Professor I applied to is about to move – can I ask them to consider my application for the new institution? I am in the process of applying for graduate programs at various universities. Given the importance of research in some graduate programs, I have been searching for professors/potential mentors when I came across a particular professor whose work impressed me immensely. I got in touch with the professor to discuss my application.

Now this is where the tricky part begins. The professor informed me that they will be moving to another university shortly and will not be accepting mentees anymore at their old university. Luckily, I had submitted my application for their new university a few days back. Is it okay to ask them to consider my application as a part of an application different from the one I had initially approached them for? My desire to carry work under them is genuine but will doing something like this make me look too opportunistic of unscrupulous?

It is absolutely not a problem for you to ask for help!

Faculty move is part of academic life and often times one of the trickier things to handle – especially when figuring out how to handle relocating a lab full of people. Your interest in their work is not tied to where their lab currently is, at least as far as you describe it, so it is fully acceptable for them to advise you on the application process.

Regardless of their affiliation, their role has been strictly advisory (as described). This means it is as if one professional is simply giving advice to someone entering the field – there is no conflict of interest.

Continue, and if that professor’s research excites you, you should certainly try to get into their new university and rotate with them to see if it’s a match.


Medium-quality English conference vs. Higher-quality non-English conference As a first-year masters student in a non-English speaking country who is considering to later continue to study Ph.D. abroad (US or Canada), which option would be more desirable? Publishing in a medium quality (locally held) international conference which is in English (and indexed by IEEE Xplore) or a higher quality (local) non-English conference or journal?

Clarification: neither conference is top by international standards. It's a question of comparing two nationally known conferences where the English one has less national reputation.

Which conference to publish in depends on your goals for the publication:

Conferences can be extremely valuable networking opportunities, and speaking at a conference puts your work in front of the audience of that conference.  If the non-English venue is a community that will be valuable for you to connect with, then publishing there can be extremely helpful with building professional contacts, getting into a good Ph.D. program or getting a good job, etc.  Note that this may apply even if you're planning to study abroad later, as those colleagues may have overseas contacts.
On the other hand, sometimes you are less interested in the interactions at the conference than in just having a "this is published" stamp and collecting citations for another line in your C.V.  In this case, it's not the conference itself but the online accessibility of the paper that's likely to be matter more to you, and it will likely to be more valuable to have it in English if your subfield is (like most currently are) English-dominated.

Note also that you may be able to gain the benefits of both by a follow-on journal publication.  If you are in a field where it is typical for conference publications to be upgraded into a more archival "extended form" journal publication (e.g., computer science), then you might publish originally in the other language, then follow up with an English journal publication, thus obtaining both sets of benefits, though at a cost of having the English version come out much later.


Motivating students to push their limits I think I must be stranger than usual sometimes, I always seem to take on topics that are somewhat more difficult than the mainstream, in very trying conditions - but the outcomes are very much worth it (not for me per se, but the benefits for everyone, potentially).

I try to instill this in my students, by 'gently' mentoring them and encouraging them to push their own limits a little further each time.  Also, I teach them that 'failure' is just another step to success.  For the most part, my students take on the challenges and the work, ideas and enthusiasm from them, frankly humbles me.

However, I am always wishing to learn new techniques to encourage my students to push, and even exceed their limits.

What strategies are most effective for encouraging students (and colleagues for that matter) to take on the difficult topics?

The most important aspect is the teacher's attitude. It sounds as though your students are already benefiting from yours.

As @Cinco says above,

  motivation is not a static, unchangeable property of particular students... A good teacher arouses the motivation indirectly, by creating the right environment for learning.

Based on my experiences with some awesome professors, I will say DO

hold your students to high academic standards.
assume that the students are capable of doing more than they are currently doing.
show them how the subject you are teaching is relevant to them.
be enthusiastic.
recognize their great work, and always expect more and better in the future.

Perhaps most importantly, have fun! Enjoyment is contagious, and a good professor can make it fun to learn about anything. A great professor can make it fun to struggle and push against the limits of our abilities.

(Sorry, this is rather subjective...it is hard to quantify what makes a great teacher!)


Is Relocating Necessary in Academia? Despite experiencing a lot of drama and negativity at my university, I love my city and hate the idea of relocating. Sometimes I even think of reapplying there just so I could stay in this city (this is its only university) and still attend grad. school, but the negativity would be a lot to deal with. There's another program that seems like a good fit for me, but I think I'd be miserable in another city, even if I enjoyed the program itself.

However, is relocating a necessary part of academic life? For example, with the job market being so tight, I've heard that you have to be willing to move almost anywhere for a job. I've also seen posts where Ph.D. advisors suggest their students apply to specific post docs/jobs etc. Can you specify that you refuse to move from a specific city? Is it even realistic to pursue an academic career if you're not willing to relocate (perhaps even multiple times)?

Edit- I'm from the US

There are exceptions in some specific fields (for example accounting) where corporate jobs are much more attractive than academic ones, but, in general, an academic considers themselves very lucky if they can find any academic job at all, let alone one in a particular city.


Does anyone monitor/support public-sector scientists? The government science sector is relatively small, but when you add up all the state and national departments and related organisations, it's a lot of people doing a lot of science.

Despite the strategic importance of public sector science, as far as I know there is no group responsible for the sector as a whole. It is no one’s job to support, connect or speak out for the highly diverse, often committed but sometimes isolated workforce within the government science sector. It is no one’s job to keep track of the sector, to share knowledge and work towards practical resolution of shared issues. This stands in contrast to the relatively well-organised, represented and funded science in academia. (Note that public sector jobs can be well paid and secure)

I would like to know if there are any organisations, initiatives or resources aimed at a) monitoring or b) supporting government (public sector) scientists, in any country.

One excellent example is the UK's Government Science and
Engineering profession. Well worth a look.
https://www.gov.uk/government/organisations/civil-service-government-science-engineering

What do I mean by government / public sector scientist?

is not employed by a university or college (what I think of as academia)
employed within executive arm of government, often a department e.g. Dept of Environment, Dept of Health, Dept of Agriculture
spends subtantial amount of job conducting research
generally not rewarded by academic measures of success and so in some sense decoupled from academic career structures (not saying this is good or bad)

What do I mean by monitoring?

Keeping statistics and recording trends in number employed, discipline, funding, salaries, career paths, impact on public good or economy etc (while not perfect, there seems to be many reports and organisations tasked with tracking these kinds of things in academia and private sector R&D)

What do I mean by support?

The kind of work done by national academies of science (e.g. AAAS in the US, the Australian Academy of Science, the Royal Society in the UK) and disciplinary societies, professional bodies and the like. Note that their work may or may not be relevant to government scientists, but it is generally not targeted at them. Can anyone share an example of work by a body like this that is specifically targeted to government scientists?
Initiatives, policies, resources aimed at supporting career development and tackling issues. For example just about every university/college and many departments and institutes within them will have their own set of policies, initiatives and resources targeted to early career researchers, whether it's developing writing and publication skills, grant application training, outreach skills, building a career plan, finding a mentor etc.
An issue is that university and college resources, and the staff within them, are often active in the public domain. There are probably a lot of resources out there but government scientists may not be encouraged/authorised to have a public presence and their departments may not prioritise sharing what may be seen as internal resources with the general public.

Your questions appear to be asking about non-academic government scientists.

To answer your question about supporting science, yes groups exist that support them. The largest of which is probably the American Association for the Advancement of Science (AAAS) who advocates on behalf of scientists both in the United States of America and other countries as well. The mission and purpose of AAAS is to
advance science, engineering, and innovation throughout the world for the benefit of all people.

I am member of AAAS and a government research scientist. The news and updates section of Science includes both news about government scientists and what AAAS is advocating on behalf scientist and science.

To answer your question about monitoring science (at least in the United States), the Office for Personnel Management (OPM) provides oversight and standards for managing scientists across agencies (e.g., this public webpage lists some of their resources).


Advice on who to ask for a letter of recommendation for phd applications? I am currently in the process of looking for a phd position (in math). Almost all universities require three recommendation letters (some only require two, but ideally I'd have three) from professors. The problem is that I went through my studies rather anonymously and don't really know anyone. For one of these letters I am going to ask the advisor of master thesis which seems like a pretty clear choice with no real reason against it.
Possible options for the others would be:
-The professor who held the seminar I was in last semester. I got an A+ on my talk and he probably has more to say about me than someone whos lecture I was in.
-The advisor of my bachelor thesis. The thesis was apparently considered very good in terms of mathematical content, but a bit flawed as there were quite a few small mistakes left (typos etc.). I also got very good grades in all of her exams. Reasons against her would be that the Bachelor thesis was in a different area of mathematics, I haven't talked to her for 2 years and that the accompanying seminar talk of my Bachelor thesis was rather mediocre.
-Any other professor in whose exam I had a good grade. There would be a few candidates, but besides from the oral exam I never really talked to them.
Another point mentioning is that I have excellent grades, so I guess that these letters are supposed to focus a bit more on soft skills (communication etc.)?

