll find a variety of other types of assessments.

The three most common ones for end-of-course assessment are the exam, the project, and the paper, but they definitely aren't the only things that can be used to determine a grade.

In literature classes, and I'd imagine the majority of humanities classes, papers are a more common form of assessment.  Even exams, when given, are more paper-like being in essay format.  In most math courses, on the other hand, you'll tend to find exams are more common.  In computer science courses or the visual arts, projects are probably more likely the substantial source of grades.

It's also not uncommon, at least in the US, to find other elements of courses counting for part of the final grade.  Participation can be an important element of discussion classes, or classes where interaction with other students is very important such as in music or theatre courses (and those may also have a performance/recital as part of the grade, though that may be considered a test of sorts).  Homework may also be counted as a portion of the grade.  Portfolios, which can be a sort of mix of hybrid of homework and/or smaller projects, are also relatively common.


May additional time in college harm my chances of going to grad school? I'm an electrical engineering major (my home university is ranked #25 nationally). I'm about to start the fifth year(engineering takes 5 years in my country).

I also granted a national science scholarship last year, and was an exchange student at University of Colorado at Boulder. I did very well over there (3.9/4.0).

In my country, electrical engineering and electronic/computer(EECS) science are different. Electrical deals with power systems and telecomunications, while EECS deals with microelectronics, dsp, embedded systems, theory of computation and so on.

My home university doesn't have the EECS option so I had to choose electrical engineering, since I hadn't money to move to another place.

at CU Boulder, I basically only took classes in advanced math (even grad school level) that is my passion for life and computer science(another passion). Since I got back I'm not very motivated with my program, because I want to study EECS and math and not power systems.

Currently I'm attending the math summer program(summer here is January and February) at one of the leading math research institutes in my country(and even one of the best in the world) and I was invited to start the Master of Advanced Studies in March. They offered me a scholarship, so all my expenses will be covered. Since I didn't complete my undergrad studies yet, they offered to transfer my Engineering course to the school of engineering and math(ranked #1 nationally), and then after 2/2.5 years from march I'd have a bachelor's of electronic/computer science engineering, a second bachelor's degree in math and Master of Advanced studies in math. The only "problem" is that in the end, I'd have taken 7/7.5 years to complete my bachelor's of engineering program.

My question is the following: Will this "long time" for completing the engineering program harm my chances of being accepted by grad school, in math or computer science in a top graduate school?

May I argue in the applicant's form that I took 7.5 years because I moved on, I wasn't happy with my course/university, and when I chance to study my passions at the best schools in the country so I went forward ? (that would in fact be true)

In the whole thing I'd have 3 degrees(by # 1 institutes) in a total time of 7.5 years and a really good education, but I'm a little concerned about this "time to complete" thing, I really don't know how it works, specially in US

Can someone help?

Thank you everybody,

Dmitri

Taking a long time to complete one degree can be a bit of a red flag in US graduate admissions. However, this does not apply in your case, because you will have three separate degrees. The fact that you have transferred from one school to another also mitigates the lengthier time you've spent in those study programs.

If you hadn't done this "master of advanced studies," spending 7.5 years as an undergraduate would probably not be looked on too favorably. But in your specific circumstance, it's not as bad as it looks at first blush.

There might be a question, however, about why you want to do EECS at the graduate level, given that your master's degree would be in a math-related field. But that would be up to you to explain in any case as part of your statement of purpose.


Is it a contribution if I prove the result in previous paper in my own way and provide small extension in the form of application of the results? If I have an idea to extend an already published paper (P1) but the extension is very small and further I know how to prove the results of (P1) so my question is as follows. If I prove the results of P1 through my own way and has slight extension (in the form of application of the results) of P1 then is it worth writing that idea or should I avoid such thing?

It is often very difficult to answer "Is this paper worth writing?" in general terms.  Sorry to say, but it is very common that you don't know whether a paper is worth writing until you write it, and you don't know whether a paper is publishable until you submit it (sometimes more than once).

