Widening the Search-ability of a Journal's Articles I manage a peer-reviewed and open-access publishing journal for academic research. At the moment, the articles are not viewable in google searches. If someone wants to access the articles, they must go to the journal website and download the article from there. This means that someone must know of the article and our journal to access the piece of research.

I am interested in making the articles that are in our journal appear in google search results and generally more accessible to a wider interested audience. What is a good way to do this?

I have looked into Google Scholar, but it seems you can only upload your own research articles (i.e., that it's only for individual researchers, and not for organisations like an open-access publishing company).

I would appreciate any advice on how to widen the visibility of a publishing company's research articles.

Google scholar

You can find the general indexing policy of Google scholar here: https://scholar.google.com/intl/en/scholar/publishers.html#policies

And the more technical information is available here: https://scholar.google.com/intl/en/scholar/inclusion.html

In case of link rot, the articles should be findable via search keywords such as "google scholar indexing".

The non-technical summary is that the abstract or the first page of the articles should be vievable for everyone. Further, I think the article should look like scientific articles, with titles, possibly abstracts, text, references, and so on. The exact parameters are almost certainly unknown. I know at least one journal published as a blog, and it is not indexed by Scholar, while some websites are.

General visibility

Publish good articles, get famous editors, perhaps appear in conferences or sponsor them, if relevant for your field. Avoid being a predatory publisher or looking like one.

Maybe also look into the basics of search engine optimization (not the arcane stuff about how to cheat Google, but the basics like having metadata and website headers right) and usability of websites.


Private Git repositories for students, that don't become public later Short version of my question: Is there a good way to provide students with free, private, Github-like git repositories, that won't become public later?

Background: In computer science, it is considered best practice to use Git (a version control repository) for software development.  Many universities want to encourage students to follow those best practices as part of their coursework, so they'd like to encourage students to do the same.  However, they don't want student work to be made public, as this creates a temptation for cheating.

Github in particular is popular, as it provides both Git repositories, an easy-to-use web front-end to Git, and a convenient workflow for collaborating using Git.  Github is free if you make your repository public; normally, you have to pay for a private repository.  Github has a special program for students: as long as you are a student, you can have private repositories for free, if you sign up for their student discount.  However, this only lasts as long as you are a student.  After two years, the student discount expires, and then the private repositories are locked; if the ex-student wants to retain access to their repositories, the ex-student has 30 days to either pay Github a monthly fee to keep it private, or they can tell Github to make it public and pay nothing.

One university I'm familiar with encourages CS students to sign up for a student Github account and put their projects and homeworks in private repositories.  However, empirically, Github's policies seem to encourage a certain number of students to make all their repos public after they graduate and their student status expires -- and then solutions are available on the Internet.  Because good software development projects are so labor-intensive to construct, many courses re-use projects for several years in a row.  Current students have reported finding this by search and are a bit worried that it'd be so easy for other students to cheat.  Therefore, recommending that students use a private Github account seems to create a two-year time bomb that will have unfortunate consequences for courses who plan to use their project for more than two years running.

Is there any good solution to this?  Is there a better alternative than Github that can be recommended to students?

In particular, a better alternative should meet the following requirements: allow students to have Git repositories for software development and collaboration with project partners; is free; is private; will remain private over time, without encouraging/requiring alumni to make their solutions public if they want to retain access to their solutions without paying; doesn't create extra work for instructors to constantly search Github to look for inadvertently-public solutions from past semesters.

I've seen How to deal with student putting their (home)work on github, but the solutions there aren't workable in this context: creating new projects every semester is not a good solution (it's been tried and leads to pedagogically inferior results).

Update January 2019: GitHub now has free private repositories.

Bitbucket offers unlimited private repositories. I use it for this purpose.

You can also host your students' repositories yourself on your own server with Gitlab (the community edition is free). This option has the advantage that you aren't asking your students to trust a third party with their data. I sometimes use this option, too. It's very easy to set up.

However, having students' work in repositories that don't automatically becomes public doesn't obviate the need to create new projects - students can still opt to post their work publicly. (This is true even if you don't use Git in the course at all.)