I would put this as a comment, but I'm under 50 reputation, so here goes.
The first three professors you mentioned sound like your best bet. Thesis advisors can vouch for your ability to do mathematical research, which is the primary skill that phd programs are looking for.
It is not uncommon for people to ask professors who they only had for a class, though letters that say no more than "did well in class" are not very impactful. It is better if the professor oversaw some extended class project, or even better, a thesis. Remember, the phd admissions committees want students who are motivated and capable of doing research, not just doing well in the classroom.
EDIT: Additionally, I would not worry about the fact you have not kept in contact with your undergraduate thesis advisor. This is surely a common scenario.


Structure of a dissertation with two (fairly) disjoint topics I am writing a PhD dissertation that contains two main themes/topics. These topics are fairly different from each other, but they do have (some!) common threads.

Within each theme, I have two rather related sub-themes. Each sub-theme is substantial enough to form a chapter.

How should I structure the dissertation. I was thinking about having two parts, as follows:

Ch.1 - Introduction (discussing general structure & motivation)

Part I - Theme 1

    - Ch.2  - theme 1 - topic 1
    - Ch.3  - theme 1 - topic 2

Part II - Theme 2

    - Ch.4  - theme 2 - topic 1
    - Ch.5  - theme 2 - topic 2

Ch.6 - Conclusion

Appendices and References

The above structure seems a little odd to me, though. Are the purpose of parts to partition the paper completely? That is, should each chapter belong to a part? In the above structure, Ch.1 and Ch. 6 are not in any part.

In addition, would including an introduction and conclusion for each part be appropriate?

My recommendation is to consider "parts" as an auxiliary notion. The thesis should make sense to the reader even if he ignores the division into parts.

That's fairly doable with your proposed solution, it just needs clever organization of introductory and preliminary texts.

Actually, I don't think you can do much better if your 4 chapters are too long to become 2 chapters.

The only alternative I can think of is the following:

Ch.1 - Introduction (discussing general structure & motivation)

Part I - Theme 1

Ch.2 - theme 1 - deeper introduction & preliminaries
Ch.3 - theme 1 - topic 1
Ch.4 - theme 1 - topic 2

Part II - Theme 2
Ch.5 - theme 2 - deeper introduction & preliminaries
Ch.6 - theme 2 - topic 1
Ch.7 - theme 2 - topic 2

Ch.8 - Conclusion

Appendices and References

Also, as a last remark, if you realize there's nothing to put into the conclusions, I'm quite sure you can create the thesis without them, but better ask your supervisor.

Actually, have you discussed this with your supervisor?


Error in the motivation letter I sent my application to the University of Zurich for my masters studies. However, I just realized that I made a really big mistake in the motivation letter. In the first line of the letter I wrote something like, "With this letter, I would like to express my interest in studying Masters of Science in Physics at the University of Geneva starting from fall 2017."
Does this hampers the chance of getting an admission?

There is nothing you can do about this any more, so it's not worth your brain and emotional power to worry about. Spare your brain for things you can affect.

That said, having seen such mistakes many times in applications, they do seem to suggest a lack of attention to detail. I wouldn't say that we've ever rejected an application because of a mistake of this sort, but they do get noted if they fit into a bigger picture in the application. If you are convinced that your application is otherwise good, then you will not likely have to fear any detrimental effect.

(I'm going to add that everyone who sits on selection committees knows that applicants apply to many different universities. While these sort of mistakes should not happen, we understand that they do and why.)


What are potential downsides of (universal) author IDs pushed for by publishers etc.? In recent years, several organizations (publishers, arXiv, universities) started pushing for systems of a reliable author identification, gaining considerable traction with the recent launch of ORCID. This works by assigning IDs to persons. In some cases, the person itself can then connect his/her articles to the person ID. In other cases, publishers ask / plan to ask for the ID upon manuscript submission.

Examples:

ORCID (supported among others by Spinger, Elsevier, American Physical Society, American Chemical Society, IEEE, Institute of Physics)
ResearcherID by Thomson Reuters
Scopus Author ID

There are some obvious advantages of a precise and machine-readable author identification. These pros are strongly advocated by the big organizations, which are of course very interested. But what about the cons? Before all researchers become obliged to using such IDs, we should discuss the cons and potential problems.

What do you think and what are the biggest potential disadvantages for the authors? Do you know some nice article / blog / discussion about disadvantages?

Related texts:

http://scholarlykitchen.sspnet.org/2009/03/11/the-author-id-dilemma/
http://blogs.plos.org/mfenner/author-identifier-overview/

Your question is long and somewhat argumentative. I'll answer here to a small part of it. You say:

  “Are you sure that you will still be proud of your last paper in 20 years time? In some cases you might prefer to not include a certain article in your next grant/job application.”

To me, the sounds very contradictory with the principles and aims of scientific publishing, regardless of how identification is performed. Once something is published under your name, it is part of the academic record and should not disappear, even if you don't like it anymore.

It is actually a very good thing that the integrity of the academic record, including published literature, is maintained throughout history. It is even part of scholarly publishers' duties to do so. That it is associated with your name and affiliation(s), or with a unique identifier, doesn't change naught. To given an example, if an academic were to produce a full list of publications (as part of a long CV or grant application) and willingly omit a publication from this list, I would consider it unethical (though I don't think it is something that often happens).


Writing a draft of your own recommendation letter: how to compare yourself to other students? I'm currently applying to Research Masters and PhD programs. One of my letter of recommendation writers asked me to write up the first draft of the letter, so I've been trying to do so (pretty sure the "first draft" will also be the thing he directly submits). After doing a bunch of research, most resources advised doing two things:

Use concrete anecdotes and examples to show the student's proficiency instead of just meaningless praise. I.e. Describe how he showed he was intelligent through a specific task he completed.
Directly compare the student to other students. I.e. "The student distinguished himself from his peers", "One of the brightest students I've taught", "Stood out from the rest of the research assistants etc", "Top X% in his class", etc.

The first is fairly easy to do since I obviously have a ton of anecdotes about myself. However, I'm not really sure how to do the second. I obviously don't know how my LOR writer sees me relative to my peers, and it seems extremely presumptuous to hand him a draft saying that I was one of the best students he's had. How am I supposed to compare myself to his other students for him?

Does anyone have any advice on this? Unfortunately, I can't get another LOR writer, this specific writer is extremely important to my application. It also seems extremely important to do the comparison, almost every resource and example I found repeatedly stressed the importance of doing this...

Write the letter the way you want it written.  Send it to your recommender along with a note that says something like

  I've been offered advice to the effect that the best letters offer a
  direct comparison to a peer group.  Toward this end, I've provided
  some recommended language comparing me to the group I feel is most
  relevant for this letter in paragraph X.  Obviously, I'm not perfectly
  comfortable doing this, and I suggest that you read that paragraph
  carefully and adjust it for accuracy.


Mentoring students - Computer Science I am interested in mentoring students (undergrad / MSc) in areas of Artificial Intelligence and Software Engineering.

Unfortunately, the university I graduated from/ currently work at do not offer such mentoring programs; however, this is a valuable experience that I wish to gain.

I appreciate any suggestions.

To answer with something fully external to your university:

Google Summer of Code

Google Summer of Code is a program that is about getting university students (undergrad or postgrad) contributing to open source.

Some open source project can be very technical/scientific.
I've mentored this year and last for JuliaLang/NumFocus.
Since Julia is a language primarily aimed at researchers, many of our projects are very technical.
The project I co-mentored last year was literally to implement and improve an algorithm from a paper.*

JuliaLang runs a bunch of AI projects each year.
I am sure the R and Python communities do too.

*Lagaris, Isaac E., Aristidis Likas, and Dimitrios I. Fotiadis. "Artificial neural networks for solving ordinary and partial differential equations." IEEE Transactions on Neural Networks 9, no. 5 (1998): 987-1000.


Are academics allowed to own/be part of/found a private company (UK)? I have seen some professors being members or even founders of one or more private companies. Many times in a similar topic as the one they teach/research.

What is the legal status behind this in the UK? Is it universal (controlled by state laws and rules) or contract/university specific (to be negotiated with the employer)?

I believe that this is university based. To make a long story short, the university usually owns some form of copyright on your intellectual work and passes it to you when you publish. If any of said copyright is used for commercial purposes then you need to make a deal with them on a case by case basis, though there are standardised contracts. University will have a office devoted to this. If the company is unrelated to your field/work than there's no need for such arrangements, but you still might want to double check with them.

This is my understanding having seen a colleague going through some of this (and eventually get told there was no need to make arrangements, essentially if is not something you devised or developed while working its ok)


Studying for an exam with an unprepared student I am a student and another student asked me to study together for an exam and I agreed. But when we started studying he didn't know much about the subject, and I had to explain to him how to solve the problems and waste a lot of time in doing so.

Should I keep studying with him?

Ask yourself what you are getting out of it. If nothing, then give it up and just advise the student to study harder.

But it is just possible that you are benefitting from the experience. Having to explain things to others firms up your own understanding in many fields. Many professors have had the experience that teaching a relatively low level course for the first time gave them a deeper understanding. Even something like, say, calculus.

One of the most important aspects to learning is reinforcement and feedback. Depending on the other student's questions and issues, you may be getting both from the interaction.

