text:
How to put time spent self-studying on grad application in a verifiable way
Since my university doesn't have algebraic geometry courses or professors (*), I'm self studying algebraic geometry with the goal of finishing prerequisites before transferring. I've already started on commutative algebra and algebraic toplogy, next my goal is to read Royal Road to Algebraic Geometry. After that, I'll finally start Hartshorne.
How do I put my efforts on my transfer application for U.S. schools? I'll mention how I self-studied and what exactly I did in more detail on my statement of purpose, but is that enough? My primary goal in studying is to prepare, but my secondary goal is to convince universities that I'm putting in a ton of work on my own and thereby boost my application. I'm certain to succeed in my primary goal, but I'm unsure about the secondary goal since even if they do believe I studied, they have no reason to believe I carefully studied. I could type up exercise solutions, but they're not gonna spend time reading through all of them when there's so many students applying.
A similar question was already asked here but there are 2 differences: the topics are more advanced and I'm applying to transfer. The answers given there are to excel in the math subject GRE and get a professor to vouch for your knowledge through a letter of recommendation. The 1st difference makes the former answer irrelevant (besides, I already got 96%), and the 2nd difference + (*) makes the latter impossible unless I get someone from another university to vouch for me. What's the best way to do that, knowing full well that I would be approaching faculty just to get them to check my work?

What country is your desired university in? If it's the U.S., then knowledge of things such as commutative algebra and algebraic geometry (even if intending to pursue these fields) is less important than the overall sense of your mathematical promise/potential regarding both intellectual potential and academic perseverance. Maybe the answers to How does the admissions process work for Ph.D. programs in Country X? will help.

@DaveLRenfro Applying to all U.S. schools, thanks for the clarification

A professor who doesn't work in algebraic geometry can still write a letter about how you are studying it.

If this is the United States, this might merit a line in your statement of purpose, but only to state that you have been studying on your own, showing self-sufficiency, in areas that will help fulfill your future research goals and/or fill in any gaps in your undergraduate education. However, I will say that this is fairly common for incoming graduate students to study on their own; it does not need to merit more than a few words.

I might disagree with @parever about the universality of self-directed study... in people going to math grad school in the U.S.
Yes, some do... and, yes, it is highly desirable, both for the sheer information, and, for me, as a grad-admissions-committee person, to see that an applicant doesn't "just take classes", but has some self-motivated interest in the subject!!!!
Sure, it is possible to skim through things "without mastery", but, hm, given that we are finite beings, it is often optimal to skim through lots of things without mastery, rather than look at just one thing to "master" it... especially if/when that thing turns out to be just some gnarly little technical point, and of no great consequence.
Again, if anything, I'm more interested in applicants' self-motivated study rather than in their transcript. :)

Why is graduate admissions so...secretive? I have read that when it comes down to narrowing down a list, it starts to come down to minutiae. For example, one sentence in a recommendation letter might not be as strongly worded as it could have been, which leads to rejection. Or the applicant might have said something that could be interpreted in a certain way, leading to rejection. When I applied to grad school one professor told me that there are so many factors that go into hiring that it could seem random.

I do get where you're coming from, Paul. I think yours is a helpful addition, especially coming from a field more akin to the OP's. If the applicant writes in a letter that they have studied on their own, that's a sign that they're self-motivated and self-directed, which is helpful for pursuing a PhD. However, it's difficult to tell whether or not they studied well or carefully, or if they just read multiple textbooks without doing many assignments.

@cgb5436, it's not that grad admissions (or hiring) are deliberately secretive, most of the time. Rather, the difficulty in quantifying the desirable features, combined with HR's and higher-adminstration's seeming demand to do so, and different interest groups competing for the same positions... often lead to very messy causal chains. People have tried to make it all "objective" by numerical rubrics, but I have not ever seen that really work, since the numbers are either already subjective, or are precise measures of things that are not of great interest...

@paulgarrett Not relevant to your answer, but do you have advice on how I can write a paper that's good enough to be accepted in the Annals? I was attempting to understand your 1987 paper on triple product L-functions.

@cgb5436, ah, well, that paper of mine was actually a semi-random spin-off of stuff I'd been doing since 1978, that I couldn't "get published" (no internet at the time) ... :)  I really do believe that one should just follow one's own curiosity... despite the poor correlation with fundable-ness or (traditional-) publishable-ness. Otherwise, one drives oneself crazy trying to guess and comply with the hasty-random dictates of hierarchies... or trying to "join the gang" of some "programme". Just try to do what you like, and try to present it as well as possible to get paid for it. :)

Life is about day-to-day, I think... so one should arrange to more-or-less find some pleasure in each day.

@paulgarrett is that the best approach for getting a tenure-track job and winning the academic game? Academia is just one big game.


text:
My supervisor spells my name incorrectly
I've discovered that every time my supervisor has cited any of the papers or technical documents I've written she/he would:

spell my name incorrectly or forget to add my name
spell the article/technical document title incorrectly

These are citation made in articles already published (!!) or at final stage (where she/he denied to make any effort to try to correct them). Althought this means she/he also loses citations of these articles she/he is doing mistakes only on my papers/technical documents, not with others.
I am obliged to add her/him in every paper as co-author, although she/he never engages in any discussion concerning any of the papers or phd. This is not someone that has a flock of PhD and MSc students under her/his wings, the number of students are really reduced.
How should I react to this? What should I do about it?

I think the question could be simplified to "My supervisor spells my name incorrectly, how I can I fix this?"

"I am obliged to add her/him in every paper as co-author, althought she/he never engages in any discussiong concerning any of the papers or phd." Your problem is not that your advisor does not remember your name. Your problem is that you have a terrible advisor.

@xLeitix yeahh... that i know :) but i am determined to finish the phd, even if the cost was to add her/him in all my papers. now i don't know anymore what to do.

HAve you ever simply pointed it out to him and told him how you spell your name and why its spelled that way (if need be)? Lets say your name is michelle, but growing up all his friends names that sounded the same as yours were spelled michaelle. He might simply doing it out of habit and needs to be reminded.

@TheOneWhoPrograms I have done that already, besides spelling it wrong she/he also forgets to add my name.

Sounds like they are cheating you of your deserved recognition. I would take the issue seriously and confront them and state how you feel. If it continues, bring it up with someone higher up.

I'd do this: Send the corrected citation, something like: "I've noticed you spelled that wrong, so I'm sending this to you". Do that for every citation that is incorrect in separate e-mails. Next time send a new e-mail and resend all old e-mails. Next time send a new e-mail, all old emails and variations with different formats (bibtex, endnote, refworks...) each in a separate email. When (s)he gets 100+ e-mails about the same thing in the inbox, (s)he will get the message and will either fire you (just for trying to avoid his/her mistakes, in an annoying way) or learn the lesson.

I think you should start spelling his/her name also incorrectly on the articles he/she "co-authors"! That should fix it ... :)

"I am obliged to add her/him in every paper as co-author". Why? Does your supervisor claim this? Adding an author to a paper who has not made a meaningful contribution to it is against the guidelines of all scientific journals.

It would be nice to know whether you finished your PhD by now, and whether you could answer your own question now, in retrospect.

Mis-citing articles (and worse, removing authors) is one of those crimes that academics take very seriously (and no one else really understands). If you were a collaborator, then repeated behavior of this kind would get your advisor in trouble not just with you, but with editors at the journals, reviewers, and so on.
So you really should bring it up.
How do you go about doing it ? Because it's your advisor, you have to be a little more gentle: some options:

keeping it specific to each mis-cite: "I noticed you cited my work, but you omitted my name: can you please fix it". It sounds like you've been doing this already though.
the technical solution: "Here's a BibTeX file containing all my papers: you can use that for citing" - this works only if your advisor uses some kind of citation manager to cite papers.
the direct solution: "I noticed that in this, this and this paper, you omitted my name from the citation. I'd really appreciate it if you could contact the editors and submit a correction: I'd like to get credit for my work".

In other words, keep the discussion focused on outcomes and actions, rather than intent (because a) it's hard to argue intent, and b) you're in a position of weakness)

In accordance with the comments, I think you have two choices, get out or stick with it. Since you are determined to finish (no-one but you can weigh the choices) just try to do so and swallow the problems you describe. I am sure it is extremely irritating but focus on finishing and do not let your energy go to issues you cannot change. The sooner you finish the better. So, if you can, focus only on the work leading to your thesis.
That advisors put their names on papers, is a separate discussion and one which has been dealt with here on academia.sx for many cases. Search on, for example, the authorship tag combined perhaps with advisor.
In the end, you need to assess what you do and how you best should spend your time to reach your goal, the PhD. If you feel you are drawn into things that are not productive for this goal, use the goal as a reason not to involve: "I really must focus on my PhD, I fear I may not be able to finish in time otherwise". Also, it sounds as if you have numerous publications already, so try to probe what is enough, if that is not already clear. Simply try to find the path of least resistance to get to the goal.

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text:
How to cite ISO standards?
I am currently writing my PhD thesis and several times I cite various ISO standards. I am unsure what the correct way to format the bibliography entry for such documents is.
Currently I am doing something like:

ISO (1997). ISO 4287 Geometrical Product Specifications (GPS) – Surface texture: Profile
  method – Terms, definitions and surface texture parameters.