Personally, I typically use Bitbucket and ask students to keep their repositories private for the duration of the course (so as not to make cheating too easy), but they are free to make them public later. Part of the appeal of project-intensive courses to students is that they create something they can show off to potential employers. I want my students to have the option to make their work (which is often very impressive, and which they have put a great deal of effort into) public, so that they can enjoy this benefit.  I occasionally see students publish their repositories, put a link on their résumés or LinkedIn profiles, and then continue to improve their projects for months after the course is over, which is extremely gratifying.

I would consider it a disservice to students to prevent them from showing off their work after the course is over or after they graduate, even if I could prevent this. My university does not claim ownership of intellectual property produced by students in the context of uncompensated coursework (unless there is an explicit written agreement stating otherwise), so unless their projects also include material which I hold the copyright to, I couldn't stop them from publishing their work even if I wanted to.


Is it possible to count the citations that a paper has received in a particular country using Web of Science? I'm new in the use of bibliometrics. I was wondering if you can help me out? Consider this situation, an author "x" of the country "c" , publishes a paper "p" with a(n) international collaborator(s). If I want to know how many citations does the paper "p" has received from the country "c", is that possible? Is that so, three situations can happen.

One is that "only" author(s) of "c" cited "p", in which I will count 1. The second case is that there is a mix between author(s) of the country "c" and international authors, in which I will count a fraction of the authors belonging to "c" divided by the total authors of the paper that is citing "p". The third case is that only papers with international authors are citing "p", that I will count 0.

WoS allows you to look at all the papers citing a given paper P, and there is a link to "Analyze Results", where country is one of the options. (It defaults to a minimum count of 2; you'll want to drop this to 1)

For a randomly selected paper from a recent search, here's an example:

There are 11 citing papers; of these, seven have at least one US author, two at least one Czech author, etc. This would give a value of 0.64 if your original author was American, or 0.18 if they were Czech.

The obvious downside is that you need to do this for each paper P; you can't do it automatically for a hundred at once. But it's a start...

Edit: you can do this through Scopus as well. Select the paper, find citing papers, "analyse search results", and you get this:

Here, there are a total of three papers citing P, two of which have German author(s), one Austrian, etc.

With Scopus, you can do the analysis for a large group of papers, but it won't help you very much. From your initial search result, select all items using the checkbox, and click "view cited by". Then analyse search results again, and you get the stats for all papers citing one or more of the original search results. However, this won't help answer your question as to %age of papers with overseas citations - they're all bundled together and not segregated by cited paper.


Etiquette in applying for undergrad research I am currently looking into applying for funding as an undergraduate summer research assistant.  At the moment, two professors have agreed to allow me to work with them.  Since I can't be sure that the funding application would be accepted, I am considering accepting the offer from both professors and going forward with applying for funding with both professors - is this a good idea?  If so, should I let both professors know this?  If not, could I try asking the prof's permission to do this, or would it be in my best interest to just decide on my top choice now and just pursue that?

Thanks in advance!

You could do it with the permission of both professors, I think, though the funding agencies might disagree with that. But don't do it without at least their agreement. If the professors are at the same institution, perhaps you could work out something that they both participate in. There might be issues with that, of course.

But asking them both might also give you better information about which would be easier to work with. If one seems cooperative and the other not, it might be an indicator.

In general, asking is always a good thing to do.


State-of-the-art writing in machine learning According to Wikipedia, State-of-the-art is as follows

  State-of-the-art (sometimes cutting edge or leading edge) refers to
  the highest level of general development, as of a device, technique,
  or scientific field achieved at a particular time. However, in some
  contexts it can also refer to a level of development reached at any
  particular time as a result of the common methodologies employed at
  the time.

So there are two interpretations for state-of-art: one is general development across time and another one is the  best method available today.

Which interpretation is apt for state-of-the-art writing in machine learning?

For example consider a task Semantic Segmentation on PASCAL VOC 2012 test. There are 34 methods to perform that. Among them DeepLabv3+ (Xception-JFT)
has only the SOTA status. Remember that remaining 33 methods might also have SOTA status at their times.

