Should I send this e-mail to my instructor who is also my supervisor? I am very mad about my grade and I prepared this letter. could you pls give me a piece of advice about how to write and complain about the grade? I really do not know what to write. I really want to tell him that this grade is not fair.

PS: I should say that this prof is my supervisor as well.

HERE IS MY LETTER

I am writing this email regarding ++++ grades.
I am not happy with my grad. I hope you do not mind but I'd like to ask some questions.
I should say that I am really surprised by the final exam grade.  The questions were very easy for me since they were very similar to what we learned in the lectures and you had already covered all of them through the lecture, I thought I could get 100 in the final exam.

In the written report, I got 86.00 I am really curious about this grade. I want to know why I really performed badly. Did I miss anything in the report?

I am available days and nights to discuss these three parts.

I would strongly suggest not sending this mail. I'll give some specific feedback below, but in general, it is very distasteful when students complain about their grades when they don't even know why they lost points. I understand that you are angry, but especially since this professor is your supervisor, I think asking politely to learn what you missed and to raise any concerns is likely to end better than going in angry and demanding points.

I think the best course of action would be to ask for an appointment to discuss your grade.  At this meeting, you can ask to review these three items with him/her, at which point you can listen while they explain why you got the grades you got. At this point you can politely ask for clarification or politely request they reconsider certain subjective marks.

To the points you raise:

  firstly, I should say that I am really surprised by the final exam grade(93.00). The questions were very easy for me since they were very similar to what we learned in the lectures and you had already covered all of them through the lecture, I thought I could get 100 in the final exam.

This is probably your weakest argument -- "I thought I would do better" is not actionable. Instead, I think you should ask where you came up short, and then follow-up from there if you think the answer is unfair.

  secondly, I think the oral presentation was way better than other students oral presentation. Most of the presentation given by students were not well organized and even they did not even care about timing and the rubric. I got just 89 and the second mark is 88. I think there were lots of difference between our present and the guys who got 88.

It's not clear how you know that you got the top score and the second mark was one point below you. Even assuming this is true, how other students were graded is not your concern. If there are scores on the rubric that you object to, then it is fair to raise those points. But again, I would try to be very polite and ask for an explanation rather than trying to argue that you deserve more points. After you understand the perceived weaknesses, you will be in a better position to respond to their concerns and even ask that they reconsider one or two of those marks.

By the way, I hope this presentation was recent -- it seems very opportunistic when students have no complaints until the end of the term, and then all of a sudden old grades become unfair.

  Finally, in the written report, I got 86.00 I am really curious about this grade. I want to know why I really performed badly. Did I miss anything in the report?

I'm not sure in what course an 86.00 is "really performing badly." But I wouldn't ask "if you missed anything" -- obviously you missed 14% of the report, in the instructor's view! I would simply ask to be allowed to review/discuss your professor's comments, and then you can follow up if you think any of the complaints are not valid.

So, I would write this instead.

  Dear Professor, I was a little disappointed by my final grade. I'd like to go over the final exam and written report with you to see what I missed. I am free anytime this week, please let me know what time you are available. --Name.


What major is beneficial for a long-term career goal in medical robotics/ robotics/ artificial intelligence? I have done my undergraduate degree in a Indian university in electronics and communication engineering and have done a job in one of my field of interest medical image processing and I worked in robotics while doing my degree projects. Now I am going to apply for masters in US universities but I am confused about what major I have to choose. My long term goal is to be a researcher in medical robotics/ robotics/ artificial intelligence also I can work with nano electronics but I have not done any work or not so much study in that before so I am a bit nervous to choose that.

As after masters I will go for PhD so please help me to resolve which of the above field will be favorable. As I have doubts like medical image processing is not a vast and not so many funding is there for PhD students.

Robotics in itself is an inter-disciplinary field, which I assume is why you are asking the question and have no just found it online.  There are some programs specializing in robotics, but the main question is what part of robotics you want to work on.  Control, Design, Theory, etc..  Humanoid robotics is different than nano robotics.

If your end goal is Nano electronics, look into schools that specialize in... Nano electronics.  In that field as well, you should figure out what aspect you are interested in.  Department of Physics will sometimes have these majors, or some inter-discipline schools may have a special Nano program.

Purdue has a Nanoelectronics field inside engineering: https://engineering.purdue.edu/NRL/Students/index.html

Carnegie Mellon Univ. has a Nanorobotics lab inside mechanical Engineering:
http://nanolab.me.cmu.edu/

Utah State has a bionanoelectronis lab in its Biological Engineering lab:
http://be.usu.edu/htm/research/research-labs

As you can see, "nano" is a hot topic, and can be approached by different fields.  First figure out what aspect your intersted in, and if you do not want to go directly to PHD, you can major is a more generalized aspect, either Mechanical engineering, Physics, Chemistry, or Electrical Engineering.

If your interested in Artificial Intelligence, then you may want to go into Computer Science.

If you want build medical robotics, it may be useful to have some medical training ontop of your EE background, which may make you attractive to interdisciplinary labs.  Or you can do Mechanical Engineering.

Saying your interested in Robotics, is a bit like saying you want to "Build Things".  You want to build Sculpture, Houses, Sky Scrappers, Bridges, Circuit Boards. Etc..


Should I add a non-requested work to my major revision of a scientific journal paper? I am wondering if I should follow the advice of my co-advisor or a relative of mine who is also a researcher and used to write a scientific paper in the same field (but currently with less experience then my co-advisor).

I will make it a bit more clear:

I am a Ph.D. student in CS, specifically in networking, I wrote a scientific paper that I have sent to an Elsevier journal.
Last month, the journal replied to my submitted paper and requested a major revision; so I know that I have a bunch of rework to do.
One of three reviewers was complaining about the contribution and evaluations/simulations that I have done, while the other two didn’t complain in the same manner.
Following to this and in order to make it clearer for the complaining reviewer, my co-advisor advised me to add a small simulation/evaluation to my paper to clarify the contribution and justify why we considered various scenarios in terms of scale.
In the meanwhile, I asked a relative for help, he said that it is not a good approach to add this simulation/evaluation since no reviewer asked for it, and could be harmful to my work/my chances to being published.

While I can agree with my relative about adding a non-requested work, my intuition pushes me to follow my co-advisor, since this is a little work that can clarify, justify more the need for considering various scenarios (which I have done and the reviewer didn’t understand why I did it).

As somebody in a different area of computer science, I find it hard to see how including a little more true, relevant information could possibly be harmful. The reviewers think your paper is worth publishing with revisions. The worst case I can see is that, when you submit the revised version with this extra unsolicited material, the referees ask you to remove it again.

You can always mention your parent's opinion to your co-authors and see what they think.


What to do about advisor with history of possible plagiarism? Recently, my MS advisor instructed me to submit a conference paper.  They outlined what this paper would include, which would be a simulation study that is a near duplication of a ten-year-old published journal article (from a different group of researchers) that I have been reproducing results from for learning purposes.  They said to omit citation of that journal article for the initial submission, and add it in the final draft if the conference paper is accepted.  From a professional integrity standpoint, I have no intention to do this.  I plan to write a paper that extends the results, and to include the citation in all drafts.  I am unhappy that my advisor instructed me to essentially plagiarize, but plenty capable of not doing so, so I wasn't going to make a fuss about it.

However, in my literature search for writing my conference paper, I stumbled across Paper A that is extremely similar to one of my advisor's papers, Paper B.  Paper A has different notation, but the same equations and results, published about 30 years earlier than my advisor's paper.  Paper B does not cite this older paper, but does include a new simulation example in additional to the similar material, so it is not a complete copy.  In light of their recent request to me, I am suspicious of my advisor's previous publications, and uncertain how to proceed working with them.

Should I show this older paper to them and ask about it?  Should I report this to some higher authority?  Is this a relatively common occurrence that I am overthinking?  I do not rely on my advisor for funding, but I would not be thrilled about sabotaging my thesis by starting drama with my advisor.  I would also not be thrilled to sabotage my future publishibility by working with a serial plagiarizer.

First, don't assume that it is plagiarism without more evidence. Parallel research is very common in many fields and a 30 year old paper may not have been well known in the time frame your professor wrote his/her paper. It may well be plagiarism, but it isn't necessarily so.

It is appropriate to point out the newly found paper to your advisor and gauge the reaction, but it is premature to "complain" to higher authority without solid evidence. You are correct to be wary. But showing it to your advisor could be just an "oh by the way, I came across...". Depending on the reaction you may learn more about their general attitude.

It would, indeed, be unfortunate to have to work with someone with poor ethical standards and if your suspicions are verified you might try to move to a different advisor. This is less critical at the MS level than it would be later, but as long as you preserve your own ethical reputation, you should be fine.

But, certainly, the recent instructions about omitting a reference are problematic. It is possible to write a valid paper reproducing and verifying old results without crossing ethical boundaries. But the work clearly needs to be presented that way, rather than as an innovation. If the referees are up to date in the field, such obfuscation may be caught to everyone's detriment.


Making the most of having two group affiliations I am co-supervised by two PIs and I am spending half my time each week in one lab and the other half in the other lab.