Think about it and also think about your best use of the time. Active learning (as in such a scenario) may be more effective than passive (reading notes, say).


Where to publish supplementary math intensive material for magazine article I received a review report on my magazine article (Impact Factor 7.6). Based on magazine restriction we can not use more than 3 mathematical equations. But the idea I presented in article require some mathematical evaluation as well. The reviewer suggested that we should publish relevant result and cite them in magazine article. They didn't mention whether the results should be peer reviewed or not. My question is for such a high impact factor (in my research area the magazine is listed as 99 percentile in JCR) magazine article is it acceptable to refer something which is not peer reviewed?If its ok then what is best way to do so? I don't have personal website and my school don't have publicly accessible repository and arxiv accept only the full articles not just some kind of mathematical evaluation.
 Is it fine to use researchgate to publish mathematical results?

If the main idea of the mathematical evaluation can be explained in words, then the details may not be necessary to make public, as the motivated reader can certainly rederive them.

If on the other hand the math is non-trivial, then it should be explained in a high level way, with appropriate references to the more advanced techniques used.

If the math is highly non-trivial, then that would be sufficient material for a publication in mathematics, and the full paper on the math may be posted on the arxiv.

And no, personally I wouldn't use researchgate. Researchgate is not a journal, and submissions there do not count as publications. The same applies to arxiv too, and if you have a paper-worthy mathematical result, it ought to be eventually submitted for publication.


I find a work title similar to mine without any published paper, what I have to do? I am doing my PhD study. I have already finished my objectives. Before 4 months, I have done one of my objectives.  Today, I found a title similar to mine in some way,  in one of the conference workshops. The work was presented at 04 to 07 of Jul 2018. I read the abstract which does not give any further information about the work. I search for the work via Google Scholar and the library of my university, however, I found nothing.

All what I understand from the abstract is that they used the same name as the model that I have used, which was not investigated when I finished my objective.

I am really confused now. I do not know what I have to do. There is no peer review paper about the work.

Any advice, please?

There are at least three options. One is to contact the original authors for more information, perhaps including a copy of the paper. If the work is too similar you may have to change direction. But perhaps the change in direction is to extend that work.

The second option is just to carry on and hope for the best while continuing to check to see if more information becomes available. This is the risky option, of course, as you will be spending time now on work that may need to be modified or abandoned later.

The third, maybe best option, is to have your advisor or another faculty member request the earlier work and make a judgement on your behalf. One option of the advisor is to analyze the work in light of your own and give you advice. This has the additional benefit that you don't see the work and so can't be influenced by it unless that is necessary for ethical reasons. While this doesn't preserve the claim of "parallel work" it helps protect you from any charge of improperly benefitting from the work of others. Of course it also depends on the solid reputation of your advisor.


Does writing a book improve your chance for getting scholarship for applying PhD abroad? As you know there are many candidates competing for winning the scholarship for their PhD program, specially the ones who are applying abroad. So, having better skills likely spell to overcome the other candidates.
I have two SCI papers in my field. So I don't have a very bad research background as a graduated student of electrical Engineering for M.SC. degree. But, recently, I've started to write a book in English. The content of book is very general and simple but still can be fitted in my field. The book title is going to be 'Technical use of English language in electrical engineering'. This book is one of the courses of Electrical Engineering for undergraduate program in our countries.

So, since the books are not usually peer-reviewed, I was wonder to ask:

How much does writing  a general and simple book in your field help
you to get a good scholarship for PhD program?
Is the effect of writing a book more than a namely SCI research paper?
Is the affects of having a book variy in different countries? If
yes, please tell me about Australia, US and Canada for precise.
Is it okay if I self-publish the book or I need a good publisher?
does it compensate my bad GPA by any chance?
finally, what are the advantages of having a book as a graduated
master student?

The goal of a PhD is to teach you how to do research. Teaching is not the primary goal of the PhD. Book publishing is also considered something that can be detrimental early on in one's career, since it takes time away from the other more important goals (advising students and postdocs, peer-reviewed publications, grants, teaching, committee work, etc.).

That said, a well-written published book probably can't hurt your chances. If, however, it's riddled with poor writing and technical errors, it will not help and may even do some harm.


Why isn't pre-registration required for all experiments? Why aren't all experimental results of any validity required to register the experimental plan used for the research paper in question, ahead of time, giving the understanding that the results will be made known.  Why,

because

The description of the experimental procedure should be untouchable once the experiment commences, and most importantly
it removes the option of simply failing to publish.  This option may introduce bias as there may be myriad reasons why a valid experimental result could be withheld.  Such reasons include those given by the biases of the experimenters themselves or the judged impact of an out-of-the-box result.

By all appearances, if one is to embark on an experimental program, shouldn't one be bound to disclose the results?  Registration seems to be the only way to enforce this.  It wouldn't be taxing... simply emailing a pdf to a database system of some kind would be enough.

I'm guessing many papers undergo this process on an informal level, but I doubt every research paper has some sort of registration like this.

[My background is in mathematics, not the sciences proper.]

Pre-registration is not the easy "cure" for publication bias that you seem to think it is. In short: Who is going to enforce that authors actually follow their pre-registered plan and publish their results (which takes time, effort, and money to check)? What kind of consequences can be imposed on those who don't?

There are no major incentives in place for editors, reviewers, or authors to enforce this, except for their desire to advance the field and enhance the rigor of their discipline. Clearly, this intrinsic desire is not enough to prevent authors from throwing out negative results, reviewers from recommending rejection of negative results for not being interesting, or editors from declining to publish negative results.  Pre-registration alone does not change that incentive structure; changing the incentive structure is not easy to do.

In medicine, pre-registration of clinical trials has been required by many major journals as a prerequisite for consideration for publication since around 2004-2005. However, there is no clear evidence that this has had an effect on publication bias in that field. Authors continue to submit papers in which the primary outcome of experimental protocol deviates from the registration, and reviewers often don't check the registration document to catch this. Non-publication is still common. And many journals are unwilling to take a hard line on pre-registration.

You said,

  The description of the experimental procedure should be untouchable once the experiment commences,

In medicine, the pre-registration did not actually achieve this. See e.g.  Mathieu, S., Boutron, I., Moher, D., Altman, D.G., & Ravaud, P. (2009). Comparison of Registered and Published Primary Outcomes in Randomized Controlled Trials JAMA, 302 (9):

  Of the 323 included trials, 147 (45.5%) were adequately registered (ie,
  registered before the end of the trial, with the primary outcome clearly specified). Trial registration was lacking for 89 published reports (27.6%), 45 trials (13.9%) were registered after the completion of the study, 39 (12%) were registered with no or an unclear description of the primary outcome, and 3 (0.9%) were registered after the completion of the study and had an unclear description of the primary outcome. Among articles with trials adequately registered, 31% (46 of 147) showed some evidence of discrepancies between the outcomes registered and the outcomes published. The influence of these discrepancies could be assessed in only
  half of them and in these statistically significant results were favored in 82.6% (19 of 23).

You also said,

  it removes the option of simply failing to publish

Pre-registration does not, as you seem to believe, compel the experimenter to publish the results.  How could it? Who would enforce this?

Pre-registration can potentially make it much easier for the results to be published than they otherwise would have been; some journals offer peer-review and conditionally accept the article based on the pre-registration, before the experiment has actually been conducted. (Negative results can be quite difficult to publish otherwise.)

But non-publication remains common in medicine, even among registered clinical trials. From Ross, J. S., Mulvey, G. K., Hines, E. M., Nissen, S. E., & Krumholz, H. M. (2009). Trial publication after registration in ClinicalTrials. Gov: a cross-sectional analysis. PLoS Med, 6(9), e1000144:

  We examined reporting of registration information among a cross-section of trials that had been registered at ClinicalTrials.gov after December 31, 1999 and updated as having been completed by June 8, 2007, excluding phase I trials. We then determined publication status among a random 10% subsample by searching MEDLINE using a systematic protocol, after excluding trials completed after December 31, 2005 to allow at least 2 y for publication following completion. Among the full sample of completed trials (n = 7,515), nearly 100% reported all data elements mandated by ClinicalTrials.gov, such as intervention and sponsorship. Optional data element reporting varied, with 53% reporting trial end date, 66% reporting primary outcome, and 87% reporting trial start date. Among the 10% subsample, less than half (311 of 677, 46%) of trials were published, among which 96 (31%) provided a citation within ClinicalTrials.gov of a publication describing trial results. Trials primarily sponsored by industry (40%, 144 of 357) were less likely to be published when compared with nonindustry/nongovernment sponsored trials (56%, 110 of 198; p<0.001), but there was no significant difference when compared with government sponsored trials (47%, 57 of 122; p = 0.22). Among trials that reported an end date, 75 of 123 (61%) completed prior to 2004, 50 of 96 (52%) completed during 2004, and 62 of 149 (42%) completed during 2005 were published (p = 0.006).