If I need to write and present State-of-the-art on Semantic Segmentation on PASCAL VOC 2012 test, then is it enough to present DeepLabv3+  and ignore remaining (assume no dependencies) or there is a need to understand remaining also for state-of-the -art?

Context: My University generally follows the interpretation I for state-of-the-art, but popular machine learning website paperswithcode is following interpretation II. So I got confuse and hence asking which one is more apt for state-of-the-art writing. If interpretation II is the actual one,  then there may be possibility for me to convince my guide and act accordingly.

State of the art refers only to the very highest accuracy ever achieved up to the point that you write your paper in computer science (I work in the field).


File / Data / Script management as a PhD I started my PhD 7 months ago, and as I generate more and more data, and do more and more analysis, my folder structure is getting out of hand. I wanted to ask for best practices and opinions on how to organize my files in order to not lose track of everything and quickly find what I need. I am a geoscientist and have lots of analytical data as well as programming scripts. Along that I also have README.md for some analysis and snippets of ms word or plain text, if I wwrite something down to remember for a paper possibly.

I've made it a habit not to edit raw data at all and to backup regularly for obvious reasons.

Right now my simplified general structure looks a bit like this:

├── data
│   ├── analysis
│   │   ├── isotope_temperature_reconstruction
│   │   │   ├── report.ipynb
│   │   │   └── script523.py
│   │   └── light_micro_growth-line-analysis
│   │       ├── img1.svg
│   │       └── regression.py
│   └── raw
│       ├── isotopes
│       │   ├── run2019_02_19
│       │   └── run2019_02_24
│       ├── light_microscope
│       │   ├── sample_xy123123
│       │   └── sample_xy123124
│       └── sem
│           ├── sample_xy123123
│           └── sample_xy123124
└── documents
    └── paper1

I know the system my files are organized in doesn't really matter as long as it is consistent. However I am facing some struggles:

The data usually varies in "quality" and "ripeness". I have data that resulted from:

Some trivial test -> won't be used ever again
Is for calibration -> Doesn't belong to any project, but matters in many cases
Is directly and only needed for a certain publication

My problems with this are:

I find myself often linking and copypasting my data all over the place, because it is not where it's currently needed. As a consequence i also make edits only in certain places and not everywhere, and lose track of whats the most recent file. I also lose track of what files are handled programatically and where I edited something "per hand".
I have a lot of duplicate python/R/whatever scripts that I copypaste wherever needed. I think this is the easier part to resolve by modulating code and putting it into version controlled system wide libraries.
I sometimes have snippets of word or plain text that contain relevant research insights, but are scattered all over the place, because they are not directly related to a paper / data.

So I am looking for suggestions to address these problems, as well as suggestions for general file and data management, and general organization at a researchers main desktop machine.

The only problem that I feel adequately solved is my literature management because I just use zotero and let it organuize all my papers in a coherent folder structure. (It also makes it easy to search via tags, which would be super cool for data files)

In general I would distinguish between two approaches or a combination of both before ending in a very time consuming categorization of all your files

top-down
This means you use intelligent software to find again files you are looking for and don't worry too much about where it is stored. For example reference manager (Mendeley, Zotero,...), a Desktop search engine (Copernic). In the desktop search engine or with windows search (indexing turned on) you should see which file was changed at the latest. Most of your ideas and sketches you save in Onenote or something else that can link to files and www links.

bottom-up
This means you come up your self with a distinct structure like you did with a rough categorization (raw data, devices, projects). But don't complexify this, when most of the files can be identified by the file type/ending, then it may be more convenient to order it by projects and keep all file types within such subfolders.