I'm using an author-year style so the entries normally look like

Author (year) Title, Journal/publisher

Is there a better way to format this?

If you are using or plan to use APA Style, you might be interested in my answer to a related question.

check out this blog entry on Citing ISO Standards or this site on Bibliographic Citation Standards and Schemes
As you can see there is no definitive answer to you question.
Maybe you ask your thesis advisor.

Please summarize the discussion here as those links may die.

Do you have an example of BibTex, where the corresponding fields are filled? ... Sry, found one: https://tex.stackexchange.com/a/278558/31964

Depending on how a standard is published, it should be cited either as an article, a book, or a technical report.

If the standard is published as a journal article or has an associated journal article, e.g., then it should be cited as journal article.  Example: the BioBricks Assembly Standard.
If the standard is published as a stand-alone book (e.g., being sold by a standards organization), then it should be cited as a book.  Example: many ANSI or ISO standards.
If the standard is published through some other archival mechanism, then it should typically be cited as a technical report.  Example: IETF standards.

How exactly you format such citations then depends on the citation style that you are being asked to use (e.g., MLA, IEEE, Harvard).

Using the C++ programming language as an example, one can find nearly every citation for the C++ standards in BibTeX format here:
http://ftp.math.utah.edu/pub/tex/bib/isostd.html
For example, here is the reference to the ISO C++98 standard:
@Book{ISO:1998:IIP,
  author =       "{ISO}",
  title =        "{ISO\slash IEC 14882:1998}: {Programming} languages
                 --- {C++}",
  publisher =    pub-ISO,
  address =      pub-ISO:adr,
  pages =        "732",
  day =          "1",
  month =        sep,
  year =         "1998",
  ISBN =         "????",
  ISBN-13 =      "????",
  LCCN =         "????",
  bibdate =      "Tue Dec 12 06:45:55 2000",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/isostd.bib;
                 http://www.math.utah.edu/pub/tex/bib/mathcw.bib",
  note =         "Available in electronic form for online purchase at
                 \path=http://webstore.ansi.org/= and
                 \path=http://www.cssinfo.com/=.",
  price =        "CHF 351, US\$18 (electronic), US\$252 (print);
                 US\$245.00",
  URL =          "http://webstore.ansi.org/ansidocstore/product.asp?sku=ISO%2FIEC+14882%2D1998;
                 http://webstore.ansi.org/ansidocstore/product.asp?sku=ISO%2FIEC+14882%3A1998;
                 http://www.iso.ch/cate/d25845.html;
                 https://webstore.ansi.org/",
  acknowledgement = ack-nhfb,
  xxISBN =       "none",
}

You can copy and paste this into your .bib file containing citations for LaTeX, which you should be using instead of Word anyway : ) You can use the natbib package to format it into whichever citation style you like.

You can cite it as follows:
Software engineering – Product quality – Part 4:
Quality in use metrics. ISO/IEC TR 9126-4:2004(E),
2004.
Website for the same is: https://www.iso.org/standard/39752.html

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text:
Academic faculty expat (Germany) experiences and new research group advice
I have been offered a W1 professorship to start a research group (CS/Engineering) at a German university and am seeking to learn from others' experiences or someone prepared to be a second-opinion / sounding board outside of the offering institution. In particular, I am interested to hear about the following;

How much leverage did you feel that you have had to negotiate on the package? Granted, that would depends on the situation / competition. In my case, I learned that there was only one other viable candidate.
What did you try / succeed in negotiating in terms of support, resources and package (with respect to relocation costs (spouse, shipping etc) and language course).
In retrospect, what did you wish you tried to negotiate?
Any advice / experience on starting a research group. What would you have done differently? How did you expend your group? which grant schemes did you target? What did you focus on in the first couple of years?
How did you approach industry to seek partnerships / grants?
In my case the professorship is endowed by a large company, what conflicts did you encounter and how were they resolved?
Which academic committees would you recommend to sit on such that one gets sufficient exposure to how the institution works whilst the administrative load is low as to not impede on time for research?
What did you do to establish a specific culture in your group? Share resources, code, libraries, social etc
When and how did you start thinking / working towards the next step (e.g. W2)?
Did you encounter an expat bias?
Any specific cultural or professional dos and do nots?

Some of these questions are not Germany specific, so any advice will be greatly appreciated.

I wanted to start an answer to some of the questions, but then realized that there are way too many quest here... I'd recommend to ask different questions separately.

I think questions 1-3 fit inside one question, 10 and 11 inside another, and all the others would work as separate questions.

Some of these questions also already have answers on this site, so perhaps check those first in order to avoid duplicates before editing the question or posting a new question.


text:
When does the "run, don't walk to the nearest exit" advice not apply to graduate students?
From reading the many, many questions here on Academia.SE, I sometimes wonder when is the "run, don't walk to the nearest exit" type of advice unreasonable and not applicable?
For instance, when I have just gotten out of a tough, intensive hours long meeting with my advisor, I often feel "abused", embarrassed, or worn out mentally; and I start to come on this site and read about other students' experiences, and the details they provide start to sound very familiar to my own experiences.
But I wonder if advisors are just pushing their graduate students to become better, and perhaps that students just don't have the right sense of what is expected of them and need to be forced to learn it properly.
What distinguishes tough, intense advising, with good intentions, from "real" abuse / malicious activity on the part of the advisor?  I find that it's sort of hard to tell who's being whiny or who's being legitimately used and abused and need to escape their situation immediately.

Strongly related (meta) question: Don't walk. Don't run either

Whether a situation is abusive or not is in no way dependent on the intentions of the advisor. Terribly abusive people think they are being "tough but fair" all the time.
Different people also have different reactions to the same situation. A situation that motivates one student to do better can be destructive to another. I would question that it's even your place to evaluate if other people are being "whiny" or not - you never have enough information to know what it's doing to them.
To evaluate your situation, ultimately what you want to know is if you are getting enough out of your situation to make it worthwhile. Long hours and feeling worn out are a function of workload, mainly. If you want to pursue an academic career, the kind of output required can probably not be achieved without a heavy workload. On the other hand, I have never come out of a meeting with my advisor embarrassed - at minimum, that might indicate that you and your supervisor's styles do not mesh. Another question is, how long do these feelings persist? The next day, do you feel like you are on a better path towards your thesis than before? Do you dread the next meeting?
A common and often extremely destructive feature of abuse is distortion of reality. You start to feel like things are normal even when they are really not. It is therefore most helpful to talk about these things to as many people not from your group as you can - make friendships with people who have different advisors! If your university offers therapy appointments, it can also be very helpful to go in a few times a year to talk these things over with a neutral party.


text:
Is there a service that can store and mail recommendation letters to schools?
I am currently applying to graduate schools, all of which request 3 letters of recommendation.
Schools currently accept letters submitted by a recommender on an online service, or sent through postal mail.
Since the recommendation letters that are submitted on my behalf are similar for each school, my recommenders have to go through a sisyphic process:

Get the email from the school
Click the link
Find the recommendation letter file
Upload the file
Submit
Rinse and repeat for each school

tl;dr
What I hope to discover is a service where my recommenders can upload their letter ONCE, and then have that service dispense the letters to all the schools, instead of having the recommenders themselves do it for each school separately.
Does such a thing exist?

When people agree to write a reference for you, they know that they're signing up for this process, so I wouldn't worry too much about trying to find an alternative.

My recommenders don't happen to be American and are not familiar with the American system.
In Europe the student is trusted to upload a scanned document themselves. If there's any doubt, the institution gets in touch with the recommender directly. There's absolutely not justification to make people who want to help an applicant do more work then they ought to. This concept needs to become more efficient and more friendly to the people who truly want to offer their support to an applicant.

@astronat Many Europeans would not expect such a process, see e.g. this answer of mine. And I'd agree to go through such a hassle (again) in exceptional cases only.

Wow, you make the process of uploading a PDF to a website sound really, really difficult. It must take literally seconds of somebody's time!

@Massimo and OP, I think it's important that we distinguish between continental Europe and the UK then, as it seems the UK system is more similar to the US in this regard. Anyhow, in this case it's probably a good idea to  explain to your referees exactly what is required: forewarned is forearmed.

@DavidRicherby: In fairness, it often is more than that.  There's often some sort of login and password process, and then some schools have a custom "questionnaire" in addition to the letter, e.g. "please rate the applicant on a scale of 1-10 in the following areas..."

@NateEldredge Good point though, of course, a central database wouldn't help with any questionnaires.

But it would since most American schools use one of the three main systems (ApplyWeb, ApplyYourself, and... that other one..). More over, such a service can mail physical copies of the letters to the schools (Like GRE, TOEFL, Transcripts, etc). This service exists for all other types of documents. It needs to exist for recommendation letters as well.

Many schools offer such a service. For example, UC Berkeley

The Letter Service will send letters to educational institutions to support your admission to graduate and professional school. We will also send letters to educational institutions for the purpose of supporting your applications for academic/educational and research employment, i.e., teaching positions.

You should check with your school/department to see what is offered.