And authors have many reasons for not publishing, reasons that don't necessarily go away with pre-registration. From Song, F., Loke, Y., & Hooper, L. (2014). Why are medical and health-related studies not being published? A systematic review of reasons given by investigators. PloS one, 9(10), e110418:

  We included 54 survey reports. Data from 38 included reports were available to estimate proportions of at least one reason given for not publishing studies. The proportion of non-submission among unpublished studies ranged from 55% to 100%, with a median of 85%. The reasons given by investigators for not publishing their studies included: lack of time or low priority (median 33%), studies being incomplete (median 15%), study not for publication (median 14%), manuscript in preparation or under review (median 12%), unimportant or negative result (median 12%), poor study quality or design (median 11%), fear of rejection (median 12%), rejection by journals (median 6%), author or co-author problems (median 10%), and sponsor or funder problems (median 9%). In general, the frequency of reasons given for non-publication was not associated with the source of unpublished studies, study design, or time when a survey was conducted.

Actually verifying that the details of a manuscript match the pre-registration document involves some overhead for reviewers and editors. See e.g. Mathieu, S., Chan, A. W., & Ravaud, P. (2013). Use of trial register information during the peer review process. PLoS One, 8(4), e59910, which found:

  1,136 authors (n = 713) and reviewers (n = 423) responded (37.5%); 676 (59.5%) had reviewed an article reporting a clinical trial in the past 2 years. Among these, 232 (34.3%) examined information registered on a trial registry. If one or more items (primary outcome, eligibility criteria, etc.) differed between the registry record and the manuscript, 206 (88.8%) mentioned the discrepancy in their review comments, 46 (19.8%) advised editors not to accept the manuscript, and 8 did nothing. The reviewers' reasons for not using the trial registry information included a lack of registration number in the manuscript (n = 132; 34.2%), lack of time (n = 128; 33.2%), lack of usefulness of registered information for peer review (n = 100; 25.9%), lack of awareness about registries (n = 54; 14%), and excessive complexity of the process (n = 39; 10.1%).

Finally, publishers and editors may be reluctant to require pre-registration because they fear that authors will simply go elsewhere. From Wager, E., & Williams, P. (2013). “Hardly worth the effort”? Medical journals’ policies and their editors’ and publishers’ views on trial registration and publication bias: quantitative and qualitative study:

  Only 55/200 journals (28%) required trial registration according to their instructions and a further three (2%) encouraged it. The editors and publishers interviewed explained their journals’ reluctance to require registration in terms of not wanting to lose out to rival journals, not wanting to reject otherwise sound articles or submissions from developing countries, and perceptions that such policies were not relevant to all journals. Some interviewees considered that registration was unnecessary for small or exploratory studies.


How to include showcased work at a conference in a resume? I am working on adding to my fledgling academic resume and I'm not sure about how to cite one of the work.

My team designed an educational game that was showcased at a conference. There was no presentation per se. People could come take a look and try it but that is all. Is this even worth including in an academic resume? If so, how would I go about including this in APA? I don't want to make it look like I did a presentation when I did not.

I assume that your showcased work was not published in the conference proceedings either online or offline.

If you did not receive any written acknowledgement about this showcased work in the form of a certificate, then it is not wise to write this in CV. There are many activities we do while studying, but not all go to CV.

If you have any proof for the same (in the form of a certificate), you could add the following information into your CV:

(Author, Year, Title, Conf, Venue) e.g.

Lastname1, Firstname1, Lastname2, Firstname2, (2018) "A demonstration on the XYZ Game," in International Conference on Funny Games (ICFG), January 22-23, University of ABCD, Country. [Showcased work, unpublished]


Elsevier open-access fee waived for subscribers? I have recently been comparing publishers regarding their policies on double dipping (charging an open-access fee for publishing in a hybrid journal and then charging again a subscription fee). Many publishers (Springer, Wiley, Taylor and Francis) state they lower the subscription fees based on the amount of open-access articles to not charge their authors / readers / customers twice for the same article.

Elsevier has a different approach. They state:

  Elsevier's policy is not to charge subscribers for open access articles and when calculating subscription prices only to take into account subscription articles – we do not double dip.
  [source]

But how is this implemented? The Elsevier support team was of no help when I asked there. I only got links to the help pages, which I have read forwards and backwards three times already. I even created an account and started a test submission to two of their hybrid journals but there wasn’t even a box to tick for selecting Open Access.

Has anyone made use of this policy and asked for a waiver based on a journal subscription?

@Stephan Kolassa has given the technically correct answer.  I will add that all of this is irrelevant to the vast majority of universities, since they don't pay individual journal prices.  They pay for an Elsevier bundle, and Elsevier forces them to keep the amount paid secret.  It seems clear that bundle prices are determined based on what Elsevier believes a university can afford (i.e., will submit to) and are not based on any formula involving numbers of articles.  Thus Elsevier is double-dipping.  The only way they could prove otherwise would be to have a transparent pricing scheme and to allow universities to make public the actual prices paid.

Note that Elsevier has gone far beyond this and even charged for access to articles whose authors paid an OA fee in some cases.


How beneficial is speaking at non-academic conferences to future computer science career? How beneficial is speaking (or holding a workshop) at non-academic software development conferences (like PyCon, Strange Loop or LambdaConf) to future computer science career (applying to PhD and further)?

That really depends what you mean with "beneficial". One of my junior PhD students recently went (partially self-funded) to a relevant developer conference, and he felt he benefited greatly (probably much more than from an average scientific conference).

He was able to establish great contacts to industry. This included potential partners for studies and interviews (lately a big part of our research), as well as potential internship opportunities. (as a sidenote, this mainly happened because this specific student is an excellent networker - you can't just go to a developer conference and hope that useful contacts will spring up automagically)
He got a lot of perspective on how industry sees the current challenges of our field (as opposed to other researchers). This gave him interesting ideas for his PhD, and also tremendously boosted his motivation, as he saw that many of the things we are working on are actually quite interesting to big industrial players (such as, in our case, Facebook).
He was able to give a presentation about our ideas, and they were perceived really well (much better than he expected, truth be told). This gave him presentation practice, forced him to collect and structure our early ideas, and further strengthened his commitment to the topic.

Now, since you specifically ask whether attending such a conference will be valuable for:

  (applying to PhD and further)

I think you can safely ignore this aspect. In pretty much any career phase, nobody is going to read your CV and think "that guy attended this conference, he must be great". I don't even list attended conferences (of any type) on my CV anymore, simply because it seems so irrelevant to a recruiter.

Edit:

@ff524 correctly notes that you were specifically asking about speaking at an industry conference, not just attending. I am not entirely sure about this, but I would assume that this may be a small positive factor for applications on a junior level (say master of PhD student), depending on the conference:

Nowaydays, many of the industry conferences in my field are organized like un-conferences. That is, everybody can speak if they want to (maybe pending some light review for on-topicness et cetera). In that case, you are back to square one - speaking at a conference where everybody is allowed to speak does not count for much. It maybe speaks to your motivation, but really that seems like a very small and insignificant factor.
If the conference is more like a traditional conference, where speakers are typically either invited or you need to apply in some way for the honour of speaking, presenting may be perceived as a sign towards your esteem, but this really requires that the reviewing professors know this specific industry conference, think highly of it, and know that speakers are competitively selected. I would not count on this to happen, but it surely won't hurt.

For any application after graduate student level, your research credentials are so much more important than any talks at industry conferences that you can safely ignore them for future applications.


What should I do if I have just observed minor mathematical typos in my accepted paper? My paper was accepted at a good conference after 3 reviewers cleared it. After proof reading for the publishing, I sent it to the editor with approval.
However, now I have realised that there are 2 mistakes in the paper: 1. One of the equations dependent on time is using t instead of t+1 2. One of the equations is using best instead of best_i.

The editor has told me that the paper has been sent already for printing, and nothing can be done anymore. Can someone suggest what might be the best course of action now?

As you wrote yourself:

  The editor has told me that the paper has been sent already for printing, and nothing can be done anymore.

Given that the editor decides how a publication runs, there is nothing you can do. "Normal" journals usually publish errata but conference papers often do not have that possibility.

Don't worry about it too much: everybody makes mistakes/typos and it is not a big problem. The intelligent reader will spot the mistakes and not mind too much because he gets the point anyway, the other readers will not spot the mistake so they won't care either.

Just make sure you learn from this: next time double check everything and ask a meticulous, friendly colleague to do the same.


I think my professor misunderstood something I said and may have taken offense; what should I do? I am following a graduate mathematics course. While in class, I noticed that my classmates notes almost sliding off her inclined desk, and I whispered to her that gravity was a bitch. I think I saw the lecturer, a woman, react to this but I am not sure. I am now worried that our lecturer thinks I called her a bitch. I have the utmost respect for her and I'd hate for her to think otherwise. How can this be fixed?

I think the best course of action is to explain what happened and apologize to the instructor. After that it is up to her if she is willing to accept your explanation and apology. Natural you should avoid repeating this attempt at joking in a classroom setting and save it for more informal environments.


Job adverts with "proven track record" In some job adverts I found something on the lines of (emphasis mine):

  Requirements:

  Graduate degree in X or PhD in Y with a proven track record in X, ideally with experience in Z. We are looking for a highly motivated scientist to join an interactive, multi-national team at the cutting edge of...