Additionally, one trick I use is tagging files in their filename like "#phdthesis" or "#interesting" or "#cite" or "#collaboration".
Sample files (data, images of samples) always get a date ProjectnameDayMonthYear independent of their file type.
Don't make your system too complex or too time consuming. For instance most of PDFs I read and download end in one folder. No point in categorizing them, this will not work/help over years and decades. Defining content-relative filenames takes too much time, most of them I find again over my desktop search engine months or years later if they were memorizable with keywords and search operators or self-created #tags.
For files which the PI or teammembers have to have the possibility to retrace them you anyway have to arrange a common plan how to structure and save the files everyone understands and can contribute. I would either suggest cloud storage or a local wiki here (moinmoinwiki for instance).
The most productive system is probably the one "invented" by Stephen Wolfram, but it took probably even more time to set it up than writing his article. But you get a lot of ideas, so I'm not sure it is future-proof to organize yourself with a propertiary software.
A personal opensource free wiki like moinmoinwiki or tiddlywiki is also an alternative and combination of bottom-up top-down and file system. So my experience is a wiki is only worth the additional time and effort at least with 2 or more team members, otherwise your personal choice and mixture of bottom-up and top-down is more time-efficient and humanities/experimental research/programming single reaserchers will end up with very different management system due to available time, number of files, work-flow and necessity to document and retrace everything.
File systems and desktop search engines will never die out, so my general tip is not to rely too much on fancy software like onenote, mathematica or alternatives to have a future-proof system.


Supervisor wants me to withdraw from program I have had continuing problems with my supervisor in that

I used data from a publication but didn't cite it properly (this was an honest mistake and during discussions, I plainly said that I received the data from elsewhere) leading him to accuse me of academic dishonesty.
I had some publications in journals not of a good standard and he started accusing me of lying and having fake publications.
I did a lab presentation for which I was not prepared enough and he called me lazy and incompetent.
I got delayed in providing him with some research material and he plainly stated that he does not want to supervise me anymore.

I am planning to talk to the chair of the dept about my issues but are these sufficient grounds for the chair to recommend that I be withdrawn from the department?

I used data from a publication but didn't cite it properly

It is hard to say from that description, but yes, that can qualify as academic dishonesty/misconduct and be grounds for removal from a program. That said, except in the most blatant and worst cases, programs, and universities, generally try and provide some other sort of punishment.

  some publications in journals not of a good standard and he started accusing me of lying

I cannot see how publishing your work would be grounds for dismissal under any circumstances. Lying obviously can be related to academic misconduct and be grounds for dismissal.

  got delayed in providing him with some research material and he plainly stated that he does not want to supervise me anymore.

Not meeting deadlines can be grounds for dismissal, but generally there is a procedure that most be followed. The fact that he does not want to supervise you anymore is probably the most problematic issue. Your program may require you to have a supervisor, if so, you will need to find a new supervisor.

It sounds like things are going poorly and a talk with the department chair (or head of graduate studies) is appropriate. If this is the first time you are talking to the department chair, then I highly doubt the conclusion of that meeting would be you being kicked out. The meeting might start the process of you being dismissed, but more likely, it will start the process of trying to improve your situation and resolve the issues.


How to deal with political (literal) situations in the workplace? A few days ago, I went to have lunch with my colleagues (working in the same group). Somehow, the conversation turned towards politics and the "immigrant emergency" that Europe is currently facing.

To put it mildly, I as a person have very strong convictions regarding such issues. I am from India and I have to deal with passive racial profiling on a regular basis (People looking me up and down and then holding their bags a bit more firmly; No, It was not my appearance, I was very well dressed/groomed). After having experienced it the first few times, I understand the biases that affect such behaviour and do not really mind it.

Nonetheless, it is very difficult for me to ignore it when my peers portray this issue from a one-sided perspective. At that moment, I let the matter be because a short argument over lunch is not going to change a people's minds.

Yet, at this moment I feel very angry at myself for not having spoken up.

For future reference, how should I go about addressing such sensitive issues without raising a furore?
In other words, how can I present history/societal and political issues from the other side of the fence without creating a fuss? Is that even possible?

How should I go about addressing such sensitive issues without raising a furor?

Either keep silence or avoid going to such places if you can't withstand such talks.

  how can I present history/societal and political issues from the other side of the fence without creating a fuss?

You can't. Reality is different from place to place and human minds are built according to realities they live in.

Its futile to talk about the benefit of democracy with a person from mainland China; futile to try to explain why invasion of Ukraine was a bad idea to a Russian; futile to try to convince a neo-Nazi to not to stab a Turkish guy.

  Is that even possible?

No. This is about ideology. Ideologies can't be argued with. They are deeply rooted into human souls.