My school doesn't have a similar service. This is something I would be very happy to pay for.

Although such a service could save lots of time for the letter writers, I assume there is no popular service of this kind for a genuine reason. There are two types of letter of recommendation.

Generic: in which the writer describes his/her own perspective about you (both personally and professionally).
Tailored: in which the writer tells the target committee how and why you fit the requirements of the position (e.g., a specific PhD program) you applied for.

The first type can be in the form of To Who It May Concern, and you can upload a copy whenever you send an application.
The reason that the writer is directly asked for the second type is that s/he should write his/her recommendation based on the request considering the position under consideration. This means s/he may recommend you for a position but not for another one. For instance, s/he may believe that you are an excellent candidate in a specific PhD program, but your skills do not fit with another one (people tend to make shifts in their academic education). A tangible case is your previous experimental/theoretical skills when applying for a program with an emphasis on theory or experiment. In this case, there is no point to store a generic letter of recommendation and send it to different committees.

A common case is that the letter is "generic but confidential": the same letter will be sent to all schools, but the applicant is not supposed to be able to read it.  This is the norm in the US.  In that case, your "generic" solution doesn't apply, because the applicant won't be given a copy.  Indeed, many schools don't accept recommendation letters through the applicant's interface.  This is the case in which the proposed service would be useful.


text:
What to write in an impressive about me section
Can you give me some suggestion on how to write an impressive about me section in my cv?
I know I'm supposed to give relevant information (I'm a scientist, by the way) which is not directly covered by my academic background and career, but basically I don't have a clue about what to include (for example, should I add the description of some traits of my personality?).
I'm particularly thinking about some sections of the second page of this one www.teemeurope.eu/documents/europeanCVformat.doc namely PERSONAL SKILLS AND COMPETENCES and OTHER SKILLS AND COMPETENCES and the linkedin profile

CV sizes vary broadly from one-page concise versions to extensive 7+ pages long web-page versions. Unless you specify the desired size (and purpose) of your CV, there is no general answer.

I have never seen an academic CV with an "about me" section. Can you point us to some examples?

I'm particularly thinking about some sections of the second page of this one http://www.teemeurope.eu/documents/europeanCVformat.doc namely PERSONAL SKILLS AND COMPETENCES and OTHER SKILLS AND COMPETENCES and the linkedin profile

relevant information...not directly covered by my academic background and career — What? An academic CV is a summary of your academic background and career; nothing more or less.  (If you're asking about a non-academic CV/resume, you're at the wrong site.)

"PERSONAL SKILLS AND COMPETENCES" I'd say something like the tools (OS, frameworks, VCS, languages like LaTeX, etc.) that you can use. I like to keep the traceability of my stated skills with my past work done. I don't have an "about me" section, and if I was checking CVs I'd completely skip that section, I'm quite skeptical about everything. My advice may be bad and biased, after all it's about marketing and you are the product, but I think I'm more of a "doer" than a talker and I'd prefer to work with doers, even if talkers seem to get better jobs and better salaries (lol skills: skype :P ).

It looks like what you are being asked for here is sort of a hybrid between an academic and conventional CV. I dislike this sort of form filling CV but if its what you've got to do...
Personal skills and similar sections generally are looking for your soft/transferable skills. Good communications, team-working etc. Try and not just state these but add some qualification e.g I'm good team working which I have developed/demonstrated during whatever project or competition or something. It's very easy to say you have some skill but far more convincing if you can demonstrate it. Similarly be prepared to defend anything you say in an interview.
For an academic CV you should focus more on your publications and academic work etc. and keep your personal skills section fairly short. When given silly form type CVs to complete don't feel obliged to complete all the sections. I would definitely just remove the Artistic skills section if I was doing this (I have none!).
Here is a similar template which also has some basic instructions and an example (admittedly non-scientific) http://europass.cedefop.europa.eu/en/documents/curriculum-vitae/templates-instructions
For advice on writing actual academic CVs see http://www.careers.ox.ac.uk/wp-content/uploads/2012/10/Academic-CV-2012.pdf

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text:
When to approach my dissertation supervisor?
I am about to start a masters degree in the UK.
Our induction day is late next week and on this day we will have a talk on choosing our modules and preparing for the dissertation. Formal teaching begins in 2 weeks time.
On the website it says that we can select dissertation topics listed on the website or if we have a topic in mind, we can pursue this as long as we can find a supervisor.
Say I have already found a topic that I would like to pursue.
Would it be inappropriate to contact the supervisor for that topic this early before the start of term?
Or should I wait after induction?
I do not want to miss out on this topic.

I'm not sure about the UK, but I think that in general, it is better to contact the supervisor soon. Btw, you really call the master's project a "dissertation"?

yeah I call it a dissertation and so do most universities I have come across lol

Guidance is typically provided on when you'd be expected to come up with your research question and your nomination of supervisor. Follow that guidance. If you haven't been told yet, then at least wait for the induction week to find out how things are organised. To kick off on choosing a dissertation topic and supervisor before induction really would be too early. Indeed, it would just look silly. So at the very minimum, do at least wait for two weeks.
On our (UK) Masters courses, the selection of thesis topic and supervisor doesn't happen until the second term. That's because the taught modules in the first term gives the students the grounding in research skills and research areas, and an introduction to the staff, that enables them to make better decisions.
If a student approaches a member of staff earlier than that, then a common response would be to note the interest, and to invite them to come back in the second term if they were still interested, but that there's no commitment to do so, as lots of things change after the first term.
An early approach does not necessarily make a good impression. It can look hasty. It can look like you're not expecting to learn anything in the first term.
And we don't really do reserving of research-questions, as such. At least, merely being the first to propose a research question for your dissertation doesn't give you priority in doing it. We work with students to get the best match of question, student skills, and supervisory support. If student B provides a better match than student A, then we'll recommend that student B does that dissertation, regardless of whether A or B proposed it first. In recent cases where we have had overlaps between particular students, then the research area has has sufficient open questions that the students have each been able to do a distinct dissertation within it (and indeed subsequently co-author papers together). So I don't really recognise this notion of "missing out on a topic".
It takes quite a bit of subject familiarity to understand where the open questions are, and that's one of the reasons why we wait until the second term before we get to topic and supervisor selection.

I think this answer, like mine, is just common sense. No contacting a potential supervisor doesn't guarantee you a project, no you're not forging a binding contract for either party... but is it really "inappropriate" to contact a fellow human doing interesting work that you might like to work with in future? I'd still vote not.

It would not be inappropriate to contact a potential supervisor in advance. Getting in touch early and specifically mentioning your topic of interest seems a good idea and an opportunity to make a good impression.
A potential issue is that, assuming the MSc begins with taught courses, you may meet other academics you'd rather work with or your interests may change before the project begins. Still, informal discussion about a potential project down the road would be fine.

MSc courses do begin with a taught course and we work on dissertation over the summer. However I think they want us to choose a topic and a supervisor at the start of the course.

In my experience having done an MSci in the UK, if there is a list of possible topics there will probably be a process to enable people to best choose a project suitable for them.
When I did it we had to rank our top 5 or so projects from the list by a certain date and then you would be assigned one from your selection. This was because most projects could only support a pair of students and some would be very popular.
I suspect most institutions will use some variant on this sort of system, in which case contacting academic very early is of no advantage and you will only have less of an idea of what you actually want to do. In any case I would at least wait until you know what the system used is.

authors: ذوالفقار الحميداوي


text:
IEEE rejected our article after minor revisions because the reviewer did not understand a small issue. Is it likely to succeed if we appeal?
I submitted an article to a certain top IEEE  transaction journal, and after a year and a half of peer review, it was finally rejected. During this period, we got a chance to make minor revision.The paper was then sent to two new reviewers. One of the new reviewers made several rounds of incorrect comments. In the latest revised version, I clearly addressed his error issues. However, he deliberately claimed that he could not understand it and said that my notation was problematic. As a result, the paper was rejected.

How do you know the reviewer deliberately 'could not understand it'?  In general, as a reviewer, I want to be able to extract the key ideas in the first read.  An important aspect of writing a paper is to write in a manner even a 'non-expert' can walk away with the key ideas.  Similarly, when you write the responses to reviews, you have to explain your reasonings like to a 10 year old.  It is possible that you wrote the paper to be understood by you only.   A reviewer is likely to reject a paper that he/she doesn't understand, just to be on the safe side.

You are so right, I totally agree. We have answered and explained the reviewer's questions in detail in the current version of the appeal, hoping to get a good result.

No, it is very unlikely to succeed unless you do major modifications, addressing the concerns of the reviewer(s). Even then, resubmission after rejection may be impossible.
Most important, however is to try to address the reasons why you weren't understood. Was your notation non-standard, for example? And if so, was it completely and clearly explained in the target language.
What you write here seems like two people talking past one another having different backgrounds and/or assumptions. You need to address that if you want success. It isn't up to them (and future readers) to try to understand you if you are insufficiently clear.
Your words "deliberately" and "unreasonably" worry me. Complaining to editors of unfairness or claiming the reviewers are idiots will get you exactly nowhere.
Even for another journal, you may have a lot of work to do. In the long term, high standards are to your benefit as well as that of the world of scholarship.