My question is, how can I make the most of this situation? What are the pitfalls? How does this differ from being supervised by one person and therefore spending all of one's time in one lab?

I am a PhD student, but I suppose this could also apply to post-docs. If it matters, my field is biology.

When the two PIs are at different universities, you could perform your thesis as a double degree (something I did myself), assuming that both universities allow this. One aspect that needs to be taken into account is that if you do so, you need to adhere to the regulations of both institutions, which sometime leads to conflicting requirements. Also you need to align with the bureaucracies of both institutions, which certainly results in some overhead for you.

Anyway, even when the PIs are at the same institution, you can profit from their (hopefully somewhat complementary) expertise. Also you will have a larger network. You will need to balance your time between both research groups, and align their feedback, which is a potential pitfall, but also a learning opportunity.


Shall I include a list of workshops and conferences attended during my UG in my 4 page CV? I'm currently applying for US graduate programs (doctoral study in Molecular biology). I'm asked to submit a maximum of 3-4 page CV. I have  participated in nearly 20 workshops and conferences in my 3 year undergraduate  period. As the list is big I didn't include in the CV.

I would like to know how to prove or tell to grad committee members that I'm ardent on learning techniques and that is the reason I went beyond college curriculum to learn it individually and in depth?

Thanks.

You should definitely mention that you attended conferences. How much detail to include depends on how much space you have left after you included all of the more important information on your CV. I cannot tell what is more or less important. You have to figure it out yourself. Here is what I usually do in such situations:

Make a CV listing everything you have that is even slightly relevant to what you are applying for. If you went over the page limit proceed to step 2.
Divide your CV into absolutely necessary/required info and 'other stuff'.
Rank the 'other stuff' from very important to barely relevant on some continuous scale, say 1 to 10.
Delete the least relevant info until you reach the page limit of your CV.

You can apply the same procedure to your conference list. I would say it is important, but not 100% of it if you don't have enough room. Rank the conferences you attended from the most prestigious/impressive to the least impressive. Start listing them from the most prestigious until you hit the page limit. Leave one sentence to mention the conferences you omitted, generalizing them in some way to underline their relevance: "... and other (number) conferences on topics related to molecular biology.


How to deal with an arrogant advisor My advisor is a highly regarded scientist in his field. However, that also made him a very arrogant person. I have two things I desperately need help with:

Research projects
My advisor becomes more and more picky about research projects. He only wants to work on "important" projects and he only trust what is in his toolbox. New methods, new ideas, and trendy topics are usually considered either useless or non-essential to him, therefore I have never got a chance to work with him on anything that is trendy and more publishable. On the other hand, he is incapable of doing anything ground-breaking, as he would wish, at this point which push his students to work on their own.
Student management
My advisor really cherishes his time, therefore makes sure to never spend it too much on his students. And he hates to waste his time talking to people who are apparently not in his league. His students usually fall into this category. You can definitely tell when you go to talk to him and didn't prepare anything "interesting" or "important", he will put up this tired and impatient face. Therefore these days he chooses to collaborate with other professors not his students. Besides the science, he rarely helps student getting postdocs and couldn't care less about paper editing for his students.

I know most of you would suggest to switch, but is there a way or any soft skill to make this advisor-student relation work? Other than becoming an expert within his league in a short-period of time?

Okay, he doesn't like to chit chat with students, and he is conservative in his choice of topics and methods.  He's not proactive about arranging postdocs and he doesn't edit his students' manuscripts.  None of these things strike me as deal breakers, necessarily, but of course you'd have to weigh these things against what he has in the plus column.

But speaking of pluses, all I got from your post is that he is a highly regarded scientist in his field.

I suggest you take the next couple of months to try to find the pluses.  Find out what his strengths are.  See if you can figure out what makes him tick.

One of my best memories of my advisor is that once, on a long drive to the airport, he told me his memories of staving off hunger by working as a translator for the U.S. army in postwar Japan.


Contacting a reference for verification as an editor I am an assistant editor of a local health journal and recently an author submitted a paper on the psychometric property of a translated instrument.

I have requested for a proof of acknowledgement of the original developer allowing the translation, in which the authors were not able to find, citing the time lapse. Would it be fine if I email the owner myself and ask if this was true?

Thank you all.

I think that since the authors are making a claim that will eventually be public if the paper is published, you can do this certainly.

If you have any suspicions of misconduct then due diligence might also require that you verify the accuracy of the translation, but that is a different issue.


How should I cite a paper from a journal that has changed its name? I found that a journal changed its name after 2005. The paper which I am citing is from 2004. Does it matter if I use the current journal name or should I cite the paper using the (old) journal name in 2004?

Cite the journal name that was used at the time of publication. For example, the British Medical Journal officially changed title to BMJ in 1988. Cite articles from 1987 and earlier as Br Med J, not BMJ.

(Source: The NLM Style Guide for Authors, Editors, and Publishers, 2nd edition.)


Journals for tutorials I've written a paper that describes a system (for encryption), showing step by step how the system was formed. It's not a system I invented. I analyze that system and compare it with similar systems. Novel aspects include new understandings of those systems and how they relate to one-another. Can I publish this paper in a journal?

You describe an existing system, analyze it, and compare it with similar systems. If any of that is novel, your work is publishable, otherwise, you might be able to publish your work as a tutorial.


can't reach book editor For the last 5 years (delayed partly by teaching, a parent's death and caregiving for another parent), I've been writing a textbook that examines a famous 18th-century political work. The proposal was accepted and a year later, I got very positive feedback on the first half of the manuscript.

I finally submitted the entire manuscript in early December 2018 and felt quite confident about it--despite the fact that my Ph.D. is in English literature and not history or poli sci.  I wrote to the editor back in late January to see if he'd gotten any word; he replied that he hadn't heard anything and to wait until late February. I've been writing to him once a week since then--and twice last week, but with no luck. It's strange because when I was corresponding with him back in August-December, he always answered very promptly.

I've tried writing to the editor who approved the book proposal (he's since moved onto another department) and another who was a supervising editor. No response. I am really stumped: what can I do since I cannot seem to reach anyone at all? I realize there's not much action I can take and that there are any number of scenarios (maybe none of the reviewers liked it and they are sending to others?), but it is really driving me up a wall. I've looked up the "Contact us" section in the publisher's website, but there is no information on the editor of the textbook for the series that I am editing. There are no phone numbers either.  Any advice?

Obviously I don't know how this particular editor works (and I'm not familiar with textbook edition), but it's quite common for an academic review process to take several months or even more than a year. Another general fact about reviewing: if reviewers don't like it they don't send it to another reviewer, they write a bad review and you will be informed about it.

Unless this editor promised you a fast review process, from the information you provide it looks to me like there's nothing to worry about. At this stage the reviewers have your book but it's possible that some of them haven't even started reading it yet.

  I've been writing to him once a week since then--and twice last week, but with no luck.

Are you sure this editor was happy about you emailing him every week? Unless you are in very friendly terms with him, your frequent emails might be a bit annoying to him! And that might explain why he stopped answering.

Obviously I don't know any specifics, but it seems to me that there's absolutely no reason to panic: as you said, the first half was well received and you were feeling confident about it when you submitted. Try to go back to this original state of mind instead of imagining the worst. Delays are frequent in a review process and they are not a sign of negative outcome... just a sign that everybody is busy. Patience and good luck!


What do professors do with personal copies of old textbooks? I've been teaching a few years now and the number of older editions of textbooks is beginning to pile up in my office. There is no policy at my university for disposal of old textbooks. These books were purchase with department funds and it troubles me to throw them away. They content is still relevant as the newer editions are not ground-breaking in material.

My questions are as follows...

Please share how you deal with older editions of textbooks?
Is there a policy at your institution (if so please share) or do you have a personal way of dealing with this problem (again please share)?

At my school the custom seems to be just leaving them in a stack in the hallway next to one's office door. Anyone walking by can peruse through them and take anything they want. At some point the janitorial stuff disposes of the stack as rubbish.


Why are papers accepted even if they don't release code or data to allow reproducibility? Recently, we had a lecture about Reproducible research on of the slides was:

  Reproducibility: start from the same samples/data, use the same methods,   get the same results.
  Replicability: conduct again the experiment with independent samples and/or   methods to get confirmatory results.

  Replicability = Reproducibility + Conduct experiment again

  Replicability might be challenging in epidemiology (recruit again a cohort) or   molecular biology (complex cell manipulation).
  Reproducibility should be a minimum standard. One should strive to at least make his/her   own research reproducible.

I find many articles that use software and when they hint what kind of analysis did they don't provide the code nor the data. There are public free ways of storing data and code of studies, and even with a DOI.

So far, I thought that some data might not be freely available because it has some private information (my field is bioinformatics), or the authors intend to use it for further investigations and want to keep for themselves the data.

The same happens with the code is the intellectual property of the lab or principal investigator, but retaining the rights of the code don't goes against the replicability.

Why are these papers accepted and publicized, even if they don't allow reproducibility?

Related: Reproducible Studies? and an example of the problem it causes Can up to 70% of scientific studies not be reproduced?.