If I understood the situation properly, it's this: there is a paper in the literature by someone else that contains some mathematical-ish result: something that received a proof in the original publication.  You have (i) your own proof and (ii) a small extension of the result, and you are wondering whether it's worth writing up and trying to publish.  So the answer is: it might or might not be.  If you are a junior researcher -- by which I mean anyone who has a designated advisor or mentor -- then I strongly suggest that you talk to your advisor about this.  The question of what constitutes publishable work (and if so, where it can/should be published) is really a question about the sociology of your discipline, and a veteran researcher in your field will probably have better instincts about this than a newer researcher...and this can continue to be true even when the veteran researcher has equal or lesser insight into this particular project.

Probably though at some point you will just have to decide whether to push on with it or not.  That's really up to you.  The main downside is that you may spend time writing and trying to publish the paper and eventually learn that the paper is not publishable, or at least not publishable in the sort of journal you want to publish in.  There is also the chance that you could publish the paper and that others in the field may view your contribution as too minor to meet their own standards of publication, but in that situation I would expect them to mostly ignore the paper.  (There are other situations in academia where people count papers, and even a very minor publication will still count for that.  This is not a great situation, in my opinion, but it exists, and some people may in fact have large incentives to keep the publications coming.)

I think the right way to look at the decision is this: the question is not really whether to write up and publish versus not to write up and publish.  Rather, you will want to spend your time writing up and publishing something, and practically speaking there is a limit on the number of projects you can try to write up and publish at any given time.  (This varies based on the field and even the person.  For me (a mathematician), even if I start with a huge stack of manuscripts already on my desk with all the Theorem:... and Proof:...'s already written down in some mathematically satisfactory form, nevertheless I would struggle mightily to find the time to edit and submit more than 4-5 of them per year.)  So do you want to spend your time on this or something else?

I want to end by mentioning that a few months ago I submitted for publication a project that has the same rough description as the OP: in this note I give a new (though not completely new) proof of a recent theorem of M. Kapovich, and then I prove a stronger result in a special case.  There is no question that I view this as a very minor work.  Why did I decide to submit it for publication?  Well, first I found Kapovich's result very interesting so I had already decided to give an exposition of it in some notes of mine.  Writing up these results led directly to my (very minor) new contribution, so the amount of additional polishing I had to do in order to have something submittable was rather small.  Second, the paper concerns a mathematical subfield, complex manifolds, in which I absolutely do not possess a research-level knowledge....so I have no reputation to ruin.  Finally, I have enough other publications that I think no one is going to try to draw any conclusions about my research program or trajectory from this one paper.  Whether this was a good decision is not yet clear to me...

Added: Just this morning I received an email that the above note has been accepted!


Disclaimer in syllabus, a good or bad idea for instructor and students? I have seen couple of syllabi that used a disclaimer similar to "Instructor reserves the right to change the syllabus at any time". For the instructor side, it could be good, but from students side it could be good or bad, depending on the change. Any other thoughts?

Unless there is an unusually rigid set of controls and policies in the instructor's department, it is generally always the case that the instructor can change the syllabus on the fly.  With any decent instructor, there is usually a good reason for doing so, such as incorporating an improvement the instructor has figured out partway through or adding extra emphasis on a section that people seem to be having trouble with.  With a poor instructor, on the other hand, I don't think that the situation can be rescued by making the syllabus more rigid.

As such, my interpretation of the disclaimer is that it's simply a way to insulate the professor from complaints of students who take a rigid interpretation.  From the students' side, I think it means little, only acknowledging a reality of instruction.


How much flexibility does one have in selecting their PhD coursework in the first year? For instance, if someone is working as a Phd in computer-science, but on a neuroscience related topic, she might need to take some neuroscience related courses. And some CS courses might not be any help at all for the area she is interested in. Do universities put a lower/upper limit on the number of courses one can take?
Also, does this differ from university to university?

It varies dramatically, by university, field, and country.

It can be any of:

There is a fixed curriculum that everyone takes
There are a few required courses and the student can choose the rest
The student has a committee which recommends courses to take
The student can take any courses but has exams to pass
No coursework at all (I understand this is common in Europe, where Ph.D. students come in with a Masters)

Usually there are upper and lower limits on the number of courses to take.  In the US, one usually has to take at least 3 or 4 courses to be considered a "full time student" and be eligible for funding.  (But one can often count research as one or more of these courses.)  And it is often not allowed to exceed 5 or 6 courses without special permission.