Thanks.  The response letter to the reviewer’ comments and the revised manuscript have been  sent to the reviewer.  I  believe that I have adequately addressed the concerns raised by  the Reviewer  and made significant improvements to the manuscript.  I will carefully consider what you suggest.

Do not continue to re-submit to the journal that rejected your paper.  Try another journal.

But the reviewers did not understand our method, which can be explained. Regarding the erroneous conclusions he mentioned, we all have theories and experiments to prove that our arguments are correct. We are not happy that such articles are unreasonably rejected. At present, an appeal has been applied, and the journal is processing it, but I don't know the probability of success.

@zhangyuan It's your job when writing a paper to explain your method, so when a reviewer doesn't understand it this is seen by the editor (who will have chosen reviewers they expect to be able to understand papers in the same general area) as a fault with the paper, not the reviewer.

Thanks.I totally agree with your point of view. We have provided detailed instructions and explanations for what the reviewers did not understand, and hope to get a good result.

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


text:
Is a non-tenure track lecturer position in math a suitable stepping stone to a tenure-track position?
The background: I'm a postdoc in mathematics (U.S.) and approaching the end of my postdoc term. I applied for permanent academic jobs last fall and did not end up getting a tenure-track job offer. It was somewhat surprising; I have a very good publication record, in both quality and quantity (e.g., regular papers in "top 20" pure math journals). As recently as a month ago, it seemed that my academic career was over. But I was fine with it---I also got an offer for a good non-academic job (though it is currently unofficial; it will be some time before I get an official offer).
The situation suddenly changed when I learned that my NSF grant application (the standard 3-year research grant) from last fall had been funded! I talked to my postdoc institution about the situation, and they have decided to let me extend my postdoc another year so I can apply again for jobs in the fall. A couple weeks later, I was unexpectedly contacted about an open non-tenure track teaching-oriented lecturer position at another university and quickly offered the position. It's a good offer (aside from the detail of not being tenure-track), though it would be an unusual situation to hold it as an NSF-funded researcher.
In summary, I have three options: (1) take the lecturer position; (2) stay put at current institution another year and apply again; (3) hold out for the non-academic job. I'm inclined to take the lecturer position, but I also wonder if this would be a career-limiting decision. If I stay in academia, it is with the goal of getting a tenure-track job, so I want to get a sense of what is the most viable path forward.
Here's my question: how much upward mobility does a person generally have after taking a lecturer position? That is, should I expect the chance to land a tenure-track job at a future point, or will I effectively be out of contention?
And the answer should be weighed relative to the alternative of extending the current postdoc.

Please ask only one question at a time. And a substantial part of your question as-is is rather dependent on individual factors and thus not really on topic here. Try to edit the question a bit to make it more focused and answerable with a general answer.

Related? https://academia.stackexchange.com/questions/181133/instructor-to-assistant-professor-transition/181137#181137

Key for this question is to define what the "lecturer" position entails. Everyone is assuming it's a teaching job. You should spell that out explicitly.

Does this answer your question? Instructor to assistant professor transition

Something doesn't compute.  How did you get the grant, yet not succeed in getting a position?  Which was more surprising to you, your friends and colleagues, your advisor?  Are there factors that would count against your hire but not the grant?  In retrospect do you think you could have put in more effort in the job hunt or been less selective?

As a mathematician funded by a 3-year NSF grant, you will be in my opinion a very strong contender for assistant professor positions at many US mathematics departments. You are basically ahead of 99% of the competition in an important parameter. That is a very good signal. In order for you to fail in the next tenure track job search, I think you’d either have to be very picky about geographic locations and/or institutional prestige (pickiness always makes things more difficult, obviously), or you’d have to send some very bad signals that would negatively offset the good signal. (Added on edit:) Or the job market could tank catastrophically, leading many other strong candidates to have a poor outcome.
Now, this analysis remains true whether you are a postdoc or a lecturer. So I think from the point of view of a hiring institution, they are not going to care much about your current job title - they will see your NSF grant, and evaluate your papers, letters of recommendation etc, and that will be their basis for deciding whether to offer you a job.
It is true that as a postdoc you will have more time for research than as a lecturer, so indirectly that might lead to better prospects of getting a tenure track job. But given that you’ll be applying in the fall, the amount of additional research you can generate as a postdoc compared to a lecturer in time for it to be considered for the current round of applications is probably not large anyway.
The reason that one does not see much upward mobility (as you put it) for math lecturers is mainly that the sort of people who are good enough to end up with a tenure track position are also good enough to line up another postdoc if they are temporarily unable to get a tenure track job. They can thus continue focusing on their research, which maximizes the chance for success. In the uncommon situation that a person in your situation decides to prefer a lecturer position to a postdoc, I don’t think the mere fact of being a lecturer should negatively affect how you are perceived, especially since, as I said, having an NSF grant shows you to be a more active and successful research than almost all postdocs, and indeed than even many tenure track researchers.
Good luck!

I think this is the best answer. The NSF grant makes this a completely different question from just asking about extending the postdoc versus taking a lecturer position. Applying for your first TT position with an NSF grant in hand puts a candidate in an usually strong position.  When I see that in an application I'm evaluating (in my US math department), it almost completely overrides consideration of what kind of position the candidate is currently in.

I doubt only 1% of your applicants have an NSF grant, but of course you're in a department that hires regularly and you have the statistics.  In any case, it doesn't help to be in the top 5% of applicants if only 3% of applicants get an offer.  (And I would not be surprised if, of all the pure mathematicians who send in at least one application to a research-oriented tenure-track position, only 3% get an offer for such a position.  Of course this is considering a pool a significant percentage of which is obviously not qualified.)

I don't think it's appropriate for you to be so optimistic about the questioner's chances.  If there are 50 positions on the market next year, you'll be right.  But there might only be 10 positions on the market next year.

@AlexanderWoo: Could you clarify whether the number 10 in your lower estimate "But there might only be 10 positions on the market next year" refers to all (research-oriented, whatever that means) tenure-track positions in pure maths or only in a specific sub-field? (Because for all of pure maths 10 would seem like an extremely low number for a country as large as the US, wouldn't it?)

@JochenGlueck: To say something that's precise enough to track - I would mean tenure-track positions in pure maths at a PhD granting department in the US.  Yes, 10 would be extremely low number, but unfortunately I don't think it's out of the range of possibility in the event of a significant economic downturn.

Upvoted. I might add that even tenure track applicants at research departments now often need to show some teaching experience/ability. Top ranked liberal arts schools look for both research and teaching. They might be on your radar next year. The teaching lecturer job might be a good addition to your cv.

@AlexanderWoo good point, edited the answer to tone down the optimism…

I know at least one example (from around 2005) when a differential geometry with a regular NSF grant had to settle for a 3rd postdoc in the US.

@AlexanderWoo it doesn't help to be in the top 5% of applicants if only 3% of applicants get an offer - Umm... I think it helps a lot, especially given all the randomness and non-linearity involved.

The one thing I'd add is that it can be tougher getting a TT offer from a teaching oriented school when coming in with like 4-5 years of postdoc and a big gap in teaching experience. That's not a problem if you get a research focused position of course. So even if you continue for 3 more years in a research postdoc, make sure to stay sharp with teaching skills and to be able to market that part of your skillset.

For better or worse (actually: for worse) it is very rare that someone who had gotten onto the lecturer track (where your emphasis will be on teaching) to get back onto the tenure track. Part of that is just practicality: Your job is to teach, and do so to the exclusion of having time to do much research. As a consequence, after a year or two you will see that people on the lecturer track no longer have new publications coming out. Part of it is also just perception: Someone has apparently chosen teaching as a career, whereas there are plenty of candidates who have chosen research.
Which of your three options you pursue isn't for me to recommend.

Part of it is also just perception: Someone has apparently chosen teaching as a career, whereas there are plenty of candidates who have chosen research. - If I see someone applying for a research position (TT or postdoc) from a lecturer position, my assumption is just that they were unsuccessful in their last search in getting a research-oriented position.

(Mathematician at a research-oriented US university)
If you aim at a tenure-track position, especially at a research-oriented university, then I would recommend extending your postdoc.
From the standpoint of hiring committees, in principle your decision shouldn't matter, as you should be evaluated on the strength of your record. In practice, you might look slightly better applying as a postdoc, as opposed to as a NTT lecturer.
From your point of view, moving, adjusting to a new institution, and carrying (presumably) a high teaching load seem likely to be a major distraction -- right at the time when you'll want to focus on your job applications. This seems unlikely to be helpful, unless you would be interested in staying there for multiple years.
Between the non-academic job offer and trying again for academic jobs next year... I really can't say, that depends on your priorities and how the job market shakes out next year. Unfortunately the academic job market is getting worse, and many deserving candidates are not getting good job offers. On the other hand, many still are. With an NSF grant I would hope that you get multiple strong offers, but it's impossible to predict.
Good luck.