Edit:
Some other papers about replicability: 1, 2.

Excel case: in this paper we can see an example. Reviewers of Growth in a Time of Debt estimated
(note that this is not measurable/checkable afirmation) that the
analysis could bring the results presented.

(I couldn't find a description of the methods used for the analysis on the paper, but it is a different field of mine and I have skimmed through).
But in new methods without prior experience/validation how can one estimate it without looking to the analysis itself?
And in "old" methods, how bad would be to share them if they are already checked?
"Understand why replicability is important, and you'll understand
which guidelines and rules should be applied, and how to deal with
research where guidelines are skipped.":

Replicability is important because science is about finding objective mesurable relations. This makes the relationship independent of who performs the study. But this can be discussed/answered on another question :)

I am aware that we do our mistakes, (see my other question here on academia), but we should aim for the best behavior and the best science.
"Put another way, there are finite resources so the more you rerun
the same code the less scientific progress you make overall"

I don't think that we make less scientific progress overall rerunning the same code. Checking that we know for sure that A is true is far better than work for 3 years or more and then discover that A was wrong.
How many finite resources are/were used on studies based on those the ALS Therapy Development Institute couldn't replicate?
At the same time the induced pluripotent cells were hard to reproduce and replicate, but this isn't a software based, or the recent example of @tpg2114, 3 years to replicate their own study in 4 new settings.
Quality of academic software when sharing it, here it seems that it is better to share the awful, crapy code rather than hide it.
Necessity of the reviewer of the code and data was answered here. In short:

  Of course, the degree to which a referee is expected to verify the correctness of results varies greatly between fields. But you can always choose a personal standard higher than what's usual in your field. Just realize that good refereeing takes a significant time investment.

It seems that the comments are extending, and from the answers it seems that it is not the job of the reviewers or the journals, it might be a job for the reader (and of no one), or it doesn't worth it to make articles reproducible because it is too hard.

There are multiple answers to your question.

Academic publishing assumes good faith. At least in the circles where the majority of people are genuinely interested in the advancement of science. This is the only viable mode of sharing scientific information between adults, although it sometimes fail as we all know it. Publishing should firstly serve the purpose of communicating results in a fast and convenient manner and second provide some sort of quality control.
Sharing code and data is not a necessary condition for a study to be reproducible. It surely lowers the threshold of work that has to be done by other groups to reproduce the results, but clear and comprehensive descriptions of the methods and algorithm, as well as how the data was gathered, suffice. In fact, it's even better since starting from scratch will avoid the reproduction of results that are due to artifacts in the implementation or the original data.
Acceptance standards vary vastly between journals. Nowadays anything can be "accepted and publicized" providing you pay the "article processing charge". The question is where was it published and by whom. The most prestigious journals in my field have strict guidelines about the study design and sharing of materials and methods, the other ones don't.


Contractions ("can't", "don't") in a mathematical paper I am refereeing a  paper (a good one) for a mathematical journal. The author repeatedly writes like this: "we can't do", "we don't know" etc. He is not a native English speaker, and this paper is his first paper in English.

Question. I am going to ask the author to change "can't" and "don't" to more formal "cannot" and "do not". Is that a right thing to do?

I am not a native English speaker either....

(Since a referee is supposed not to disclose their identity, I ask the question anonymously.)

My experience has typically been that the more formal mode, with no contractions, is preferred for most scientific publications.  It is not a terribly strong or important custom, however, and in one of my more high-profile multi-disciplinary publications, I actually found the copyeditor introducing contractions into my writing!

In short: worth mentioning, but not a big deal.  As a reviewer, you might say something like: "I found the contractions distracting, and would advise removing them" but I wouldn't recommend being much stronger than that in your statements.


Wrong proof in a research paper, will the paper be rejected? We submitted a research paper to a journal for publication and we received the reports of the reviewers. However, the two reviewers pointed out a flaw in one of our proofs. Unfortunately, we cannot find another proof and we cannot also find an exemple in which the result doesn't work. One of the reviewers said that we can remove the result. The editor-in-chief asked us to send the revised version as new submission. What we can do in this case?

First, notice that the question asked in the title has already been answered: your paper has not been rejected solely because an incorrect proof has been found.  So your real question seems to be "What do I do now?"

The obvious answer seems to be to do what you have been advised: resubmit the paper with the faulty proof removed.  To me an "unproved theorem" sounds a bit self-contradictory; although there are some things that you might want to informally describe that way, using that language in a paper seems to be asking for trouble.  Rather you should decide whether you want to include the statement that you now realize you cannot prove in some form, e.g. as a question or a conjecture.  If you think the work would be much more valuable if the statement was proved, you might want to delay resubmission while you make a more concerted effort to prove it.  Or you may decide that without the theorem you had, the paper is not in your opinion worth publishing.  All this is up to you.


Why are examinees often not allowed to leave during the start and end of an exam? I notice that, quite often, exams have a rule similar to this:

  You may not leave the exam theater during the first ten minutes and last ten minutes of the exam.

I'm wondering what the purpose of this rule is. In the first ten minutes presumably nobody would have finished the exam, but I don't see why that should stop anyone from leaving. As for the last ten minutes, if I had to guess, it's to prevent an "arms race" where examinees race to leave before everyone else so they can avoid the traffic jam at the end of the exam. However this hardly seems like a deal-breaker. There're also exams where nobody can leave the exam theater until the exam is over, and usually the end of those exams aren't a complete mess: examinees just wait until scripts are collected and then leave. Besides, having this rule just pushes the "arms race" to ten minutes before the official end.

What is the point of this rule?

Well the 10 minutes at the beginning is to allow some to arrive late without the possibility of collusion.

Where I work, it is 15 minutes at the beginning just for any who are late...

The 10 minutes at the end is probably to allow those rushing to finish a quieter time to concentrate - most students leaving manage to make noise - chairs scraping etc


Is there a community driven unified article database? I am using Mendeley to keep track of my papers. It allows me to group the papers in folders, and I can easily export BiBTeX for a folder which I can include in a paper I am writing.

However, almost always I need to fill in all the details when I add a new paper to my library. "Search by Title" feature does not do a great job.

I think everyone around the world is creating their BiBTeX (or any other format) entries by hand. Is there a community driven (wikipedia like) website/service that unifies this process?

What I have in my mind is something like this: People add article meta information (title, authors, year etc.) to this public DB, if they see a mistake they correct it, if they see duplicates they prevent it by deleting one. And one can export entries as BiBTeX, etc.

The closest thing I saw is Google Scholar. But because it tries to automate nearly the whole process there are still lots of mistakes.

Sadly, not yet...

Many publishers view their bibliographic metadata as commercial property and hold-on to it fairly tightly.

Mendeley will release little bits of the article data they have accumulated from all their users, but they will not let anyone download all of it - it's valuable property that they want to keep 'in-house'.

There are a few truly community-driven projects trying to change this e.g. Open Citations & Open Citagora.

These projects aim to build truly public & open databases for anyone to build upon & annotate. The other tools mentioned in the question aren't really public or fully open.


Funding from Advisor This semester, my advisor supports me financially from his NSF funding. So I was wondering if I can write this NSF funding in my resume in honors section?

It’s not an “honor” to be funded by a normal NSF grant, or any other grant. It’s how you got funded, and is not something you can typically claim as an “award,” because it doesn’t represent you specifically. The only exception to this would be if you were somehow involved in the preparation of the grant.


Do Australian universities pay expenses to attend a faculty interview? I have been invited for an interview for a lecturer position at a university in Australia. I am based in Europe at the moment. It is not expicitly clear, at least to me, in the invitation email that they will pay for the travelling and accommodation expenses, whether in full or in part. I thought I should ask them for clarifications, but I am not sure how to ask it, and perhaps it is better to find out more about the custom before asking.

The short answer is 'yes'. I know some colleagues who were invited for an interview for a lecturer position at an Australian university and they were indeed reimbursed for all their travel+accommodation+food+visa procedure expenses for the trip. The reimbursement was not conditional on if they would accept the job if offered or not. It was also written clearly on their invitation letters (needed for their Australian visa application) that they would be reimbursed all these expenses.
However, you must NOT assume anything. It is going to be a good amount of money travelling from Europe to Australia, and you must clarify about your reimbursement.


Is it OK for graduate students to draft the research proposal for their advisor’s funding application (like NIH’s or NSF’s grant application)? Is it appropriate (I type 'common' in the original post)for graduate students to draft the research proposal for their advisor’s funding application (like NIH’s or NSF’s grant application) ?

in the field of Biomedical research.
major grant proposal, like NIH's or NSF's)
Is this behavior allowed? Although it is OK and somewhat common for graduate students to draft grant proposal in our country, I'm not sure the situation in US or Canada. I do not know if I should write this thing in the personal statement for PhD application.

In experimental fields, this is not exactly a routine practice, but it is not rare either.  Especially in a sizable lab with a large number of graduate students, multiple grants are needed to support all the work going on.  It takes a substantial amount of time to prepare a grant proposal, and most proposals are not funded, so working to get grants can be a major drain on a PI's time.  If a graduate student can do some of the work, that may be the most efficient use of laboratory resources.