(I know I should ask the OP as they are the only ones to know what do they want to say... but,). What does this "proven track record" mean ?

Does that it mean I should have publications?
Could it be other published work like blogs, programs, discussions, answers in SE traceable back to me if they are related to X?

For an industry position this typically means you have worked on and completed a project that involved X. Ideally you should also have some way of presenting verification of this if challenged, but generally confidentiality agreements may prevent specific details. In the academic sense, this effectively means the same thing, but you should have some sort of publication to verify your involvement in X.


What post PhD path alternatives are there? Progression in academia, in general, seems and feels extremely linear, i.e. you do your undergrad, then you do graduate studies, then you do a post-doc (or two, or three ... ) and eventually if you are good/persistent/well-connected/... enough you might get funded to start your own group and live the rest of your professional life in chasing grants, fighting with faculty and editors etc [yes, I am exaggerating], which I don't find particularly appealing.

Alternative to this scenario is to quit academia and go to the industry, often labeled as "selling out" by senior scientists I have personally met and discussed this subject with.

But life in general never gives a clear bisections, like you do either A or B, but there are typically a number of options to choose from. Thus I figure there should be some shades of gray in between the white and black. As a resource to other doctoral students I figured we could perhaps accumulate the possible career paths for people that have finished their PhDs, besides trying to climb up the ladder of academic ascension.

The ones I can think of are:

specialized (lab) technician: working for instance with complex instruments. I have noticed in our lab that having an experienced technician operating and maintaining the heavy instruments is invaluable for the group. Not only for the sake of projects going as smooth as possible, but also for teaching grad students how to properly use the instruments.
popular science author/editor: I have read quite a few popular science books by people with PhDs on fields that I know little about (here's a good example). Similarly, magazines such as Illustrated Science typically need a middle layer between cutting-edge science and interested (but not adequately educated) readers.
research position at industry: I am really going on a limb here, as I don't personally know anyone who is actively doing just that, but companies in several different fields actually do research; either in collaboration with universities, or in-house. I am inclined to think that such a position would include less grant-seeking, and publishing headaches (perhaps replaced with other types of headaches).
production position at industry: from what I understand this is the more typical scenario where people that go to industry after doing a PhD end up in. Based on my discussions with people (in academia) these positions typically include little to none intellectual development or acquisition of new skills. Thus not-so-desired or looked-down-upon by academics.

My question(s):

what other career paths are there, that I might have missed?
am I correct in my understand of the above 4 paths? are there any insights that you would like to add?

Selling out?  Hardly!

I am a researcher in industry, and I love it. I get to work on important problems and my work is expected to translate into real products in roughly 5-10 years.

While working on my PhD, I felt that the academic mindset was overwhelming. I have never had any intention of doing anything but research in industry, but I was certainly in the minority.

Some of my reasons for choosing my career path were/are:

Many people in academia seem to be overly focused on publishing, even before they can make reasonable and meaningful conclusions (which can contribute to a mass of conflicting literature). To me, conferences are for discussing interesting work, but publishing is for disseminating conclusions (& supporting data) that can have a meaningful impact on a field of knowledge. In industry, I have to write up reports all the time, but only the important stuff gets published.
I am a scientist, which is just the modern term for a "natural philosopher." I take my role as a philosopher very seriously, but as much as I love knowledge, I believe it is irresponsible to use other people's money to pursue research that is unlikely to benefit those people in a timely manner. Pure research is a hobby; Applied research is a job. In industry, I am free to pursue pure research when I have spare time, but I get paid to work on real problems.
In an academic setting, it is far too easy to pursue research in a very narrow field in which everybody knows everyone else. No thanks! I love that my job forces me to work outside my comfort zone, with a wide variety of people that I would never interact with in an academic setting. I have grown personally and professionally from these interactions.
Working for a company, I am usually guaranteed funding for something... but not necessarily things I think are important or interesting. As with any funding agency, I have to propose research projects that the company is willing to pay for. I have some early-stage projects that require minimal funding, but also others that require huge investments and therefore must offer much in return. However, I can also apply for funding through both private and government agencies. We often do this when we want to pursue a new area of research and/or collaborate with other organizations.  (Note that we also fund grants for others too, so some of my work involves reviewing those proposals.)

Granted, very few people can actually get a job doing research in industry. It is highly competitive, and you often need far more than just a PhD. I worked in industry for 2 years before starting my PhD, but internships can also be great experience.  (Unfortunately, most PhD programs frown on internships or other outside jobs... which is very disappointing!)  Of course, networking also helps.  I have found that most research jobs are not advertised, so you have to actually talk to people.  In my case, I asked the VP of research for some career advice and ended up with a job offer.

I hope this helps.  Doing research in industry is very different in some ways, but similar in others.


Why is demographic information asked during college applications? I remember that at some point there was a quota system that colleges used to get the minimum number of certain demographics into their school. I remember that this was stopped.

Why is demographic information asked during college applications?

Are they using it solely for statistics, or does the choice have an impact on the chances of getting into the school for the student that is applying?

In the United States, colleges are required to (try to) collect demographic information about their applicants and attendees, as a condition for various types of federal funding and aid.  The government uses this information to track the success of various underrepresented groups in higher education.  For the government, it is the aggregated information that is primarily important; individual students are not tracked.

However, in many cases, the schools themselves make use of the information for operating their own affirmative action programs as well.  Information about the racial and ethnic background of applicants may be used to target certain individuals, to try to draw a diverse student population to campus.  Moreover, when the new students arrive, the information can be used to connect the students to appropriate campus resources (minority student organizations, etc.).


Is it unusual for a prospective university to offer a bonus to your stipend after visiting? I am a prospective PhD math student. This year's application season has brought me down to two schools to choose from:

Medium-sized department, ranked <80 on US News (whatever that means), very welcoming people, potential advisor is very young but seemed like we would "click", surrounding area and city is beautiful, program looks awesome.
Larger department, top 20 program, potential advisor is famous in his field, current advisor says I would work well with him/he's a cool guy, don't know much else since I've not visited.

I am waitlisted at university 2. University 1's initial offer to me included the standard stipend along with a decent fellowship. I made a visit to university 1 and talked with many professors and my potential advisor. After this visit, they offered me a ~17% increase in my stipend due to some professors advocating for me who were apparently impressed (whom I do not know other than my visit). I feel that this is a good sign, but I am ultimately pursuing a career in academia. So I know prestige plays a big roll in future jobs. Assuming I have an offer from university 2 as well:

Questions:

Is this late stipend increase offer typical?
Based on your experience and insight in the job market for academics, which university is the better option?

Thanks for your time to read.

It's not too unusual. Lower-ranked schools know they need to work a little harder to attract top talent. For example, I did an REU at a lower-ranked school, and they admitted that the only reason they bothered offering an REU program was hoping that some of us would become grad students -- they normally couldn't attract grad students of our caliber. Offering a 15% stipend increase to particularly promising students seems altogether appropriate.
University 2. I might seriously consider university 1 if you didn't like university 2 for some reason -- what you do is far more important than where you go, and getting into a top school does not guarantee you an academic future (not even close!!). But in your case, both seem like good options, so if you get into university 2, I would go there.


Should I provide experimental results for a paper presenting an algorithm? In a paper I proposed an algorithm for something (extracting data from a webpage), I described the steps and the result of the algorithm using a sample webpage. Do I need provide experimental results on various websites?

Here I think my purpose is not to compare something with another thing, the precision of the algorithm depends on its input provided by the user, I just want to say the application based on this algorithm is easier to use by providing how the application works, and extendable to similar websites by justification its approach.

I am confused!, if I always for any algorithm I should provide experimental results, then please let me know by Yes always, if there are exception then please let me know what are those?

If your intention is to publish a paper in good journals and conferences then you have to show that your algorithm works in more than one case, just one page is not enough, except if that is the specific intention, lets say, collect data from Google Finance pages about each company.

First prove correctness, which could be done formally, running a good number of different cases or just obtaining results that are similar to other established algorithm.

Also you have to prove the value of the algorithm, which could be done demonstrating his complexity using the big O notation; or benchmarking against other algorithms that solve the same problem. Eventually you will discover that the algorithm is better in some metrics (false positives/negatives, response time, memory usage, power, network traffic, ...) and not so good in others.

I suggest that you verify how other algorithms are presented in the same area, specially in the journals or conferences that are good fit for it, and try to use the same methods and data sets. That will make easier for readers to evaluate how good is the algorithm when compared with others that solve the same problem.


Is the following publishing strategy convenient? I work in the field of CS, and recently published one of my works (Algorithm A) in arXiv (not peer-reviewed), as a short technical report which introduces a new method along with relevant mathematical analysis/proofs/etc.

I want to submit a paper-X to a conference by using that method in some practical applications and in combination with other methods. I decided to not introduce Algorithm A in that work due to space limits and enough contributions that paper-X has by itself.

But i want to also submit an extended version of paper-X to a journal along with introducing Algorithm A with proper further analysis/proofs.

So:

1- Is this allowed?

2- Is it convenient / advised?