This is a pointed non-answer.
I am assuming you applied widely, essentially to every tenure track job you are remotely qualified for.  I am also assuming that you didn't fail miserably at interviewing - that if you had interviews you gave reasonable job talks and were pleasant with the people you talked to.
Your situation is basically unprecedented.  Think of it this way: of the members of the NSF panel that recommended your grant for funding, something like 6-8 of them were probably from departments most of whose faculty members do not have an NSF grant (and 2-3 from a department most of whose faculty members never had an NSF grant).  This basically means none of those departments, or departments with similar evaluations of applicants (and departments don't vary that widely) were hiring with openness to hiring in your area.
Pre-pandemic, that would never have happened.
For the non-tenure-track position, I am assuming it is a teaching-oriented, permanent position.  You should expect that you will get no research done while in this position, though (assuming you don't teach over the summer) you can use summers to write up the research you are doing now.  In the past, people (and not just one or two exceptional cases) have managed to get hired into research-oriented positions after 2 or 3 years doing minimal research on the strength of their past research and the continued output based on work in progress.
However, as already noted, the current job market is unprecedented, and I don't really know just how bad it is.  Past experience isn't going to help predict the future here.

Can you elaborate on the third paragrph about the situation being unprecedented? I couldn't follow the point you were trying to make.

I do not see this as unprecedented: In over 30 years (US academic life) I saw enough randomness in hires and grant awards not to be surprised by anything.

@mordecaiiwazuki: Given that the panel recommended the grant, there were at least 6-8 mathematicians whom we know would have strongly recommended them for hiring in their department if they had the chance.  Pre-pandemic, that alone would have been worth an expected 1-2 offers, and that's not counting the vast majority of research math departments not represented in that NSF panel.

Consider that unless you get a job at an R1, whatever tenure-track position you get will involve a lot of teaching. I have been in many tenure-track search committees, and every year we look more and more at proven teaching experience. In other words, we discard all of those BS teaching philosophy statements and look at your actual experience. In my eyes, a successful NSF grant AND solid, verifiable teaching experience tells me that you are a person who can write grants, knows how to balance a teaching load, and knows what you are getting into.
I always tell my students that you should judge your past decisions based on the odds you had when making the decision. Gambling at the casino is a bad decision even after winning the jackpot, because you gambled with the odds against you. Gambling you'll get an R1 tenure-track job is in my opinion, always the wrong decision (even if you were to get it.)
I would take the lectureship, balance teaching and research, and not miss a bit applying to tenure-track positions from day 1.


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Uninvited involvement in postgraduate supervision
What is your opinion about another member of staff, uninvited, requiring postgraduate students to discuss their research with him, not even informing the actual supervisor and even requiring / insisting on significant changes? This uninvited intruder has considerably less supervision experience, research experience and in fact lower indices and international accreditation than the supervisor but is the head of department. There is no problem in terms of relationships between the various students and supervisor (in fact those relationships are good - quite possibly excellent). When the topic is raised by the supervisor with the HoD he says it is normal academic practice. He has never indicated that he thinks there is any problem with the current supervision.

Talk with your supervisor and let them deal with him.

Generally "what is your opinion on (...)" style questions do not work well here in Stack Exchange.

As for your question - I would not touch the "lower international accreditation" wasp's nest in this argument; no good can come from this. The question is - based on your regulations and customs, can the department head interfere or is the research direction solely up to student and supervisor? If it's the former you will need to live with it or change regulations. If it's the latter, you can more or less politely ignore his feedback.

My impression from your question is that you are very upset by this. My first advise is not to take any of this personally, and assume that everybody involved means well (even if the execution of those intentions may leave room for improvement).
The process you describe does not sound uncommon to me, though the execution seems (based on the limited information in your question) awkward.
In academia advisors have a lot of power over the people they advise. The vast majority of advisors handle that power correctly. But if you hand many people such power, then there will always be some who abuse it. Abuse can take a lot of forms, it can range from not adequately advising the advisee, up to abusing their labor or worse. So it is sound policy to regularly (say once a year) "check up" on all advisees, no matter if there are complaints or not. That way the university can keep an eye on whether the advisees are "on track" and give the advisees a more or less secure possibility to voice other concerns.
As an well intentioned (or so I say) advisor, I see such a process as a potentially helpful "second set of eyes". However, a lot depends on how such a process is implemented. At the very least, the purpose of this process was not clearly communicated to you, nor the status of his "advise".


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How has academic research on Massive Open Online Courses (MOOCs) improved MOOCs?
It seems that the number of more academic papers on Massive Open Online Courses (MOOCs) surpasses the number of MOOCs. Is there any indication that academic research on MOOCs has actually improved MOOCs? And if so, in what way?

I like this question a lot, but it seems a bit broad for a SE website.  You could probably write a research paper (or at least a lit review) on this topic.

Interesting although very vague. What does 'improving' mean in this context? Also, the assumption? There are more published research papers on MOOCs than there are MOOCs actually available to study with? Not quite sure. Then if educational research improved education, the world would be very different, or maybe it does already.


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Does having external funding raise your chances of getting accepted ? ( Masters )
My UG university have awarded me a scholarship for master's degree ( I'm an international student ) the scholarship pays for all expenses of the master's degree for the whole duration of the study.
I would like to know if this raises my chances to get accepted for a masters program ? Does being a "risk free" student gives me more leeway?

a scholarship for master's degree, Did they say it's the master degree for the graduate school at your current undergrad school or any other university? The expense of master degrees varies a lot between universities.

I was given a list of 30 universities that I could apply to that the scholarship covers. ( all US universities )

It might be relevant to say whether or not you plan to continue to a Ph.D. If not, It might not help you as much since students are normally self-funded for terminal Masters anyway.

Your situation is the same as self funding. When you apply for F-1 visa, they are going to check if you have enough funding (self or scholarship) anyway. It has little to do with risk free.

fkraiem: Part of the scolarship is that you have to continue the study to PHD, I did mention that in the SOP.

It does show that your former university has several k$ of confidence in you. I think that speaks more than any added economical stability.

In the science and engineering fields in the US, where nearly all graduate students are supported by teaching or research assistantships (TA/RA), academic departments have to decide whether an applicant is adequately prepared to be a successful student in the program and whether the student can do the TA/RA job.  When the student comes with their own funding, that second question doesn't have to be answered.
In my department (mathematics) it's quite common to have an applicant whose academic preparation is good but whose English isn't good enough that the student could be successful as a TA.  We would typically admit the student without offering the student an assistantship.  Most applicants that are offered admission without an assistantship don't enter the program.  However, if the same applicant came to us with their own funding, we'd admit the student.  So, having your own funding might help.
There are some costs associated with having a student even if the student has their own funding for tuition and living expenses.  Supervising a graduate student takes faculty time, and some faculty are only interested in supervising PhD students and less willing to work with MS students.
Also in the lab sciences and engineering students need access to research facilities, equipment, and supplies to conduct their research.  Students who are funded as RA's under a grant also come with grant funding to cover these costs.  Depending on your area of study, you might have to convince the department (or perhaps an individual faculty member) that you would be able to contribute enough to the research activity to justify these expenses.

It may depend upon what field you are in, but in biology in the USA most universities I know would be much more interested in a student if they brought their own funding!


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Why is Scientific publishing methods at stagnation in this age of internet?
To be specific, I have a few questions regarding the Review and Publishing methodology.
1) Why are there no comments sections in the Journals where the first reviewers (or anyone who has read the work) can provide their feedback and it remains open for everyone to see. Isn't it a transparent method?
2) In today's world, journals like 'Jove' are coming up where the videos of the actual experiments can be uploaded, why is that it has not been picked up in the Physics community? This is not only important for Experimentalists but for the Theoreticians too.
3) Where can these suggestions and feedback be provided to the Journals?

Please ask one question per post. These are three separate questions with independent answers, so you can ask them in three separate posts.

Also, I believe How is publishing in JoVe (a "video journal") perceived? addresses your second question - the answers there explain the cost and difficulty associated with producing a video.

Also, the premise to your second question is wrong: Most journals nowadays accept supplementary materials, including videos. However, most experiments do not allow for videos that one would like to watch.

Your point 1 was discussed in part here: Towards a Stackexchange-like comment/reputation system for research papers

Why do you assume that the "new" way is better than then old or tested way, without any proof? New does not equal better or improved.

PubMed allows comments.


text:
My Professor is pushing me in a problem that isn't solvable for the deadline
I have a month to finish an undergraduate research project required to receive my diploma and I am facing the situation when an undergraduate is too low in the academic scale to fight his/her professor, a very stubborn one indeed. Just to say that in a previous situation I warned him/her about certain approach that I knew was not going to work (because I checked) and, besides being scolded, was obliged to loose an entire month of my project doing menial things.
Yes, I made mistakes too. This is my first research project in his/her field and some scripts needed corrections. I don't want to sound that harsh. The professor went discontented and very stressed for a couple of weeks due to finals and similar stuff and, during that time, the amount of data exploded.  Furthermore, He/She is an excellent Human, willing to support you in every possible situation, but, when it comes to work, I have been feeling like Sisyphus, pushing a stone that goes nowhere for most of the project and then obliged to fix up everything that went wrong (and made responsible of it).
I put sweat and tears in the project expecting, after all the ordeal, something good will come out, but this definitely won't happen. The project involves funding and my professor wants the most accurate results, but I have to think about myself and my graduation too. This is Computer Science and, although we have lots of machine power, there are always amounts of data beyond our capacities. Did anyone in computer science had a similar problem with his/her advisor? What did you do?