And an experience graduate student is likely to be the person with the best practical understanding of what precisely they are doing in the lab.  The student should understand the significance and the challenges of what they are planning to study further, and including that specific knowledge can help to make the best case for funding a proposal.  That being said, I would not expect a student two write an entire proposal (including all the parts of the proposal describing logistics and budgeting), nor would I expect their discussion of the research aspect to be used without substantial editing by the PI.

Moreover, regardless of what career path they eventually take, it will be important for the students to be able to explain cogently what they are working on and why it is important.  Having a student write a draft describing the research they want to undertake may be a good way of teaching these skills.


Request for high res figures: what should I be mindful of? A researcher in my field has written to ask me high resolution files for 5 figures from 3 different papers of mine. He states:

  Currently I am revising one review article where I have used several figures from some of your excellent papers. Due to the editor and the reviewer ask me to provide them with high qualities.

I see no problem in sending him the figures in high resolution. One thing is worrying me slightly: if you write a review with 5 figures from someone else, it's either a very long review, or you may simply not be the right person to write it, it seems to me. Should I be worried about plagiarism?

So, when I write him back, and presumably send him the request files, what should I be mindful of? I see the following (nonexclusive) options:

Ask to know a little more about this review.
Give him links to my few very recent articles related to this topic, trying to make sure he's not forgetting anything relevant (some papers are only a few weeks old, so it is understandable that they may not have appeared on his radar yet).
insert here others options I haven't thought of

What I will definitely do anyway:

Ask him to send me the review once it's published.
Remind him that he needs copyright permission from my papers' publishers, in addition to my files.

if you write a review with 5 figures from someone else, it's either a very long review, or you may simply not be the right person to write it, it seems to me.

Or you just think that person has amazing figures.  :-)

If the author's university and the journal publishing the review are both reputable, then I doubt you have much to worry about.  If they aren't, then it is more worrisome.  If the author hasn't already specified where the review article has been submitted, then that's strange in itself, although it could be awkwardness rather than dishonesty.

There seem to be two issues here:

Will it be a mediocre review article?  There's not much you can do about this: you presumably can't stop the article from being published, so the only question is whether the world would be better off if it didn't include your figures.  (That outcome would be worse for you, and I can't see why it would be better for the rest of the world, so I'd be inclined to give them the figures.)
Is there no actual review article, and this is just a setup to get copies of your files for use in plagiarism?  It would seem crazy to draw your attention if there's plagiarism involved, but sometimes people are crazy (or it could be someone using a fake address or hacked account).  I wouldn't worry about this too much: the chances of plagiarism are not so high, and the chances the plagiarizer will actually get away with it are even lower.  Besides, you might end up with an amusing story about the time a plagiarizer asked you for copies of your figures.

  Remind him that he needs copyright permission from my papers' publishers, in addition to my files.

Definitely, and you could even cc the permissions e-mail addresses for your publishers, to help speed the process along and make sure the author doesn't forget or lie about it.


Is it fine to submit a paper to a journal via arXiv without updating on arXiv? I have uploaded a preprint of my article to arXiv and it is published there. After that, I made several changes to it and I am submitting the same to a journal which allows submitting via arXiv (Physical Review E, to be specific). My question is, is it okay to submit the article without updating it on arXiv because I am submitting via arXiv?

If I understand correctly, the answer is "no" and seems to be obviously so.

The journal needs the latest version of your manuscript.  The journal will acquire your manuscript from arXiv.  Therefore, you must put the latest version of your manuscript on arXiv.

In any case, there seems to be no reason not to update the version on arXiv.


What is the etiquette for using empty desks in a communal grad student office? I will soon be visiting a friend who is a graduate student.  She works in a communal office with around 50 other desks (which are mostly occupied by other grad students).  Is it appropriate for me to study at an empty desk?

Think of it like visiting somebody else's house.  Your friend is your host, but also shares her "house" with a bunch of roommates.  She is the one who will know best what sort of etiquette is followed in her community.

Why not ask her, "Where would be a good place for me to study around here?"  You might get sent to one of the desks, or to an empty meeting room, or the student lounge, or the coffee shop down the street.  There's no way to know without knowing the lab culture, and your friend is the one in the best position to judge.


Asking a professor whether my application has been accepted or not I applied to a university which has offered acceptance letters to a few students so far. What would be a polite way to ask my professor whether my application has been accepted or not by the review committee.

When a department decides to accept someone, they try to tell them as promptly as they reasonably can (sometimes they need to get administrative approval or the like), so delay indicates that a final decision has not been made.  If you haven't heard anything, you can assume you have not been accepted yet.  It's theoretically possible that the acceptance e-mail got caught in a spam filter, but that's probably not likely enough to be worth worrying about.

If you reach the point where large numbers of people have heard acceptances and rejections, but you have heard nothing, then it's worth asking about your status, just to make sure there wasn't a communication difficulty.  It's also worthwhile if you are facing an upcoming deadline and hope for an answer before that point.

However, if just a few students have received acceptances so far, then your best option is to wait and see what happens.  Asking for a status update will likely just lead to a response along the lines of "Sorry, we haven't made a final decision yet.  We'll let you know when we do."  (And asking more than once is likely to annoy the committee.  It's better to save your request in case it matters more later.)


During a PhD, what should I do that is not research? I am PhD student finishing my first year in Computer Vision. While I take my research seriously, I was wondering what I could (or should?) do that is not research. I can think of very different things:

Studying related subjects that do not directly benefit my PhD as Natural Language Processing;
Studying completely different subjects that interest me: Finance, Chinese, Management, etc;
Go to the gym;
Sleep more;
Play PC games;
Watch movies;
Travel;
Look for jobs for after my PhD;
...

So far, I have been focusing on research during the week, and if I'm tired of it during the evenings or the week-end (which is usually the case), I just rest or read a book.

Not sure if this is being lazy or having a good life-work balance, but at least I am still very motivated and things are going not too badly (I am quite close to completing the key experiences of my first paper).

So, what should I do?

As the comments say, do what you want.

It is your free time. There is no meed to sacrifice it to your PhD. Otherwise you might later end up feeling that you have "wasted" time, as in this question. Your research work seems to be going well, so there is also no pressure to put in more hours.

There is no need to optimize every aspect of your life. Try out those things you have mentioned, see what works out for you/what you enjoy more. We cannot make that choice for you.


Should a Database Update be sent for publication in same journal where previous edition was published? My lab published a database (db) two years back in Nuclear Acids Research. Now looking at the increasing data and new features we are planning to update the db. but the db admin is leaving now and I have taken full charge over it.

Is it mandatory for us to send the update to same journal (so as to increase chance of acceptance)
What authorship may I expect? (1st or 2nd)

Nothing ties you, neither ethically nor legally, to publish your new work (your database update) in the same journal as earlier work on the topic. However, if the journal was a good venue for this particular publication some years ago, the same reasons probably still hold, which means it's still a good place to publish your update. If, however, you feel like changing, just go for it!

Regarding authorship, this should be discussed right now. If you have full charge of the database, did important work on it yourself, and write the paper, then you have strong arguments to be first author. On the other hand, if you're the new admin but contributed little to the recent improvements, your position is weaker. In the end, it will be the result of a negotiation.


How to deal with a setting where some students come to synchronous class unprepared? With Online Learning, I have prepared recorded videos that are equivalent to lectures. Therefore, I was planning to make the module more interactive. However, it is often the case that only 15% of students watch those lectures, 35% have watched some of the recordings, 20% attend online but have not watched any videos while the rest just never attends (until the last couple of weeks just before the coursework submission and they start to stress) a synchronous session in the morning.
Although I always send emails informing students that it is quite important to watch these videos so that the class discussion will be positive and impactful for their understanding, I always end up with some students who have not done their homework essential for our synchronous discussion.
Now, I know that some of you will say that it is those students responsibility to worry about their learning outcome. As a teaching lecturer, those students' satisfaction is important, and if they are not happy with such an arrangement, I am worried.
The problem is like in all democracy areas, and some students love this approach others do not. I find it difficult (and stressful) to please both extreme parties, especially that many do not wish to show their faces in online learning.
As you know, some like to be passively taught, i.e. using old lecture-style way where the lecturer do the thing online without student interaction unless they have a clarification question. I am currently having this issue where I do not know how to make the majority of students happy and learn actively.
I really value any good advice, suggestions, previous experiences you may share are highly appreciated by both students and teachers.

This is the online version of the flipped classroom, of course. But, I suspect that a lot of your students aren't familiar with the concept or how to behave. Like most everything else, you need to teach them what their responsibilities are. Probably they are most used to being "told things" and then working on their own. But that won't work here.
One possibility (the stick) is to hold a quiz at the very start of each synchronous meeting, based on the readings. Another is to start out asking individual students to respond to a question of yours. This could be at any time during the class.
But you should also probably publish a sheet that describes the expectations and what will occur (and what won't) in the online sessions.
To put a bit of carrot along with the stick, you could make the quizzes count "extra" toward their grades, so that answering correctly add something, but incorrectly doesn't penalize them. This works with the more motivated students, of course.
But the normal flipped classroom is normally a problem solving session where the problems are based on the previous readings/videos. These normally form the basis for a part of the grade, perhaps substantial. The face sessions aren't just for questions, but might begin that way.
But you probably need to make "coursework submission" more regular, so that it doesn't just come at the end. Students are busy and will ration their time and effort within the parameters they see. Tighten the parameters to see different behavior. Whether they "like it" or not is less important than if they learn something.