As you describe it, it seems like standard practice (more or less). Conferences prefer somewhat shorter works than journals due to time (reviewing) and space (proceedings) considerations. Journals don't have that limitation, though some won't publish long works.

You will need to be careful about citations of your own work, of course and you may have issues with the possibility of double-blind review in some situations.

However, if you publish the journal article first, there would probably be a presumption by the conference committee that it is "old work" and not suitable. But, in general, extending an older work is acceptable - even praiseworthy.

But, to satisfy journal reviewers, the "extended" work should be more than a restating of the earlier work. A summary of older work might not be enough, even if it brings together the, already published, algorithm, and the, already published, use. Reviewers may be looking for what is new.


What do you think about a part time PhD vs full time PhD, when the part time PhD involves working on my master's thesis research full time? I am working on my masters thesis. If my full time job involves working on the same research project, will it be worthwhile to do a part time PhD?

Are there any things I am going to lose on? Is there any way i can make up for that? If I want to have a career in academia 3-4 years down the line, will it hurt me?

I can relate to your situation somewhat. I have been full time while studying my Masters and now my PhD, but in my case, there were no direct links (the job pays the bills).  The final academic transcript says the degree, not whether you did it part or full time.

While working full time, I finished my part time Masters (physics) in 3 years and are on track to do the same with my PhD.

It really depends on how much time you can realistically spend on your research so that it does not impact on your paid job, your lifestyle, family and friends and such.  Whether it is worthwhile really depends on you and what you are aiming for - it sounds like it may well be worthwhile for you, given your job is in the same field and that you are aspiring to have a career in Academia.

Hope this helps.


Is it possible for someone with a BA in mathematics who is not currently a student to get an applied research job? My graduate school applications fell through and I was wondering if there was a job I could do that would keep me improving as a mathematician, or if the best I could hope for is the least invasive mode of sustaining myself while I study/prove in my own time. I don't need much money to live off of, but I do need to support myself. Is it possible to get applied research jobs with a BA? I know there are research opportunities for graduate students and undergraduates. Do these apply to "unattached" peoples? What about part-time or consulting work?

I'll explain my situation. Due to circumstances outside my control I was unable to apply for graduate school.

In the mean time, I am staying busy until I can apply this fall. Currently:

I am taking programming/CS at my community college.
I have been studying math, physics, and computer science on my own. I've been on here a decent amount, I do project euler, I have books, there's Coursera/MITOCW.
I live somewhat close to a very good university (UC Berkeley to be exact). I looked up the professors for ones that are doing research in fields I am interested in, and emailed them. I am current doing some reading with one of them which will probably turn into some research/writing a paper.
I looked at the classes I was interested in at the university. I emailed the professors asking if I could audit them. They all unequivocally said "yes", some even offered to grade my tests or said that homework was peer graded.
I have been tutoring a lot to make money (with a BA you could easily charge $30-40 an hour). If you really want to, you can get enough students to live very modestly while still pursuing your interests.
I know a friend who works doing data science. He might be able to get me an internship at his work.
The same friend might want to design some programs together.
Once I get a little better at programming, I was thinking about doing some freelance software/website/etc. development. I'm sure I could do projects here and there.

So do NOT feel hopeless. Honestly I feel like my passion for math and science has never been higher, and I feel very positive. There are TONS of things you can do. Please ask me if you want to talk more. :)


How much novelty should I add to my previous paper to get it published in New journal? I published an article in a journal, then I realized that I Can add two other ideas to it and then get it published in more sophisticated journal than previous one.
The question is : Can I publish my same previous article (same title, same sections, etc) the only diffrence would be : two added sections that represent about 30% of the article ?

This seems unlikely. I doubt that an editor of a reputable journal would accept it, knowing the details. And it would be an ethical lapse to obscure the details, of course.
You can, however, write an extension of the old work, citing it as usual. But the new results would have to stand on their own to pass review. If they don't, then an option is to continue work until you have something that editors and reviewers (not readers here) find sufficiently "interesting" and novel.


How does the experience of working at a "top" university differ from working at an average one? Being a professor at the top university in your field must be a very different experience from being a professor at a top 20 university, which must be a very different experience from working at a top 100, 500, etc. university.

But how do these jobs differ? What are the qualitative differences between working at universities in different tiers? I'm less interested in pay and benefits -- more interested in the day to day experience.

(Since I've only been faculty in one department, my answer involves a bit of extrapolation...)

Quality of students — It is much easier for top departments to attract the strongest students to their PhD programs, so the average quality of students tends to be higher.  Faculty at top schools can spend less time bringing their PhD students up to speed and more time interacting with them as mature colleagues.  This has a big impact on the productivity, research quality, and enjoyment of the faculty.  (Of course, the strongest students are not all concentrated in the top few departments.)
Quality of faculty — Similarly, it is much easier for top departments to attract the top faculty in their respective subfields, so the average quality of faculty tends to be higher.  Again, this has a big impact on productivity, research quality, and quality of life.  (Again, the strongest researchers are not all concentrated in the top few departments.)
Rock star culture — See my previous answer about the benefits of being a PhD student in a top department.  The same comments apply to faculty in top departments. Of course everyone publishes in the top conferences and journals.  Of course every assistant professor gets a CAREER award.  Of course everyone has a few best paper awards.  Of course everyone sends their PhD students to academic positions in top departments.  Of course the faculty got another umpty-dozen-million dollars in grant money this year.  That's not exceptional at top places; that's just normal business.  That assumption of excellence is both incredibly powerful and incredibly stressful, just as it is for students.  Impostor Syndrome is rampant.
Center of the world — Top departments are more likely to attract the best researchers to visit, either as informal collaborators or as formally invited speakers.  This opens up many more avenues for collaboration.
Administrative support — Because top departments are well-funded, they tend to have more administrative resources.  For example, my business office (paid entirely by "indirect costs" from grants) takes care of all the financial and administrative details in my grant proposals, letting me concentrate entirely on the 15-page narrative.


Why do universities tolerate uploading papers on their websites? Lots of professors provide their full papers published by scholarly journals on their personal website (in the university official domain). PDF files of their final papers published by different publishers are available online. However, this is against the copyright transfer agreement, and the authors have no right to distribute their papers publicly. In other words, the authors have the same right as well as others to distribute their own papers publicly, as this is the marketing right of the publisher.

This is clear violation of the US copyright law, like distributing cracked software programs or movies without copyright. Why the university officials do not take action over this copyright violation?

One may say that this is their personal website and they are legally responsible, but if someone distribute an illegal item on his/her personal website, the university will not allow this because it is part of the university domain.

I think universities ignore this because it seems to be less criminal, but why? as it is still illegal. So much the worse, it is even common in top universities where considering legal issues in different aspects is quite serious.

Why the university officials do not take action over this copyright violation?

Because they can't.  There is no way to tell whether a given electronic preprint violates the publisher's copyright-transfer agreement or not.  Different publishers place different restrictions on authors' rights to redistribute their papers.  Some allow posting pre-edited versions; some allow posting the official camera-ready version; some allow neither; some only require an exclusive publication license and leave copyright in the author's hands.  These restrictions change over time, and may depend on whether the author paid an open access fee to the publisher.  The only way to determine whether an electronic (p)reprint is posted illegally is to read the actual copyright-transfer/publication contract.  But this contract is directly between the authors and the publishers; universities have no record of these agreements.

Because they don't have to.  At least within the US, university web sites generally fall under the "safe harbor" provisions of the Digital Millennium Copyright Act, which requires copyright holder to request removal of the specific items to which they claim copyright.

Because the publishers don't care.  Scary legal language notwithstanding, academic publishers in many fields have zero interest in pursuing legal action against individual researchers for posting copies of their own papers in violation of copyright transfer agreements.  (I have heard this said specifically about ACM, IEEE, SIAM, and Springer, by people with connections inside each of those organizations.)

Because it's not in their best interest.  Both universities and the public benefit materially from the public availability of research by their faculty, students, postdocs, and other researchers.  Universities have no incentive—aside from a potential legal threat that they know will never materialize—to proactively censor that research.  Many universities, and more recently many governments, have adopted open-access policies that either encourage or require their members to amend publication agreements and make their work publicly available.

Because researchers would revolt.  Even if academic publishers started sending DMCA notices to universities, and even if universities required their members to take down copies of their papers, in violation of research community expectations, the people whose research is being censored would simply take their business elsewhere.  Those publishers would receive fewer papers, and those universities would receive fewer graduate school and faculty applicants.


Recommendation letter for a short time collaboration I have started my 1 year postdoc in math three months ago, of course after 1 month the university was closed and I have to work at home, due to Corona Virus. Recently, I want to apply for another postdoc position in another country. One of the required documents is a letter of recommendation from current mentor. I do not know whether it is reasonable to ask a recommendation letter from my current mentor, because I have just worked with him for a short time. Does he give me a recommendation letter?

If your contract is only a year long, your mentor is likely expecting you to be applying for jobs very soon. I don't think they would be surprised; in fact, they should encourage you. I would not hesitate in asking for a reference.


What to mention in your introduction to your research methodology chapter My supervisor told me that I should write paragraph in which I introduce the problem that will be addressed by this chapter (research methodology).