What does your professor say? What is his/her point of view on the topic? Does he/she acknowledge that the problem is not solvable?

Right now, I have to admit I'm having a hard time understanding your question. Could you focus on specifying that more precisely?

I have been feeling like Sisyphus, pushing a stone that goes nowhere for most of the project — So, real research, then.

@FedericoPoloni I think he/she is not aware of this fact yet. Although, I tried to make it clear once, but the professor said, in summary, "run the process, your are wrong..." That was past friday. I checked the process today and is still in very beginning.

This might suck to hear, but I've found that if you bang your head against something long enough you'll find some kind of solution, even if its a bizarre trade off of one thing for another. Case in point, I've written a real time raytracer in JavaScript / html5 (not webgl!). Basically I got "dirty rects" working for raytracing so the number of rays cast were very low.  I hope you can find an imaginative solution to your problem (:

@AlanWolfe I don't know if that is applicable in my case. I am not using my software and he one I am using is suppose to be the best of its kind in the moment. It is only that I have too much data. In this point, I am just suppose to feed the computer and wait for the data, but in four days barely 1% has been processed (Just checked).

So, if I understood you correctly, your professor wants you to run some time consuming program on the data, and it will not be finished before the deadline for your graduation, right?
If that is the case, you can just include in your report the subset of your data that is finished, indicating that the rest is being processed. Try to make that sample as representative of the whole, if that makes sense in your case (so, if your data goes from x=0 to x=100, try to get evenly spaced values of x, not just from x=0 to x=1.5).
 After all, what you need to show for an undergrad project is that you know how to do research, but not necessarily get results all the way.
Another thing is that if in four days only 1% has been processed, it would take a full year to process the whole dataset. You seem to need* either more computer power, or rethink the strategy; but now you have some hard data to bring up to your professor. Then, it is up to him to decide if he can get access to more CPU muscle, or if a compromise in the quality is acceptable.

Check also your cluster occupancy. If you are sharing it with other students with the same deadline, it is possible that it very crowded; more resources may be available after the deadline has passed.


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Is it acceptable to use MS Equation 3.0 for a journal paper?
The title sums it up pretty well. I'm using MS Word to write a paper I intend to publish in a SCI journal. It will contain ~15 equations (non-trivial ones: integrals, sums, fractions, special characters, etc.). I'm fairly efficient in Word, but have absolutely no experience using LaTeX.
Please correct me if I'm wrong, but I'm under the impression that once a paper is accepted, it is edited to conform with the journals publishing style, as opposed to some conferences, I attended, which provide a pre-formatted Word document in which I have to place my work before applying to the conference. As the journal provides no such template (but accepts .doc format), I was wondering if there could emerge any issues regarding the equations.
PS: the field is computer science

I hear it depends on the journal, some will just reformat your paper. Its best to check with the journal.

If they accept .doc probably they also accept MS Equation. However, the best you can do is ask them directly.
Anecdote: A couple of years ago I prepared the proceedings for a major CS conference. We had about 120 accepted papers and only one of those was written in MS Word.

Thanks, the anecdote is quite enlightening. Before grad school, I've literally had no encounter with LaTeX, sure, I was aware of its existence, but assumed always it was intended for mathematicians and the more mathematical aspects of science. It wasn't insisted on in my department, either. I guess, the next paper I write, I'll try with LaTeX. If for no other reason, than to feel the pros and cons for myself.

@iliasfl Back to your anecdote, did the authors write their papers with LaTeX? Or any other open-source software?

@Parsa Yes, everything else was written in LaTex

LaTeX has its own learning curve, but once you have written a couple of papers with it, it soon becomes easier than working with MS Word. In the end I wrote my thesis in LaTeX, one of the great benefits was being able to keep each chapter in a separate file, and import some chapters direct from PDF (they were published papers).


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How to filter data obtained with practical measurements and simulations to be concisely put into a paper?
I'm a PhD candidate in Computer Science and I'm working on my first paper that should be published in a peer-reviewed journal (until now, I published only papers in conferences).
My project is a FPGA memory module, which uses a specific approach (the main idea) to obtain better performance in terms of access philosophy and capacity.
Now, the mentioned idea is naturally the bulk of the paper, with the math, proofs, algorithms, etc. behind it. But, since the module was synthesized and tested, I feel obliged to address its obtained "measures".
The process generated quite a lot data which become even more after the simulations were done. So, I'm not sure what charts/tables are appropriate to analyze and publish in a paper? (e.g. input->output delay for a range of inputs; parameters like max clock, number of logic elements; perhaps even (parts) of the schema; etc.)
As this seems a bit specific, I would like to broaden the scope of the question. Namely, the general issue here is how to filter data which does not directly contribute to the understanding of the main idea, but is the result of a finished project and can be used to reinforce the researched concept with practical measurements and simulations. This obtained data is large, so I'm asking for guidelines what could be considered concise enough to put into a paper.

What is FPGA? Is it an academic term? If not, why does this question belong here?

You need to generalize your question so that non computer science users could understand what you are asking.

FPGA = Field=programmable gate array.

I can agree to that, I edited the content to be hopefully more generic.

@user3209815 - Please keep the tone of dicourse professional and courteous. LMGTFY links are inappropriate here.

This question appears to be off-topic because it is about computer or computational science.  There are SE sites devoted to each of those, and the question will probably get a better answer there.

@DavidKetcheson yes, perhaps the question is not worded well, but it is about writing an academic paper that involves a lot of data. Please look at the forest, not the trees.

Do you have a target journal in mind? If so, this could help steer you into a more algorithms/proof direction (with only the "important" measured data included) on one hand, or a more performance-oriented direction (with only simplified high-level concepts included) on the other hand.

Read a couple of dozen papers that are similar in nature (that is, in terms of the method and how the research question is addresssed) to yours and are in your target journal. Look at how they've supplied the sort of detailed information you're talking about.
As a rule-of-thumb, put it all into supplementary information. And then follow the advice of your edit and peer-reviewers, if they advise moving things. If there are particular numbers that contribute to your main narrative, put those numbers in the body of the paper, too.

Use the Internet
Put the raw dataset in an easily accessible format (and it's description) on a public online repository, preferably in one actively maintained by your institution - most of them seem to have such resources.
If it "does not directly contribute to the understanding of the main idea", then simply refer to the relevant URL in your paper - the data is still useful in verification, replication, and further analysis by others.
Do make sure that the repository and URL is one that would stick around for decades, not only a couple of years.


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Should I apply for a research Internship if I'm not in touch with the subject matter?
So, I'm doing my undergrad in physics in India. I want to apply for research internships, but when I read professors' CV's and stuff they are doing reasearch on currently, I don't understand anything, it's way too complicated, I see things like " X-ray Binaries, Neutron Stars, X-ray Polarimetry , quantification of non-linear quantum correlations at very low light intensities. etc. ".
It seems way beyond what I can comprehend !
So, if I have no idea about what they are working on then should I apply for the reasearch internship ?

It's normal to feel overwhelmed with the complexity of such advanced topics at your level, the goal is to learn about it progressively. However if you don't even feel interested in discovering the topic, then there's probably no point applying.
In order to start evaluating your own interest about a particular topic before applying, it would be a good idea to read a bit about it. you won't understand everything of course, but this way you can get a sense of whether you like the topic or not. This will help you choose, and it will also help you get accepted in case you decide to apply, since an advisor is more likely to choose somebody who knows at least a little about their topic.

What I'm afraid of is, I get accepted and then the professor talks about highly advanced stuff which I don't know, then he thinks I'm useless which ruins the whole purpose of the internship

As a general rule in research, don't be ashamed of what you don't know, just keep learning! Nobody knows everything, the professor is unlikely to expect you to know a lot about a particular specialized research topic. If he accepts you then he thinks you can do it. Unless you pretend to know something that you don't (don't do that of course), it won't be a problem. Be straightforward with the advisor, say that you don't know much but you want to learn.

Research broadly each of the topics that you might be interested in, and use that to help you narrow down the fields you are interested in, and then apply for research internships in those fields.  Most of these professors are focused on extremely specific research topics and it is generally expected that undergrads like you will struggle to grasp the concepts as opposed to the concepts that are more generally taught in the classroom setting.  You just want to get a general taste of what the field might be like.
Finally, when it comes to actually applying for internships, try seeking the help of an advisor of professor at your institution that you may know as to which field might be the best suited for you.  In addition to that, figure out where your interests are, and apply to as many research internships in those areas (I'd even suggest contacting some faculty behind those internships for advice to get an idea of where you stand), because the worst they can do is say no.