Should the slides in a presentation be self-explanatory or be as minimal as possible? When you do a research presentation, what is usually the focus that you take.

Some professors tell me to make the slides as self explanatory as possible, and I quote:

  Someone should be able to understand your slides without you being there

To me, this approach seems counter intuitive to the principle of a "talk". After all, you already wrote a paper that meets that objective.

Other people, for example in things like TED talks or (please bear with me) presentations by Apple, have very bare bones slides, where they only focus on transmitting the main message of the talk.

What is your take, should the presentation be made as didactic as possible or just a cold transference of information?

I would say the two most important points are to make slides you are comfortable with and not to limit your oral presentation to reading your slides.

Furthermore, if you are presenting a research paper, i.e., where more written material is available to the audience, then the objective is usually to make people want to read your paper, instead of explaining the entire paper in 20 minutes.

Some people prefer to have full slides, arguing that when members of the audience are not understanding English very well, it can help them to have both the oral presentation and the slides, especially when the speaker does not speak a perfect English. It is also helpful for members of the audience who got distracted at some point, and who can quickly read where the speaker is. Other people prefer minimal slides, arguing that having both the full text and the oral presentation might confuse the audience. In particular, whenever a slide is displayed, the audience tends to read it immediately, and during the reading, to be less receptive of any spoken words.

In other words, the only "bad" presentation would be to have full slides, and to limit your presentation to reading them, because you become basically useless. However, you can have long slides, as long as you consider them as an aid for the audience who haven't followed what you said (for whatever reason), and not as your script to read. You can also minimal slides, containing only the key points. In the end, you need to be comfortable with your slides, and to give a presentation like one you would like to attend.


Order of authors for a tenure-track assistant professor in the USA: second author after Ph.D. student or last author? I am a second-year Assistant Professor in an engineering department at a US university. I did my Ph.D. in a non-US university and post-docs in the USA. I have a two papers that my Ph.D. students are about to submit, with 5 and 7 authors respectively. A Ph.D. student of mine will be first author in each of those, since he contributed the most, no doubt whatsoever with this.

But what is best for me? I am definitely the person who contributed the most after my student. I had always assumed that I should be the second author. A colleague in Europe told me, however, "Are you crazy? You should be the last author of the list, which is the most prestigious spot after the first author! The main PI or person who helped most the student is always the last author in the list!" So now I am doubting my choice.

Where should my name be on the list, given that I am the main PI and I helped the most? I know it is surely not the main factor for tenure, but I'd like to do this in the most correct way.

The answer for appropriate author order is very dependent on the culture of your (sub)field.  For example, if you are a computer engineer, you should probably be second author, while if you are a biological engineer, you should probably be last author.  Follow whatever you see others doing in the venues where you are submitting.

That said, these days it is often possible to make the contributions explicit so that there are no questions about contribution.  Many journals now request or require an "author contributions" section that attributes specific work to specific authors. Even if the venue that you are submitting to does not have such a requirement, you can still  add that information into the acknowledgements section.  Furthermore, the CRediT taxonomy provides a set of standard widely-recognized roles that are useful for describing such work.


What is a computer science conference, really? I understand that in the field of computer science, publishing in a conference is the default, as opposed to other fields where it's normal to publish your research in a journal. But does the word conference here carry the same meaning as it does in other fields?

If your paper is accepted in a conference in computer science, does it simply mean that it will be published in a proceedings rather than a journal? Or does it really mean that you have to travel to a physical conference and present your work as a talk? If the latter, what happens if you have multiple papers accepted at different conferences in the same year but can't afford to travel to all of them? I imagine that in this situation, trying to publish any work would result in a scheduling nightmare, both on the part of conference attendees and organisers. If this is the case, how did this situation arise and why is it allowed to continue?

Or have I got the wrong end of the stick and in computer science, the word conference is just a synonym for journal?

Most computer science conferences expect that, except in extraordinary circumstances, at least one author will present the paper in person. The paper is also, in most cases, published in the proceedings, possibly on paper and distributed to some set of people, such as a special interest group.

The reason for this is that we highly value collaboration and face to face conferences give us a chance to sit and talk as well as interact with authors.

If you publish in a lot of conferences you need to plan for the travel. Grant funding is one source, as is university funding. I think that personally funding your travel is not especially common, but possible.

Note, also that many conferences attendees work in industry, not academia, where they do research of various kinds. It is common to see folks from IBM Research, or Microsoft Research, for example at many ACM conferences. They are funded by their companies.

One option for a prolific publisher (we should all be so lucky) is to do a lot of collaborative work so that if you can't attend, say, SIGPLAN POPL 2021, then one of your coauthors will be able to.

But no, it isn't just another way of saying "journal".

I should also note that quite a few people attend such conferences even when they have no part in the program. They are just there for the collaborative opportunities and for informal meetings.


When reviewing a manuscript for the second time, is it fair to comment on aspects I did not realise the first time? I refereed a manuscript and recommended a major revision.  Now, almost three years (!) later, the manuscript has come back to my desk.  The editor told me to treat it as a revision and not as a new submission.  However, since I don't remember the details, I'm re-reading the entire manuscript.

I'm noticing things that I consider need to be improved.  That includes things that were identical three years ago, but that neither me nor the other referees commented on.  There could be several reasons why I didn't comment on it the first time:

I had less knowledge and experience than I have now, or
the field has moved on since it's been so long, or
I simply didn't notice something I noticed now.

Is it fair to comment on it now, or did I lose my chance to suggest this improvement when I didn't suggest it in the first round?

On the one hand: I genuinely believe this needs to be improved.

On the other hand: if I were submitting a revised manuscript, I would not expect referees to comment on things they should have commented on the first time.  If nobody comments on a particular paragraph, I would assume all approve.

I believe that it is entirely reasonable to make major requests of a manuscript on second review, as long as it is maintaining your basic standard for acceptance rather than moving the goalposts.

For example, I have had the experience where things about a paper were very unclear to me in the initial review because of shortcomings in the authors' presentation.  Upon revision, those things became much clearer---but not in a good way.  The extra information shed light on serious flaws in the authors' work, which has led me to in some cases recommend further major revision and in other cases recommend rejection.

On the other hand, some reviewers seem to like asking authors to do entirely new work, not because it is necessary for publication, but because the reviewer wants to know the answer or thinks it will make "a more interesting paper."  This happens most frequently with "glamour" journals.  I believe this sort of "moving the goalposts" on publication is not appropriate even in the first review, and doubly so in a revision review.


Using first person in literature recommendations in a masters thesis? I am currently writing my masters thesis in computer science. I've heard that one should avoid writing "I".

In cases where one describes what was done and it doesn't matter who did it, I understand why writing "I" should be avoided. I, however, wonder if it is ok in the following case:

In the following, it is assumed that the reader knows XYZ. In case
the reader needs a refresher on any of those topics, I recommend ...

It is a subjective statement which is not necessary, but might help students who might in future read it. I should probably point out that a CS master thesis is expected to have about 80 pages, hence length-wise it doesn't really matter. It should be clear that it is subjective; if I changed it to the passive (it is recommended...) then it sounds as if there is a consensus in the community.

Some people recommend writing "the author". It, however, sounds strange and it is absolutely clear that "I" is "the author". Hence I don't see an advantage in doing so except for beating automatic tools / grading sheets.

Unless there is some reason to specifically avoid it (e.g., your have an advisor who absolutely won't tolerate it), feel free to use the first person and "I" statements in lieu of traditional academic language like "the author" or a strict adherence to the passive voice. Your readers presumably already know you are the author. Anything you can do to improve their comprehension of your work is worth doing. Plus, as this editorial in Nature suggests, "Personal language builds a connection to the reader and helps, ultimately, to persuade".

As for the literature suggestions, a separate section for providing some brief background explanations may be helpful. You can use such a section to include context along with references to the further reading.


Saying no to student requests for excessive appointments and help solving homework I am relatively new to teaching University undergraduate classes in mathematics. One of the harder things I've had to do is to say 'no'. To somehow respectfully deny a student what they're asking for.

For example, very recently, a student has been demanding too many appointments outside of office hours and during these appointments, the student asks me to solve various questions for them and also almost entirely help them on their homework. As their instructor, I am certain that the student isn't actually understanding anything, but is rather making me do their homework.

My question is, how do I tell them that their homework is not meant for me? Another question I have is, I feel like making compromises on my research time and family life to spend doing a student's homework doesn't seem like the best use of my time. So am I required to meet them outside of office hours? Or is it frowned upon if an instructor says no to meet outside of office hours?

I would limit the amount of time you dedicate to a single student to a maximum of 20 minutes a week. This is a reasonable amount of time to discuss the main problems a student has. This does not mean that you cannot make exceptions, but it is good to have a general rule.