What are some of the key aspects I should focus on? I understand that it cannot be a too detailed description, as my supervisor recommends only a single paragraph but I also do not want to write too little.

Answer this question in less than one minute, assuming that I have the basic knowledge of your area:
What is your research about?

Than add these in less than two minutes:
Why did you do your research in that specific topic? What is your innovation?

Lastly,
How did you do it?

Now, write your answers on a paper. And that would be the intro.
Edit: Commentors are right. Only the last part would be an intro for methodology.


What to do when a professor agrees to write a recommendation letter but doesn’t? I’m applying to grad school and two weeks ago I asked three people for recommendation letters, two from employers and one from the professor. There’s no specific deadline, but I’m hoping to get accepted quickly in order to be eligible to start classes in the fall. Now, my entire application is complete, except for the one recommendation from my professor. I sent a follow-up email, to which she said that she’ll complete it in the next two days, which was great. But it’s now been a week since that email, and nothing’s been submitted. I sent an email responding to that saying thank you and offering more info if necessary, and have not heard anything back. What should I do? Should I wait, email her again, or ask someone else? I have some other people I can ask, but the problem is that I have no way of accessing the link as the university sends out the link with the application. I don’t mind waiting at all, but my concern is that if the professor decided to back out of it and I have to ask someone else, I want to give the new person as much time as possible by sending them info now. Help?

Ask someone else now.  Provide a specific date, e.g. June 10, by which you need the reference and explain why.  You can almost certainly add another referee to your application.  If, for whatever reason, you cannot add another referee, cancel the one that's outstanding as soon as another professor has agreed.

If you can add a referee without canceling one, write to the professor who has already agreed and give her a deadline, also explaining why.  (NB: Professors are necessarily pretty good about meeting deadlines, and often abysmal at those things that do not have deadlines.  This from extensive research on a sample of one, namely Yours Truly.)


How hard is it for someone who already has tenure to find a tenured position elsewhere? I am in my second year as an Associate Professor (with tenure) at a top research university (listed among top 20 in US News & World Report in my field). My publication, teaching, and service records are all very good to excellent. I have also received numerous awards such as Sloan Fellowship and NSF's Career Award. In general, I am happy with my current institution, but sometime wonder if I can move to more prestigious university. There are other personal reasons as well that makes me ponder about such possibility. Would it be a good idea to apply other universities for someone at this stage of their career? How do search committees feel about hiring someone who has a tenure?

"Poaching"—"stealing" a tenured faculty away from one department to another by offering a more lucrative package—happens in academia with some frequency.

Obviously, if the position you're interested in applying for is a tenured position, then there might be a chance that the search committee will consider already-tenured candidates for the position. However, it is not a guarantee that this will be the case. (It depends a lot upon the candidate and the relative "fit." Also, a candidate who is fairly close to retirement may not be at the top of their priority list—simply because that means the search may have to be repeated in a few years anyways!)

One other thing to keep in mind—the working relationship you have with your current faculty may be significantly strained if you handle this the wrong way. You may want to see what you can find out on a confidential basis before committing to applying for positions. Once you've sent it out, it's out there—and could cause problems for you if word gets back to your present department.

You may therefore want to have a discussion with your department chair, but I would strongly recommend not using "these schools are more prestigious" as a reason for applying to them. If that's the only reason you're doing it, then you may want to reconsider, as switching schools is a time-consuming and nontrivial process.


Reusing material from thesis proposal in final thesis I'm writing my final thesis and there's a lot of material I would like to reuse from my proposal -- introductions, motivations, etc. -- and it would be nice to just copy-paste (and update a bit) entire chapters from the proposal.

But then I started to wonder what the technical status of a proposal really is. It's not archived anywhere, it's not "published" in any traditional sense. Is it a sort of first draft of the final thesis? Is it possible/legal/acceptable to reuse portions of it in the final thesis? Or is that plagiarism?

Your advisor should be able to provide you with the guidance.

In general, it is not plagiarism, and you can reuse the material. As you pointed out the proposal is not published. It is a confidential document outlining what you intended to do and is to be shared only with your committee.


When Are Fall Semester Grades Usually Issued? I am a middle manager at the US subsidiary of a large multi-national corporation, and a member of my staff has been accepted to grad school in her field of expertise. Our corporate policy is that we pay a set maximum amount of the tuition (something like $5000) per year. That reimbursement is not issued until grades have been posted, and payment applies to the year the grades are issued, rather than the year the classes took place. The payment cutoff for a calendar year is 15 December. The university in question issues grades for the fall semester well after this cutoff, and to me this raises questions about the logic behind our corporate policy.

My question is this: how realistic is it for a US-based graduate student to expect to receive their grades for the fall semester before 15 December?

Fifteen December is, indeed, a bit early. Final exams often come about then and professors have a week or so to submit grades. After that it goes pretty quickly with modern automation. But 31 December would be more realistic.

But even then, if you request grades formally, it may take a bit longer for them to be sent and received.

There are still some US schools in which the "Fall" term doesn't actually end until about mid January.


Would a question that requires an amount of text to explain be good to send? From Is it appropriate (as a PhD student) to email other researchers asking about some details in their papers?, I get that generally you will get answer if you ask question on their work. But what if your question is tangent to their work, and requires some space to elaborate?
The draft is below:

Dear Prof X
To introduce myself, my name is Y, from country Z. I have read some pages in your book about the connection between [concept A in field 1] and [concept B in field 2]. I wonder what do you think about the connection between [concept C in field 1] and [concept D in field 2]?
[16 lines and 184 words to elaborate the connection. I don't consider this as a wall of text]
I also have a blog article explaining all my observations about the connection between field 1 and field 2. It may take only 5 minutes to read.
Thank you for your reading. Hope you enjoy it.

Some notes:

I haven't read his book enough to say that I know a large portion of it (just skimming it), but I can say that I understand A, B, C, D at least in introductory level.
I don't have any institute, but I think my culture is relevant to field 1, so perhaps it can be a kind of expertise/institute?
I may apply to his school in the future

Related: How do researchers send unsolicited emails asking for feedback on their works?

As a busy person who receives these sorts of emails, my response to email tends to fall into two categories:

I can respond to this right now, and get it out of my queue.
I'm going to need to think about this some, I guess I'll put it off for later... and later turns out to be days, weeks, or months before it surfaces again, if ever.

Unfortunately, your draft email above will most definitely fall into category #2.

"What do you think about..." is an open-ended request for an essay. Is one sentence enough, or a page, or a full scientific paper?
You want the reader to digest 16 lines of technical discussion with an unclear goal of evaluation.
You also want the reader to go read your blog post, which makes me wonder if that's the real point of this.

You've thus got 3 different things you're asking of the reader, none of which actually says what you really want to get out of the interaction.

And that's the real problem: why are you writing to this person?

Do you have an answerable question they can help you with? (i.e., not "what do you think..." but "Does Concept A actually mean that Red Ones Go Faster?")
Do you want to show them your work and see if they think it makes sense?
Do you just want them to be aware that you exist?
Something else?

When you figure out what you most want, focus the email on precisely one thing that can be addressed quickly, and try to keep the whole thing to only 3-4 sentences.  If you can do that, you also will have forced yourself to be clear enough about what you want that a useful answer is much more likely.


NSF Panelist Reviewing Rubric/Criteria I will be serving in my very first NSF Panel as a panelist and reviewer. While I am excited, I am also anxious to do a good job...
Please provide any words of wisdom to be successful in this endeavor. Also please suggest if there are any Rubric that you aware with respect to
reviewing NSF proposals... If so could you share / provide pointers to it...

I don't know much about the NSF process, but can share my thoughts on the NIH process, and maybe others can comment on how this applies.  I think some of this is directly applicable.

Remember, you're reviewing grants and not papers.  You have reached the state of your career where your actions can DIRECTLY IMPACT somebody else's career, and fairly immediately.  It could conceivably even end some careers.  Do not take this responsibility lightly.

The biggest issue that I see come up is "New Reviewer Syndrome", where a reviewer feels compelled to make him or herself heard in a room full of people, even though the criticisms offered are nickel and dime stuff.  You can't offer a list of five trivial matters and then recommend a high priority score.  It doesn't work that way.  If you don't have substantive criticism, best to keep quiet.

That said, if you have substantive criticism that you believe can turn the grant from unfunded into one that's funded on the next round, SAY IT AND SAY IT LOUDLY.  Communicate it in a way that the applicant can hear it and understand it, and know that this is the issue separating him or her from a recommendation for funding.  Don't make the applicant guess about how important you consider this issue.  Failure of the applicant to understand what the study section wants will result in extra rounds, lost time, negative career impact, etc.  If the person running the section sends you some synopsis of the review, read it and make sure that it conveys the feeling in the room during discussion.  If you are asked to write such a synopsis, take that job VERY SERIOUSLY.

Another issue I have seen repeatedly is that its very tempting to score the grant that you wish the applicant wrote, and not the grant the applicant wrote.  Don't judge the grant based on how you would do that research, and remember that there's more than one way to skin a cat.