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Can any study answering or finding more about a relavant question be done as a research paper?
Can something like
'How does quantum computing accelerate mathematical modeling ?'
OR
'Variation in smartphone radiation with signal strength and age'
OR
'High speed object recognition with the HB100 radar module'
OR
'Effect of social media on human behavior'
Be published as a research paper ?
I know this is trivial, but most research papers I read had very deep and highly specific topics so I was wondering anything along the lines of the above can become a research paper.
(I included these samples above because I thought they were all broad and different kinds of stuff)

A paper is there to answer a question. The problem with broad questions is that they often don't have answers at all, or they have many answers, or that answering them takes more than one book to write up. In any of these cases a paper is not the right format for writing up the results just because of the space limit implicit in a paper.
More seriously, with such a broad question it is very hard to organize your research project and get it done. You'll typically end up doing lots of loosely related things that in the end just don't add up to anything meaningful.
This does not mean that you cannot tackle large problems. It just means that you need to break them up in smaller, more manageable pieces, and tackle those one at the time. Afterwards, you or someone else can write a review or a book that brings the pieces together. Moreover, something like this is often a group effort and not something that is done in one or two years, but rather many years, or multiple decades and for really broad question one could argue the time frame is in terms of centuries.


text:
Awaiting EIC Decision
I submitted an article 10 days ago. First at the dashboard, they put under review. After one week, the dashboard put Awaiting EIC Decision. Is that bad?

Could it be a “desk rejection” decision? Maybe. But I would say, stay positive and wait few more days. Good luck!

The answer is that we can’t know. The status of the manuscript is exactly what it says on the tin - that it’s awaiting the decision of the EIC.
Trying to divine why is a bad idea. It’s possible that the original review notice was internal, not external. It’s possible the reviewers turned things around super quickly (my personal record is a single day). You can spin up a number of “just so” stories about the status.

What does EIC mean?

Editor-in-chief


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How to publish superseding results without creating enemies
While working on a research paper with a coauthor, I found an unpublished paper in arXiv and discovered out that the technique we developed in our paper can be used to improve a result in the unpublished one. Specifically, we can design a superior algorithm to solve the same problem solved in the arXiv paper.
If we publish our results, then the author of that arXiv paper will have a hard time publishing his paper, since some journals will not consider his algorithm once a better one is available.
Of course, we cite the arXiv paper and there is no law against publishing improved results, but this may harm the author of the arXiv paper. Is there a way to publish the new result without creating enmity?
One potential option could be to combine the work and submit a joint paper. However, the papers do not "mix" very well since our paper is mainly about a different technique - the improved algorithm is only a usage example of it. Combining the papers will create a very large and inconsistent paper.
Another option is to wait until his paper is accepted for publication and only then publish our paper with the improved result. However, it seems unscientific to withhold results that we already know.

Normally, citing the result you're superseeding should guarantee it will not be depreciated by your work. Or if it will, it's between the authors and their referee rather than them and you...

Notify the author of the paper you found. Offer to co-author a paper with them to extend their results. Publish your own results, mentioning in the conclusion that you intend to pursue related work in a separate publication.

How old is the ArXiv paper? If it's already a few years old, the authors probably aren't going to formally publish it. But, as @Roland says, you should ask them.

This happened to me. My arxiv paper was about 5 or 6 years old at time. My fault for letting it sit and not pursuing publication. Live and learn. My paper is still a much easier read than the one that superseded it though, so I have that at least! It would have been nice to be contacted beforehand, but I don't see why that should be required. If you have a status/power-dynamic to worry about, and think there is a chance they will be unreasonable, then maybe think carefully about that. But you are well within your right to publish and cite the arxiv results.

I disagree with the premise of your question. “Publishing superseding results” is basically the same as what’s known as “publishing”, since all papers build and improve on the existing literature in some way and push some older work slightly toward obsolescence or irrelevance. The extra twist in your situation that you are improving on unpublished work is of hardly any consequence and simply not worth worrying about, for the following reasons:

As others have said, the authors of the arxiv preprint still have precedence and will get credit for making their contribution at the time they did, before your subsequent improvement was discovered. Referees and journal editors should (and almost certainly will) take that into account, within reasonable limits.
In general, when you improve on earlier work you show that it is interesting and relevant enough for other people to follow up on. This is actually flattering to the authors of the earlier work, even if you imagine that it is unflattering (it’s also true that an improvement can sometimes portray earlier work in a slightly unflattering light, but my point is there would still be a separate flattering aspect that I think you are ignoring, and which in most cases will far outweigh any supposedly unflattering aspects).
The publication status of the earlier work is simply not your concern. It is up to individual researchers to submit their work for publication and otherwise promote it in a timely manner. If they fail to do so, they have only themselves to blame, and they should not expect others in the scientific community to delay their own follow up research, at the cost of hurting their own careers and slowing down scientific progress, out of pity or charity.

To summarize, I think the idea that you will make enemies by publishing honest work that you did in a STEM field, regardless of the specific circumstances, might make for a cute plot element in a satirical TV show or novel about academia, but is not a realistic thing to worry about in real life.

I agree with this answer. To cite a famous anecdote in the history of mathematics when Russell found a paradox just when Frege's Vol 2 was about to go to print, "Hardly anything more unfortunate can befall a scientific writer than to have one of the foundations of his edifice shaken after the work is finished..." So, to the OP, you don't see Frege frothing at the mouth when his work was "improved" by Russell.

@TitoPiezasIII It's stated in a very controlled manner, but isn't Frege saying that having your work later "corrected" is the worst possible thing that can happen? He handles it in a very mature manner, but his comment seems to imply that later "corrections" could very much rub someone the wrong way.

@NuclearWang Frege there is commenting on Russel finding a fundamental mistake that made all of his past work invalid. It's kind of a different situation of someone finding an improvement on a result of yours.

' “Publishing superseding results” is basically the same as what’s known as “publishing”, since all papers build and improve on the existing literature in some way and push some older work slightly toward obsolescence or irrelevance.' That simply isn't true, at least in mathematics and computer science. There are plenty of papers that solve previously open problems, and those papers don't supersede anything.

@DavidRicherby you’re right. That’s basically what I meant by “basically”.

@DavidRicherby: They supercede all the previous work that finds bounds on the solution of the open problem without actually solving it.

@BenVoigt There are plenty of papers in CS of the form "Here's an algorithm for a problem for which no algorithm was previously known." Such a paper supersedes literally nothing. There are plenty of papers in mathematics that solve some open problem for which no bounds were previously known. Ditto.

I agree with what Dan Romik writes in his answer. I write only to address a different aspect (implicitly addressed in his answer too), which are the notions, that seem to me specious, that ArXiv papers should be treated as "unpublished" and that "unpublished" materials should be treated differently from "published" materials.
An article on the ArXiv (or any other online repository) should be treated the same as an article published in a refereed journal for purposes of citation and judging priority. The word "publication" should be treated as a synonym for "dissemination", the only possible qualification being accessibility (and ArXiv papers are far more accessible than paywalled "published" articles!).
The purpose of citation is recognition of priority, acknowledgment of intellectual inspiration, and facilitation of consultation of related work by a reader. None of these objectives is much conditioned by the publication status of an accessible resource.
If a (correct) result is in a paper on the ArXiv, that establishes priority in the same way as if it had been published in a traditional journal. Likewise, a paper on the ArXiv can and should be cited if it would have been cited were it to have appeared in a published journal.
The distinction between prepublication and publication is archaic, a thing of the previous century, and the more so in mathematical areas where dissemination in traditional journals can take years.
Some authors do not cite work on the ArXiv for strange reasons - they haven't checked it, it hasn't been refereed, etc. - but this seems to me mostly just laziness or dishonesty - we should check what we use and never trust that the refereeing process eliminates errors.
As for what to do when your work improves on someone else's work - be glad you will probably have an interested reader and a competent referee for your work. Be generous in your acknowledgment of their work and they will likely react favorably. Don't worry about possible "damage" to them - journals are happy to publish work that has already been cited.

Thanks for the advice to "Be generous in your acknowledgment of their work ". I changed my wording accordingly.

I agree with @Dan Romik's answer, but I have a few things to say about this part:

The publication status of the earlier work is simply not your concern. It is up to individual researchers to submit their work for publication and otherwise promote it in a timely manner. If they fail to do so, they have only themselves to blame, and they should not expect others in the scientific community to delay their own follow up research, at the cost of hurting their own careers and slowing down scientific progress, out of pity or charity.

Indeed the OP should not delay his own work because he built on work that others made public on the arxiv.  (That it could be built upon as soon as possible is why they put it on the arxiv!)  I hope though that no one will construe this to say that the authors of the original paper have some kind of moral or professional imperative to publish their results before the OP does.  (In part I worry about this because of some other answers and comments on this question that seem to imply this.)  That's simply not the way the publishing industry works in my experience: papers can be rejected, or can be delayed for years, due to reasons that are entirely out of the authors' control.
If you would not have known or thought to put X into your paper until you read Y's paper then you are not competing with Y, you are building on Y's work.  I think the OP should write his paper to make absolutely clear that Y has priority on X and that X is in the paper because of Y's paper.  This really should make it easier, not harder, for Y to publish their paper, and if it doesn't, then it is definitely not your fault.

Thanks for the advice. I edited my paper to make it clearer that his work has priority (in fact, my work answers a open question explicitly asked by him).