As a side remark: You will not make everybody happy. If somebody wants an appointment and you say "no", and he insists, you can still say "no" and walk away.


Why are most universities reluctant to offer open-ended contracts to research-funded-staff (such as postdocs)? In some countries, labour law requires that if an individual has been employed on temporary contracts for a certain amount of time, the employer must offer them a permanent contract (or let them go).  They may be reluctant to do so when labour law stipulates they need a reasonable cause to fire employees; however, if a company cannot afford to hold on to people, they can and are let go.

Somehow, different principles seem to apply within universities, where postdocs¹ and other research-funded staff are often held on contract after contract, up to an entire career long.  The postdocs at my university want to persuade the university to offer postdocs a permanent contract, but with the understanding that if the money source for their salary runs out, they will be let go; just like employees in industry would.  I'm told some universities already apply that principle.  It would not increase the de facto job security for postdocs much, but it would open up the option of getting a mortgage for those who expect to stay in the same city for a long time.

Considering that universities could let go of staff if they can show they can no longer afford to hold on to them, why are they so reluctant to offer postdocs a contract that doesn't stipulate an ending date?

NB: to the best of my knowledge, this phenomenon is global; therefore I am interested in answers that are either generic or specific to a particular country

¹By postdoc I mean anyone employed by the university with a role primarily to do research.  Formally my employer calls this "research funded staff" but colloquially this group is referred to as postdocs regardless of age.

Using the term "postdoc" may cause confusion, because to me a postdoc is by definition an early-career researcher hired for a limited period.  But the question as I understand it has nothing specifically to do with the terminology.  It amounts to why universities don't offer long-term contracts conditionally on maintaining adequate external funding, but rather offer successive short-term contracts.

One answer is that sometimes they do offer long-term contracts.  In U.S. academic medical research, it's common to have long-term "soft money" positions for which most or all of the funding comes from grants.  There are even tenured soft money positions, in which you have a guarantee that you cannot be fired without good reason, but where there is no obligation for the university to pay the salary except as supplied by external grants.  (Sometimes they are responsible for a small percentage of it, and sometimes none at all.)  This becomes less common as you move further from medicine, but long-term soft money positions exist across science and engineering in the U.S., at least in small numbers.

Why not always do this?  One reason is to avoid raising expectations.  My impression is that it's rare to offer a long-term soft money contract unless there's a reasonably high chance that money will continue to be available for quite some time.  Even if there are no legal obligations, it's terrifically awkward to fire someone from a position for which they mistakenly believed funding would continue, and it's easy for people on soft money to be irrationally optimistic.  (You see this frequently with tenure-track jobs: someone starts by recognizing that they genuinely might not get tenure, but after a year or two their nerves have settled and they find it tougher to take the possibility seriously.)  This means there's a strong incentive not to offer long-term contracts that are too speculative.

Another issue is whether the department or university really wants this person to have a long-term affiliation.  There's sometimes a feeling that people on short-term contracts don't really count for the department's reputation, since they are just visiting anyway, while people on long-term contracts count more.  This means other faculty members have more of a reason to exercise oversight.


Supervisor has suprevisees do peer reviews for them – what are the ethics of this? From Jan van Deursen’s bullying: lab members speak out:

Not everything in Jan’s lab was bad and I think it’s also important to point out that my relationship with Jan was often professionally respectful. For example, Jan repeatedly asked me to peer review manuscripts that he had received from various journals from all impact levels. The level of trust was high. Jan would give me his log-in and password. Our routine was that I’d submit reviews for manuscripts without him reading either the manuscript or the review that I wrote; it was completely hands-off. Honestly, I quite enjoyed this, although my work was always claimed in Jan’s name.

The scientist in question seems to see little wrong with that. Can you provide an ethical analysis of this behaviour?

It isn't inherently wrong to give younger members of a research group reviewing assignments (it's a legitimate and commonly used teaching tool when mentoring younger scientists), but there are two points that are definitely ethically questionable:

The review is in his name because the person quoted uploads it in his name. That's deception: The editor expects the review to be from him, in hopes of tapping his experience, but gets nothing of the sort. The younger scientist also doesn't get any credit.

There is no teaching element in all of this. Yes, there is trust, but if he never read these reviews, he can't give feedback to the younger scientist on what they could do better.

When letting younger scientists do these reviews, I often do take their (final) review after we talked about it in some detail, and prefix it by saying something along the lines

The following review was prepared by one of my graduate students. That said, we discussed it in detail, and while the words are those of the student, the conclusions are ones we share and that I believe appropriately reflect our views of the paper.

This way, the student gets to learn, and we together provide a review that meets the expectations.
In other words, I find the behavior exploitative and ethically questionable.


How should I respond to a professor's email following up on an offer of admission? I am a final year undergrad and applied for graduate programs in various universities for Fall'16 admission. I recently got an admission offer from one of the programs. The admissions chair cc'd the offer email to potential supervisors I mentioned in my application. Here's the email from one of these potential supervisors.

  Dear xxx,

  just to follow on Dr. xxx's invitation to xxx University: I was very
  impressed with your record and ambition, and would be very interested
  in having you join my group. I am looking for very motivated and
  strong students at the moment. I have been working on various aspects
  of xxx, with my students and postdocs at xxx University, and in
  collaboration with colleagues in xxx University and xxx University.

  You can read about my recent research at my webpage: xxx or check some
  of my papers on the google scholar: xxx

  Please let me know if you have any questions about living and studying
  here in xxx. I think we have a very lively and a friendly department,
  in spectacular surroundings.

  Very best from xxx.

This is my first admission offer, so I'm waiting for offers or rejections from other places. So, I'm not really sure how to respond. And even if I did want to work under his supervision, what questions do I ask to begin with? I'm totally lost.

Well, the potential supervisor explicitly mentions "Please let me know if you have any questions about living and studying here in xxx"...just email him/her if you have any such questions. If you are waiting for offers/rejections, I think a polite reply stating the same would be alright.

If you are excited to work with him/her because of reasons X,Y,Z, just mention them in the email. In any case, it is highly likely that the potential supervisor understands your position (of waiting for all offers).


Do newly hired professors have to take a drug test before they start? In U.S., Canadian and European universities do new professors have to pass a drug test before starting their career?  Or is it only required when they are promoted to full-time tenure professors?

Is this a serious question? I would refuse to work anywhere where my employer would require me to do such a test. It is simply none of their business.

I am actually not aware of any (European) university that would require anyone to take a drug test. In fact, it would be illegal in many countries to do this (or at least, there are very strict rules about the circumstances in which it would be legal).


To what extent is the students' perspective on the lecturer credible? I am giving a master course with another colleague, but since I am more experienced in the subject, I took the most difficult lectures.
My lectures contain a lot of mathematical equations and require deep knowledge in algebra. I tried to make them as easy as possible and even made extra videos to explain parts which I felt were difficult. I checked all available lectures to make sure I explain well. Therefore, I find my lectures among the most intuitive and informative ones.
It seems that my students (or most of them) are not that good in mathematics and found the lectures very difficult. They are rating my lectures with very bad scores although I made a lot of effort in these lectures (I have been teaching this subject for several years) this year as they are online. I see my colleagues just recording their old lectures.
As a lecturer, I try to transfer knowledge, so satisfying my students is my priority. However, I feel that my efforts were not acknowledged and I have lost motivation to prepare good lectures. I am planning to simply record lectures and read the slides as most of the lecturers at my university are doing.
Did anyone go through this? Also, how informative is this evaluation to me? In other words, how credible is it to validate if there is really an issue with my lectures or if it is just a biased opinion?
EDIT
It seems that the students are comparing my lectures and the lectures of my colleague with whom I am sharing the course. I assume they think the difficulty of the lectures is related to the lecturer and not the topic.

Student feedback can sometime be a difficult thing for a teacher, and it is sometimes  inappropriate that teaching quality is measured in terms of student feedback.
Let me explain this by means of anecdotes. Imagine a colleague who is a good performer, much as a stand-up comedy act. They give good jokes, tell stories, show interesting films. How would many students rate them? Quite a few students might give them a good rating on the basis that they had a good time. However ask them in five or ten years time what they got  out of that class, and they might remember one of the jokes or stories.
Now imagine a colleague who works their class. Makes them do test and examples. Makes them go places that makes them think, makes their brains ache from the thinking they had to do. It is possible that quite a few students might really give some negative feedback that this was a class they did  not enjoy and might have liked to be changed. However, ask some of these students in five or ten years what they got out of that class and it might surprise you. It might be that they remember what they were taught and use it in their profession.
Good teaching can be preparation for the future and sometimes students can only discover that when they reach their own futures. I started to find this out when I would get unexpected emails saying "remember me". "I didn't believe you when you taught me that thing, and now I see that lesson playing out in front of my eyes every day. Thank You."
We have to balance those two aspects of teaching. We have to give them something for their now and something for their future. In fact something for our future and our grand-children's future, because that is what we build by good teaching.
As has been said by others: if you care, you will find ways to improve. You are doing the right things. Keep going. Best of luck.