Your institute will provide you with some good guidelines, but here's a framework to start with:

What question is the applicant asking of the proposed study?
Is that question worth getting an answer to?
Will the proposed study answer that question?
Is the applicant/applicant's environment capable of successfully carrying out that research?

When you're outside of the review room, KEEP YOUR MOUTH SHUT.  Never violate the confidentiality of the process.  I've had people come up to me in conferences and start telling me about what was in my applications, even though they were not on the study section.  This put me in a situation where I had to moan to my program officer that they had a leak, and they should shut it.

Listen to your peers in the room.  Some have been doing this a lot longer than you, and some are in a better position to judge a particular application than you are.  Decide if their input sways your opinion, and act accordingly.

Don't get provincial about defending your area of research to the study section.  Your colleagues in the room will be doing enough of this. Research that is what you do isn't by definition good research, and research that is not what you do is not by definition bad research.

Lastly, whatever serves at NSF as the equivalent of an NIH review officer is there to help you.  Read and understand whatever review guidelines you are sent by the powers that be.  At NIH, many instructions go toward trying to get the study sections to use the full range of scores.  If you can do this, this makes life much easier for the review group.  If you can't, you really start getting the feeling that the pay cutoff is quite arbitrary.


Contacting a researcher for academic queries, but he/she may be a potential reviewer? So I have a paper submitted in a conference which requires double-blind review.
But while this paper is under review, I had a query in a paper I was reading of the very same field. Now, the authors could be my potential reviewers.
Is it fine for me to contact them regarding the query ?
PS: My paper is on arxiv as well.

Ignore the "complications". It is overthinking the purpose of double blind review. If you want to ask them questions about their paper it is perfectly ok to do so.
After all, anyone in your field could be your reviewer in a double blind process. You don't need to be paralyzed just because you submit a paper.
If there are any ethical issues they are on the other side in deciding how and when to respond to you.


Is it a bad idea to go from EE undergrad to CS(ML/AI) PhD? I know questions regarding whether its possible to go from EE undergrad to CS have been answered previously, so please bear with me as I have a few distinct questions. I'm a Junior at a mid-tier state school and I've taken quite a few CS courses (such as data structures, discrete math, programming methodologies and principles, and software development).

I've been doing some reading online and I've come to find that ML/AI(esp. Computer Vision) is something that really piques my interest. I am not sure that I have the proper probability and statistics skills required to pursue a CS PhD with a focus in ML/AI.
NOTE: (I do have a solid background in other math: Multi-variate Calculus, DiffEq, LinearAlg, multi-dimensional signal spaces,etc.)

Do you think that it would be feasible for me to actually gain acceptance into a PhD program with this focus without any research experience in ML/AI or even CS in general?
I have previous academic research experience(5 months) in EE(Semiconductors) as well as a high GPA(3.9+) and should have solid letters of recommendation. What kind of disadvantages could I face?
Would you recommend doing some self-studying of ML/AI in place of continuing my current research in EE? (I'd love to do research in ML/AI but my university doesn't have research opportunities in the area for undergrads).
How can I approach finding well-reputed groups/institutions in this area?

Thanks, I really appreciate any input or advice that you may have.

I think yes, it is feasible. On a purely technical side, regulations vary across countries and universities. At my university they consider eligible all applicants with previous education in "computer science and engineering". The rest undergo "additional examination", which in practice means that they check whether their actual transcripts overlap enough with our CS curriculum to be considered equivalent.
Computer science is an umbrella term, so it is a really diverse area. Even if you narrow it down to "machine learning", it still doesn't help much to identify your stronger and weaker points. There is machine learning in natural language processing, in computer vision, in human behavior analysis, etc., with different requirements.
Since you mentioned computer vision, I think your math background is really handy. What many such candidates lack is coding skills and general experience in dealing with programming environments. Sometimes we have to glue together a bunch of "experimental" (buggy and poorly documented) libraries and make them work. When something goes wrong, people get startled with cryptic printouts and endless error messages, as they don't even know where to begin to untangle this mess. At least, this is what I feel sometimes as I have to take personal care of the tech issues...

Sorry no comments on the "best groups", but personally I think you should approach the question the other way round. Go to Google scholar and search for papers with keywords of your interest. Read the ones you like, see who cites them and which papers they cite. Just follow the links in both directions, gather enough papers to understand (a) who is cited more often and (b) what kind of research you personally like -- after all, your personal interest in a particular type of project should matter most. And this is how you approach people: by showing genuine interest in their projects and knowledge of their publications.


Should I put my résumé on LinkedIn when applying for a PhD? When I apply to a university for acceptance to their PhD program, I send my résumé with the application. When I want to apply for a job outside of academia, I also send my résumé to them. In both cases they also read my résumé at the interview stage.

But I am not sure whether it is advantageous to also upload my résumé to LinkedIn. Will people visit my LinkedIn profile and read it? Is it likely to help?

I don't think it really makes any difference.

Admissions committees are not in the habit of doing social media searches for applicants.  In fact, I don't think I've ever heard an academic talk about using LinkedIn at all.  (Maybe it is more commonly used in certain fields that are more closely related to business.)  Even if they did, there's no particular reason they should come across your profile, and no particular reason why finding a resume there or not would influence anyone's decision.

The only possible benefit of posting I can imagine is that if, somehow, one of the admissions committee happened to see it and form some favorable impression of you, that might help their opinion when they read your application.  But that seems like an unlikely coincidence to hope for.

On the other hand, I can't imagine any possible way in which having your resume on LinkedIn could be a disadvantage in the application process.  So from that point of view, you probably might as well post it.

On a related note, I would not recommend trying to add LinkedIn connections to faculty members at the university where you are applying.  Since most probably don't use LinkedIn, this will just result in them getting annoying emails.  And you don't want them to read your application and think "Hey, I remember that name - this is the guy who's sending me all that LinkedIn spam.  What a jerk."


Citing contemporaneous (interlaced?) preprints In my area of research distributing preprints of results is very common. Consider the following seqence of events:

Group A finishes paper P, distributes it as a preprint and submits to a journal
Group B posts related preprint Q
Group A receives referee reports for paper P. Referee requests discussion/citation of Q.
Group A responds that Q came later and was not used in writing P, therefore no detailed discussion/citation necessary.
Referee insists on discussion of Q in paper P

Who is in the right?

Cite relevant literature
Since you have the option of adding a citation to a relevant source, you should do it. It improves the paper by making it a more useful reference, and comparing and contrasting the results might also be useful.
Priority
If relevant, use a phrase like "A very recent preprint A claims this and that.", or even, if your results are very similar and you really need to emphasize priority, "During peer review of this article a preprint A was published. The preprint...".


Postdoc speculative application I am just about to finish my PhD and a prof I know well and I were discussing future postdoc labs. They suggested I email a friend of theirs in the US. I got a very positive reply saying my research experience and interest are perfect for them and they will have funding for a postdoc. They then said to give them a few days to find out when they will have the money and if I can be flexible about when I could start. I replied yes I can be flexible. It’s been two weeks and he has not got back to me with the interview date and when they will have the money as they promised.

Should I be worried or does things like this take time? I have another interview lined up hence why I am curious as to know when I should expect to hear from them.

Should I be worried or does things like this take time?

No, it often takes much longer than two weeks to organize a postdoc job.  Remind them every three weeks, and be patient.


No interesting research topics available - should I quit and pay back my stipend? I’m currently enrolled in Mechanical Engineering MSc program in the UAE. I’m on a scholarship program as a TA/RA. I just finished my first semester through which I suffered greatly but I ended up with a GPA of 3.75.

To find a research topic, we are required to choose 3 topics off a list and then be assigned one of them. All three of my choices were given to more suitable candidates. I will have to choose another topic. The problem is all the other topics are of absolutely no interest to me.

I don’t want to waste my time for two years doing something that I hate. I would rather quit now and start looking for a job instead of wasting my time. But if I quit, I will have to pay back the fees and probably my stipend, which could add up to 35,000 USD. This amount increases with every semester I spend in grad school, so I have to decide now whether to stay or leave.

I might be able to pay the 35,000 with the help of my family. But I would like to know if quitting could affect my job prospects and opportunities. What would you do if you were in my place?

Please keep in mind that to quit I would have to pay back the semester’s fees and probably any stipend I have received during the semester which could add up to 35,000 USD...

"Probably" the stipend? The "probably" makes me nervous -- I think you should start by quantifying exactly how much you would be on the hook for. It could be more than that, or maybe you misunderstand and this would be zero.

  what would you do if you were in my place?

Impossible to answer, partially because I do not know what your "Plan B" is. You need to develop two detailed plans -- one for staying and one for leaving. Only then can you make a good decision.

I would also consider whether you have any professors you trust to discuss this with -- they may be able to help you find a third option.

  I would like to...know if quitting could possibly affect my job prospects and opportunities

Of course not having a degree is worse than having a degree. Paying 35K USD and still not having a degree seems awful. Starting something and not being successful also doesn't look great. But again, the question is: what is the alternative? If you can transfer to a better program, or get an awesome job, then perhaps it is worth it. For sure you don't want to acquire more debt and then not finish.