I wouldn't sweat it, other than being gentle in the wording of the comparison.*  While the other technique may have worse results, it may still be preferable in some use cases or may still be publishable as an alternate method.  Even if worse at oil reserve calculation, it may work better at...sales force optimization.  Or there may even be cases where your techniques don't work at all and theirs do (e.g. algorithms that need large amounts of training data or combnation of results feedback with physical insights.)  And even if their method is worse for everything, it still might have some spark of an idea, by using a different approach, that helps someone else with some different approach).
But big picture their stuff will be what it will be.  Given that it's on arXiv, not published, this shows something about it (not dispositive, but Bayesian, if you get me).  Also, if they plan to publish, it might already be on track and may even be easier for them if they don't know about your competing results now (and have to deal with it).  After all your paper hasn't run the gauntlet yet either.
*It sounds like the comparison wasn't even per se the driver of your work, so you could even just note it as an alternate method.  More in the spirit of giving a citation to the other crew and giving the reader benefit of your lit search.  Of course, you have to use your judgment on how important it is to emphasize the performance battle.  But given you found it late, in arxive, I doubt it's critical.  Plus you did ask how to avoid antagonizing. And this is the way.  And much easier than trying to coordinate, warn, collaborate, etc. (which could all slow down or derail your paper).

"Given that it's on arxive, not published, this shows something about it (not dispositive, but Bayesian, if you get me)."  Sorry, I don't get you -- the arxiv is a preprint server, on which papers appear before they get published.  Could you explain further?

Papers on arXiv are published.  Specifically, they're published on arXiv.  "Published" literally means "made public".  They may not be peer-reviewed, but that's not the same thing.

Let's be practical:

Talk to the author of that paper. Tell them about your improvement, tell him you want to treat their work with the respect it deserves, and ask them what they feel would be fair/appropriate.
The author of the arXiv work could have a note or a brief section, either with or without your participation, mentioning how the result can be improved. He can then update his section of applications to take the improved result into consideration. That makes his paper not-superseded.
You can minimize your description of the improvement on his result, so that nobody can understand what you're talking about without reading his paper. You could even do that while showering some praise on his paper and nudging your readers to go read that one.

Like others suggest, however, I wouldn't delay nor refrain from publishing the improvement.

Point 3 is quite terrible. Please do not do this.


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Could putting a manuscript onto arXiv affect the probability of a journal accepting it (even if the journal explicitly allows pre-prints)?
I am wondering if anyone knows, thinks or has measured whether putting a paper on arXiv before submitting to a journal has any impact on the paper reviewing process and on it being accepted or rejected?
I do know why to put it on arXiv. There are plenty of reasons for that and it has been discussed exhaustively here and elsewhere in academia. This question is not about that.
I know that journals have different policies about this. I read them, I checked them, I am fine there as well. This question is not about that either.
My question is whether, in practice, there is a known impact or can anyone speculate if publishing to arXiv has a positive or negative effect.
For instance, the editor/reviewers can see the paper in the arXiv and can have a different position about it; some people might have experiences relating to that from the point of view of reviewer/editor/submitter.
It would also be very interesting to see statistics showing whether the reviewing process for random sets of manuscript submissions with and without preprint versions differ, but I would guess those do not exist yet.

If you receive feedback on the preprint, and use it to improve the manuscript prior to journal submission, presumably there's a positive effect. But I haven't seen any related statistics.

I also wonder whether if an ArXiv paper has accumulated many cites, does it mean a journal will more likely accept it?  I.e., can a journal use ArXiV cites to select articles that have a clear evidence of impact?

Good points both. The improvements is a bit more indirect. But the point raised by @Prof.SantaClaus is a good one. If the preprint has cites it indicates it is interesting for the community and also it may impress the reviewers.

"Can anyone speculate"? Sure, they can and will, but I don't know of even any anecdotal evidence where this mattered.
The closest example I'm aware of is this story: https://www.aps.org/publications/apsnews/201211/preprint.cfm
but even here the issue was really that the authors put out a second preprint that, at first glance, appeared to undermine their initial result that was under peer review. So it's not really the same issue.

As a reviewer, I greatly prefer reviewing papers that have been posted to the arXiv, as anything interesting I learn won't be privileged information. I'd rather not invest time into reading something which I'm forbidden from discussing with others.

As a Reviewer, the first thing I do when reviewing is checking if the paper has been submitted elsewhere. If I see it online in arXiv I will still conduct my review (impartially), but I will notify the editors that there may be a violation of CoC because it may void the "double blind" peer review.

I am an editor for two journals that allow arxiv preprints, and at those journals whether a manuscript is posted on arxiv has no influence on whether it is accepted.

My speculation is that posting on arXiv has little or no impact on odds of acceptance.
When I review a paper, I'm looking for relevance, impact, and correctness. I understand editors are looking for the same. Whether a paper is already on arXiv or not simply doesn't affect any of that stuff.
I suppose if a preprint attracted a good number of citations, this could be a positive signal about the paper's potential impact. But in practice I wouldn't seek out this information as a reviewer, so I likely wouldn't know about it.

There is no plausible mechanism by which a manuscript being posted on arXiv could affect that manuscript’s chance of getting accepted by a journal.
If you suspect otherwise, then you simply don’t understand how experienced researchers think about arXiv, and/or how much thought and care editors and reviewers put into doing their jobs in a professional manner.
This applies to disciplines where uploading preprints to arXiv is the norm. In other areas where public preprints are taboo or frowned upon, the answer could be different,

I can imagine ways how having a preprint on the arXiv slightly improves the chance.

@Arno I’d be happy to hear what they are. And, to be clear, I’m not referring to second order effects like the author getting useful feedback that helps them improve the paper prior to submitting it to a journal. My interpretation of the question is that it specifically asks us to ignore such effects.

A bit convoluted: If someone has already read the paper from the arXiv (and its good), they would be more willing to accept a referee request (as they already did part of the work). Thus, papers on the arXiv are slightly more likely to be refereed by authors from their core target audience, who will be more sympathetic and understand it better,

@Arno I see no reason why this effect would be statistically biased in favor of acceptance. It might mean the reviewers end up being marginally more qualified to review the paper. Even that conclusion sounds a bit too speculative for me to think it’s worth entertaining seriously. In any case the many known, non-speculative reasons why putting your papers on arXiv is a good idea will easily drown out this tiny source of (biased, or not) statistical noise.


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Advisor does not acknowledge their paper to be wrong, what to do?
This is a follow-up to my previous question: (Advisor's paper fundamentally flawed, what do I do?).
My advisor and another student collaborated on a paper. After reading it carefully myself, I've come to the conclusion that the approach, method, and analysis are all fundamentally flawed and the main result is plain wrong. A main result of the paper is a mathematical theorem. The paper was published in a peer-reviewed venue.
I've asked for clarification, which the authors (including my advisor) were not able to give. I've then pointed out the mistakes and errors in the approach and analysis, and gave counter examples that invalidate the main result. My advisor seem to agree with the errors during one of our meetings, but as far as I can tell no further actions were taken on the authors side. I then did not bring this up as I did not feel that was a good idea, since my advisor said I should "move forward instead of find mistakes in the past". However several months later my advisor is still endorsing the paper, and after I pointed out the errors again I received no reply.
So my questions are:

What should I do regarding this paper? Should I let this slide, or is there some higher authority I should report this?

What should I do moving forward with my Ph.D. studies? Does this event indicate the incompetency of my advisor? I know a suggestion might be switch advisors, but I've already tried working with several faculty members and the experiences are all none-the-better, and this has already taken a huge amount of time and I'm already several years into the program.

This seems to be a duplicate of your earlier question.

Is your advisor still insisting you build on this work?

@Buffy The earlier question focus on how to best communicate the errors, while this question includes new development of the event and focus on the fact that my advisor refuse to acknowledge the mistakes, and suggestions on moving forward with my Ph.D. studies.

No, there is no higher authority. The academic knowledge system is specifically designed to be dependent on the individual and the distributed community judgement of a piece of work, and not a single authority. If the work is flawed, the community will come to know this in time. If you want to accelerate this, write a paper setting out your objections and let the community decide. But don't do this while your advisor is still your advisor.

All academics will have published work in their past that has flaws in it, it is just in the nature of scholarship. In more empirical studies all work is wrong. Its not a case of if someone will find flaws, or contradict it, but a case of how long our work remains the best currently available approximation to the truth. Some people will recognise the flaws in their work. Many won't. Get used it it - its how academia is.

Unless your advisor is insisting that you build directly and inescapably on work you believe to be wrong (or won't let you explore the exceptions or counter examples), then just let it go.

I do think this is the sanest response to the issue. Yes, we'd all like various forms of perfection/ultimate-truth, but these seem unavailable in real life. :)

Yes, your advisor's attitude says something on their competence and honesty. Yes, there is a difference between works that are correct (at least technically) and works that are "plain wrong". And yes, everyone makes mistakes, but there is a difference between researchers who correct their mistakes, and people who always "move forward" without making reliable contributions to science.
Regarding the flawed paper, you should probably do nothing. There are so many wrong papers out there that it is a waste of time trying to correct them, except those that attract much attention and follow-ups. Most papers quickly fall into oblivion anyway.
Regarding your PhD studies, this is a tricky question. There are many options, depending on the particulars. Formally switching advisors may not be needed for distancing yourself from your advisor scientifically.