How long after PhD Major Revisions sign off I got the result of major revisions following my second viva, and completed these changes, to resubmit a third time. Is anyone able to indicate the typical length of time for sign off following submission? The thesis went back to the examiner.

I have contacted the relevant administrative bodies to be told to wait. It's almost been a month.

Cheers

Edit: I'm in the Southern hemisphere (winter)

I can't answer the question per se (as I guess no other than the assessment committee can). But I can add my personal anecdote :)
At my University there is a general rule of 2 months assessment time (1st handin). But for me after about 1.5 month I got a mail saying that the Ph.D. School of my university forgot to send my thesis to the assessers.

In general I would suggest that revision should not take more than 2 months.


What does an optimal grading distribution look like? Researchers on education must have thought about this, so I hope to find some directions here. Suppose that I am grading students on a scale from 1 to 10. If I have no prior knowledge of the ability of the students but have obtained their test scores (let's say from 1 to 100).

Suppose these test scores have only ordinal meaning. A student with a higher score can be said to have achieved better mastery of the course but having double the score does not mean that one has achieved double as much as another student. We may also assume that a (statistically speaking) large number of students representative of the student population took the exam.

What should be the optimal grading distribution?

We may also assume that the grading distribution/scale should achieve two goals: a) it should be informative about student's grasp of the material, b) it should incentivize students to study the material.

Regarding a) from an information theory perspective, we may want to maximize the information (entropy) of the grade distribution. Thus, we would choose a scale which yields a uniform distribution. However, in practice most teachers implement distributions which are peaked. What is the motivation behind this?

Assigning grades to fit some "optimal distribution" is misguided.
We don't want to maximize the entropy of the grades in a particular course. It's not a very useful measure of a "good" set of grades. To quote from an answer by Anonymous Mathematician:

  Strictly speaking, Shannon entropy pays no attention to the distance between scores, just to whether they are exactly equal. I.e., you can have high entropy if every student gets a slightly different score, even if the scores are all very near to each other and thus not useful for distinguishing students.

(Note that this was in answer to a question that asked about using the entropy of exam scores as an indication of how good an exam is at distinguishing between different levels of mastery. It wasn't suggesting that grades should be curved a posteriori to maximize entropy.)

What we actually want is for grades to signal as closely as possible the students' mastery of course material. If every student in the course has achieved truly excellent mastery of the course material, they should all get high scores. This grade then seems to carry very little information. But in reality, it is much more useful to say that all students in this particular class achieved excellence and deserve a 10/10, than it would be to maximize the "information" carried by the grade and give some students a 1/10 because their performance was slightly less excellent than the highest level of excellence achieved by a student that year. This scenario (where all students achieve excellent or very good grades) is not even that unusual, as Michael Covington points out:

  In advanced courses, it can be quite proper for all students to get A’s and B’s, because weak students would not take the course in the first place.

For an individual student, the grade should depend on that student's demonstrated mastery of course material, and hopefully not at all (or as little as possible) on the other students in the class.

If you insist on thinking about it from an information theoretic perspective, what we really want is to minimize the Kullback–Leibler divergence between the distribution of students' achievements and distribution of students' grades.

If you have no information about the exam and what it measures, you cannot assign meaningful grades based on that exam score. If you know about the exam, you can assign meaningful grades based on exam scores, but not according to any optimal distribution - you would assign scores based on how much of the exam students are expected to know to demonstrate various levels of mastery, not by mathematically shaping the grades into some predetermined "optimal distribution."

  Edit: Suppose these test scores have only ordinal meaning. A student with a higher score can be said to have achieved better mastery of the course but having double the score does not mean that one has achieved double as much as another student.

Your edits are not going to change the answer; there's still not going to be an optimal distribution. If I have many excellent students in the class and I do an exceptionally good job teaching them, I'll give out many excellent grades, no matter how they rank with respect to one another. If all of my students are terrible and do poorly, they'll all get low grades even if one manages to get in a few more points than another (although in that case, I'll also take a closer look at the class to see why students are doing so poorly.) If half of my class excels and the other half fails to meet minimum standards, I'll give out 50% top grades and 50% failing grades. If their abilities happen to be normally distributed, their grades will be as well. You get the idea.

The distribution of student grades should follow the distribution of demonstrated achievements. Any grade distribution that doesn't is definitely not optimal.

The idea of grading students to some predetermined distribution (of any shape) is known as "norm-referenced grading."  For more information about alternatives to norm-referenced grading, see:

Sadler, D. Royce. "Interpretations of criteria‐based assessment and grading in higher education." Assessment & Evaluation in Higher Education 30.2 (2005): 175-194.
Aviles, Christopher B. "Grading with norm-referenced or criterion-referenced measurements: to curve or not to curve, that is the question." Social work education 20.5 (2001): 603-608.
Rose, Leslie. "Norm-referenced grading in the age of carnegie: why criteria-referenced grading is more consistent with current trends in legal education and how legal writing can lead the way." Journal of the Legal Writing Institute 17 (2011): 123.
Guskey, Thomas R. "Grading policies that work against standards... and how to fix them." NASSP Bulletin 84.620 (2000): 20-29.

These go into some more detail about problems with norm-referenced grading. You asked for a grade distribution that is "informative about student's grasp of the material." The literature I have cited explains that pure norm-referenced grading is not informative about that; it can only inform about student's relative grasp of the material, compared to others in the same group who have taken the same exam. In other words (emphasis mine):

  It can be useful for selective purposes (e.g. for the distribution of a scholarship to the 5 best students, or extra tuition to the 5 which are struggling most), but gives little information about the actual abilities of the candidates.

Source: McAlpine, Mhairi. Principles of assessment. CAA Centre, University of Luton, 2002.

In the middle of the 1990s, the Swedish secondary school grading system was changed from a norm-referenced to a criterion-referenced system. Thus it became possible to compare (for the same population) the ability of a norm-referenced grading system and a criterion-referenced grading system to predict academic success.

The first paper looking at this Swedish data set is not written in English. (Cliffordson, C. (2004). De målrelaterade gymnasiebetygens prognosförmåga. [The Predictive Validity of Goal-Related Grades from Upper Secondary School]. Pedagogisk Forskning i Sverige, 9(2), 129-140.) However, in a later paper, the author describes those results as follows:

  Cliffordson (2004b) showed in a study of 1st-year achievement in the Master of Science programs in Engineering that the predictive validity of CRIT-GPA was somewhat higher than it was for NORM-GPA.

In that later study, Cliffordson found (consistent with the earlier study)

  a somewhat higher prognostic validity for CRIT-GPA
  than for NORM-GPA.

and that across a variety of disciplines,

  Despite differences in both design and purpose, the predictive efficacy of criterion-referenced grading is at least as good, or indeed is somewhat better, than that of norm-referenced grades.

For details, see:

Cliffordson, Christina. "Differential prediction of study success across academic programs in the Swedish context: The validity of grades and tests as selection instruments for higher education." Educational Assessment 13.1 (2008): 56-75.


How should one proceed when they receive no job offers after a considerable amount of applications? I'm getting way ahead of myself, but being nervous on the job market I asked an advisor what happens should a candidate receive zero job offers. To which the reply was, "That never happens."

I'm sure that some people have had this experience before. I'm in the social sciences in a discipline that is very competitive with fewer than normal options outside of academia. I still have a ways to go time wise for job expectations, but I am curious about what options others may have gone for in situations where they either received no offers or none that were more appealing than something else that wasn't planned.

My assumption is that people will shoot for adjunct positions or similar options should nothing else come along, and try again in following years. Can anyone speak to being in this kind of position, or knowing someone who has gone through it?

Of course I expect and hope not to be in this position, but I am planning for everything. Others have told me that they apply for upwards of 70 positions in a year, which to me is insane (I don't know how assured I could be in the quality of that many applications). I have probably applied for 20-25 positions thus far, so I don't know if I should be approaching the process differently. And in the worst case situation, where to go from there?

Edit: Thanks all for your sensitive and helpful comments.

It certainly does happen. And when it does happen, people tend to leave academia for a job in industry, commercial sector, retail, etc.

Unfortunately, the current culture of academia still tends to focus on success stories and turns a blind eye to unlucky candidates, almost treating them as they never existed. Your supervisor's response falls is this sad mainstream paradigm.


Accidentally leaked the solution to an assignment, what to do now? (I'm the prof) TL;DR; I accidentally made the solution of an assignment visible to some of my students. How can I now fairly address that problem?

A few weeks ago I set a programming assignment to be done using Processing (a graphical programming tool), and to make sure the goal was clear I implemented a solution on openprocessing.org, which I made available to the students. On openprocessing.org, they can look at the working program (a little graphical game similar to tic-tac-toe), but the source code is hidden to them (I took a paid account to get private source code).
But then I embedded the openprocessing.org 'sketch' (a web page that displays the working program as described above) in a different web page, and failed to notice that the embedded version has the source code readily available (the person viewing the sketch just clicks an icon at the top and they get the editor with the source code). I think that's a bug with openprocessing.org and I complained to them (and there's obviously also an oversight on my part), but that's not relevant to my issue.