Someone who passed their entire life living under the roof of democracy in Hong Kong can not be convinced to cede their right of freedom of speech only because their country is systematically taken over by a communist country. That is why we saw Umbrella Movement.


Do you have to accept a postdoctoral position if the university has paid for accommodation and international flights for you to come and present? I have been invited to give a seminar related to applying for a postdoctoral position. The professor has been very kind and seems  like a very nice person. He also helped me look for a postdoctoral position for my girlfriend. Now I have received the tickets to travel to the university with first class accommodation and luxury amenities. The trip involves  international travel and also that I have been talking with other professors to see my best options.

Does this force me to accept the position or is it common that researchers give these nice invitations?
Do I need to mention  to the professor that I am exploring other options?

If you are getting excellent treatment, that likely means they are fairly keen to hire you.  They are working to recruit you.  Accepting nice accommodations and amenities from them during the hiring process places no obligation on you--none at all.  That being said, this sounds like it might be a really good place for you.  Use your judgement about what will be optimal for yourself.


Is it advisable to apply to more than one PhD program? Is it good to apply for more than one PhD program and accept ( the best case, obviously ) the most interesting/best paid/best outlooks one?

Yes it is common to send multiple PhD applications to multiple schools. I am doing this now, I would RECOMMEND it actually because getting into PhD programs is difficult.


Is it odd to contact past graduate student? I am interested in pursuing a particular program and I find the name of some of the past students from professor's website.
Is it odd to write an email to these past graduate students and ask about the job and their future career?
could you please tell me what should I write to be natural?
I am particularly worried about finding the job and future career.

In regards to your question what you should write I have but a few hints:

Students may be dependent for a very long time on their former advisor. Therefore, they may not want to badmouth their advisor to a stranger and answer some questions untruthfully (or ignore your request). So you should (if you want to get honest answers) formulate questions in a way such that no answer is negative. I. e. if it's very important to you that your advisor helps you a lot, you should not ask "Does the advisor helps a lot?" but rather sth. like "Is the advisor more hands-on or hands-off"? Also, of course ask as detailed as possible. The same things go for the "future career".

Since I would consider it rather impolite to start an email with many questions, you should ask by writing "Is it okay to ask you a few questions about your advisor and your future career"? Maybe you should also clarify what you mean by "future career".

If this is at all possible, you may ask to meet the students in person (of course in the way which is most comfortable to them). In a personal meeting, people are more likely to tell you true negative things (if they got a good impression of you) since their is no written trail.


Applied a new technique on a facial recognition program and the new results are better than the previous one. Can I write a paper on this? I was playing around with this source code which yielded say results X on using a specific data-set. Now, I came up with an idea to add a change in the source code (specifically, in the data-set) which on execution gives better results (results Y).

The results in X and Y are the facial recognition confidence.

So, the confidence is much better in the Y result when compared to the X results after the new technique is implemented.

Is it possible to publish a paper?

Where the aim of the paper would be to state that this technique gives a better confidence value for the provided data-set.

Any help would be recommended!

This is my first post. Thank you.

In general, yes, you can publish a paper. However, since you are basing your work on that of another you need to properly cite the earlier work. Check any copyright restrictions on the computer codes you use, also. It is possible that you will have to get permission if you use part of that code. But it is also possible that the authors already publish a license to use and extend.

The only other issue is to find a journal or conference that will accept the paper.

I would suggest that part of your paper discuss the earlier work in some detail and the results that it provides. All properly cited. Then you can discuss your new approach and how it improves on the original.

It would also be good to explore alternate data sets to give yourself assurance that your result isn't too narrow or tailored to the specific data set of the original paper. You can even do a comparison on a range of data to get true confidence in the value of your work.

I also think that the "new" approach would be more valuable if it is different conceptually than the earlier work, not just a more carefully coded, but essentially the same, algorithm. How is it new? How is it better?


Can work experience overcome bad undergrad grades for admissions to masters programs in Germany? I did my graduation in Electronics and Communication engineering, and now I am working as a software engineer for more than two years.