So basically the solution to the assignment was available to anybody who clicked that button at the top. It's not obvious, so I think only a few students noticed it. One team emailed me asking whether it was intentional and expressing their concern.
The assignment deadline is in 5 days (it's been up for 2 weeks) and it's the end of the term. This was supposed to be 10% of their grade.
I took down the visible solution, and I' trying to come up with a contingency plan. I could cancel the whole assignment, or give everyone full marks... Just let those who saw it submit as is (and indicate the source). I just don't know how to handle this best.

Any suggestions or recommendations?

Very simple actually. Abandon the assignment. Apologize for the error, but not for wasting people's time. Those who didn't find the solution and worked on it certainly learned something. Those who found the solution used their time otherwise and hopefully learned something else.

Mistakes happen.

If you use a large number of exercises in grading it is probably harmless to give everyone full marks. They will be happy and it won't really matter otherwise. But trying, in any way, to discriminate between various levels of "performance" on such an exercise is a minefield.

One thing to remember, however. Presumably you gave that assignment because students would be expected to learn some specific thing(s) by doing it. That may not have occurred, so you need to assure that you find some way to reinforce that lesson in some future activity.


Are the Hardy-Littlewood “rules” unethical? For the second time recently, someone mentioned to me the Hardy-Littlewood rules for collaboration (and on that very site). From what I read about it, they include the following rule:

  And, finally, the fourth, and perhaps most important axiom, stated that it was quite indifferent if one of them had not contributed the least bit to the contents of a paper under their common name

How is it ethical to be a co-author of a paper you have “not contributed the least bit to”?

I was flummoxed when I read that, it would be considered a serious breach of ethics in the communities I know. Is that a practice (those “rules”) specific to mathematics? Or are they just not used any more?

I've always interpreted such remarks as meaning that the individual papers were just progress reports on their larger enterprise, to which both made irreplaceable contributions, and that they had no interest in keeping track of moment-by-moment relative contributions.

In particular, "on average", there was no misattribution or false credit.

(Further, the "not contributed the least" may easily be hyperbole, just to make the point.)

For that matter, if one is in regular correspondence with another, how to attribute ideas that develop gradually? I think their solution was entirely reasonable.


Found an amazing source for a presentation. How do I avoid plagiarising it? Next week I am to hold a presentation in a master level course about kittens (a subject I knew very little about beforehand). I found an amazing book on cute mammals, in which the chapter on kittens contains all the information I need on the subject, while also containing numerous further sources.

Now, I am worried that if I simply rewrite the content of the chapter in the book into a presentation, I would be committing plagiarism. However, it seems senseless to dive into all these further research papers on the subject, when the book summarising it has already given me all the information I need.

How can I proceed to avoid simply plagiarising the book?

Acknowledge the influence clearly and appropriately.  Precisely what this means will depend on the specifics:

If you use direct quotes, then show them clearly as such — i.e. in quotation marks, or some visual environment clearly marking them as quotations.
If you’re using figures, acknowledge this in captions: “Taken from Miaow 2011, p.73”, or “Based on Miaow 2011, Fig 12.2”, or similar.
If you’re not directly quoting text or re-using figures, but major aspects of your overall organisation have been influenced by the book, then add a note saying this at the beginning or end: “Presentation heavily influenced by Miaow 2011, Ch.12” (or “based in part on”, “greatly indebted to”, etc.)  The bigger the influence, the more prominent you should make your note.
If your work will be advertised via an abstract, or similar brief description, and if the influence is particularly large — e.g. forms the main body of your presentation, not just one of several sections — then it may be appropriate to mention it in the abstract: “(This is an expository seminar, based in large part on Miaow 2011.)”

As long as the acknowledgement is prominent and accurate, then you are not plagiarising.  However, a couple of related issues to be careful about:

In some contexts, there’s an expectation of originality/novelty in your work.  If too much of your work is heavily based on earlier work of others, then it may not be considered suitably original or novel for these venues.
Copyright may also be an issue.  I’m not legally very knowledgable, so take this with a large grain of salt; but roughly, I think it’s likely to be a concern if you are either directly quoting a significant proportion of the text, or directly reusing figures/images.


Am I allowed to share Stack Overflow data along with a paper that uses it? I plan on submitting a paper that uses Stack Overflow data (contents of Stack Overflow questions, fetched using the Stack Exchange API) to a conference, and the conference is welcoming authors to share the code and the data used.
I saw some other papers that use Twitter data (Tweets) only share the tweet ID instead of the tweet itself, and they said that it is due to Twitter's privacy policy.
Does Stack Overflow have such a privacy policy?

The license information can be found at https://academia.stackexchange.com/help/licensing, which also has links to the terms of service.
That, in turn, has links to the API terms of service.


How to search in Google Scholar within a particular conference? Using Google's search operators, guide, we can restrict our search to that of a particular web domain, eg: site:twitter.com Paul Daniels

Within Google Scholar, can we perform a similar in nature search but for articles within a particular conference (or journal)? I am looking an operator specific to Google scholar which I expect would resemble conference:NIPS Paul Daniels

To search within a particular conference, go to the search result page (using an arbitrary search term), click on the small triangle that appears in the top row to the far right of the page and click on "Advanced search". This will open an extended search dialog where a field "Return articles published in..." exists.


Sharing Course Material With Other Lecturers I just received an email from a lecturer I do not know and have never had contact with, asking for my course materials.
On the one hand, sharing my course materials has almost no cost for me, and I have shared them before either "in house" (with lecturers in my department) or with close colleagues (coauthors/community friends etc.). This is the first time I'm encountering a request from a truly random stranger.
I am inclined to refuse this request.
I put in a lot of effort into my course material, and take pride in my work. Handing it over to some other person (who may or may not credit me) feels like I'm cheapening my efforts.
I am I just being prudish? Is this common practice that I just never happened to encounter? Is there a potential ethical issue with sharing materials that I am missing here?

Whether to share-or-not (assuming that you yourself, not your university, own the rights to what you've created) is strongly a matter of personal preference... I don't see a universal mandate.
Many years ago, I did pay careful attention to copyright control, and so on, but eventually I got the impression that it was simply not the case that people were clamoring to get their hands on stuff I'd written. :)
So, for some years now, I've put everything on-line with a Creative Commons license, and whenever anyone is polite enough to ask permission for use, I give it, without any negotiations. In fact, if one of my goals were to maximize the impact I have on ... for example, graduate curriculum in mathematics... unrestricted dissemination seems the obvious choice. True, I may not "get all the credit I deserve", but I already have "enough credit" to survive, so that'd not be a tragedy.
A situation where one should be more careful is when one's institution attempts to use-and-discard people who develop course material. In such cases, "getting credit" probably matters much more. Luckily, till now anyway, that kind of thing has not been toooooo much of an issue at my university, although arising sporadically over the years. (I'm not optimistic about the future...)
In summary: if you don't want to share the fruits of your labors, don't. You may change your mind later, and that's fine, too.


Contacting multiple professors for supervision I am an Honours student in the process of contacting professors and senior lecturers to request supervision/joint supervision.

So far, I had been in contact with a pair who were more than happy to supervise me, but after a meeting or two with them, I felt that
1) we probably would not click
2) their area of research, whilst on the outset seemed similar to my interests, is quite different.

So with that said, I have also been in contact with another pair.
These two seem extremely nice and supportive. I feel their research interests/expertise is more closely aligned with mine and that I would probably be better suited to working with them.

This is in Australia, so the semester will begin in about 3 weeks, and final supervisors are chosen in late march/early april - so I still have lots of time.

I wanted to know - should I flat out tell the first two academics that I am speaking to other academics, and may not end up going with them, even though the second set of academics are not confirmed supervisors?

Did I do anything ethically wrong? I feel bad for having had the first two (potential) supervisors have a phone/skype meeting with me + send me all their papers/manuscripts, if it was all in vain.

Finally, to add, would it be wrong to ask the first set of academics if I could be a TA for any of their classes, knowing that there's an 80% chance I won't be going with them as my supervisors?

Any advice is appreciated.

You should definitely shop around before selecting a research supervisor.  This is expected.  You do not need to declare it.  Just do not make commitments to more than one research team.  It is part of the faculty's job to compete to recruit honors students.  But prospective students have no responsibility to work for faculty until they agree to do it.


Why do people do postdoc(s) when they can already do research as a professor? I think PhD is the first time, mostly, when a person does original new work and in this process they gain the skills to do research. So, I was wondering why do people do postdoc(s) when they already have those research capabilities which they can practice even being a Professor or in Industries. Is there something else left to be learned?

Because the requirements for the majority of professorships are such that very few people can be considered serious applicants right out of their PhD.

Also, the number of PhD holders looking for a professorship far exceeds the number of available positions which creates a "backlog".

The two are obviously correlated since the higher the demand to offer ratio, the pickier the institutions can be.

So even in the case where people developed the necessary skills to conduct professor-level research and teaching during their PhD (which should not be underestimated, that level usually requires more experience than what a typical PhD can give), they usually need to spend some years conducting independent or less closely-mentored research along with students mentoring and teaching as a postdoc until they can secure a position.

Note that the majority of postdoc researchers never get a faculty position.