I have this problem that during my graduation I failed in a few subjects like analog electronics and organization behaviour. (Yeah!! It sucks that I kinda failed in Analog and Organization at the time, but now as I have experience working, I feel that they are very interesting and knowing there practical applications)

I cleared them in the following year, and passed my graduation all clear in the 4 year period.

I have three questions

Will I get into a high ranking German university?
Will the work experience count?
What else can I do to improve my profile.

The answer to all your questions depends on the university. There are only some rough standards which needs to be implemented by the universities.

If you consider computer science at my university the state dictated that one has to have a good bachelor to enroll in the master courses. Now there are two possibilities: Either you have a grade better than 2.5 (which is a B- in the European grading system and considered barely good) or you have to give reasons why your bachelor is weaker and then a committee has to decide whether you are allowed to enroll. But I know that other universities and even other departments at my university have other rules.


Maximum allowed time for PhD (Doktor) in Germany I am a physics PhD student in Germany. During my PhD I got two children, and as a mother, I had to give major part of my time to my children. I started in April 2012, and I will finish in spring 2018. Is this too long time to get a postdoc position afterwards?

The typical times for a PhD in Germany vary mostly between three and six years, depending on the specific field you're in.

Legally, the university is allowed to give you fixed-term contracts for a total maximum of six years while you're working towards your PhD. However, there are extensions of this limit for childcare, so you would be well below this limit.

For a postdoc position, I don't think the time taken for your PhD would be a major factor in evaluating your application.


Does writing code for an assignment after seeing similar code online count as plagiarism? In my compilers class assignment, we were asked to write some MIPS code. One of the problem involved implementing fact() function as a sub-problem. I wanted to implement the standard recursive version

int fact ( int n )
{
     if ( n == 0 || n == 1 )    return 1;
     return n * fact(n-1);
}

As I am new to MIPS, I looked up here on how to implement recursive routines. Unfortunately, the link explained recursion using fact() function itself. As I didn't want to "copy" code, I just understood the concept of recursion and wrote the fact myself.

But my fact code seems very similar to the one I looked up to learn recursion in MIPS. Is it for the fact that I glanced at the code already or the fact that factorial is really a very simple function with hardly 10 lines in it? Am I guilty of plagiarism here?

Here is my code

fact:   addi $sp, $sp, -8       # decrement SP to make room for pushing input var and ret addr
        sw $ra, 4($sp)          # save $ra
        sw $a0, 0($sp)          # save input on stack

        li   $v0, 1             # Set v0 to 1 initially.
        beq  $a0, 0, fact_ret   # if ( n == 0 )    return 1;
        beq  $a0, 1, fact_ret   # if (n == 1) return 1;

        addi $a0, $a0, -1
        jal fact                # Recursive call fact(n-1)
        lw  $a0, 0($sp)
        mult $v0, $a0           # n * fact(n-1)
        mflo $v0                # Save answer in v0
fact_ret:
        lw $ra, 4($sp)          # restore $ra
        addi $sp, $sp, 8        # restore $sp
        jr $ra                  # return from function

I think this is very subjective question and will depend on who the judge is. I would suggest you communicate exactly what you wrote in the question to your professor and let him be the judge. If he thinks yes, he might assign you some other relevant exercise to evaluate your learning.

By actually being honest about your situation, you will likely be treated in a positive light.


Lecturer in Math position application - UK - Teaching statement I am currently applying for a lecturer position in mathematics, in the UK. I just have a general question regarding how the applications usually compare to US applications. In the US, most of these jobs require a very precise list of documents: recommendation letters, CV, research statement, teaching statement, and maybe some other stuff. Usually it's very clear.

In the UK, most of the applications I found require an application form + supporting material. In many of them, it's not so clear what this supporting material should be. My plan was to include at least my CV, publication list, and research statement (similar to the one I would send to a US application). But what about the teaching statement? I don't want to make my application extra large by attaching unnecessary documents which could end up being detrimental. Specially a teaching statement, the idea of which I never bonded with.

I'm willing to write one and submit it as well, but I wanted to know from UK people (specially those that have been in hiring committees) about this.

Having applied for jobs in both North America and the UK, I can confirm that unless the advert and "further particulars" specifically mention it, there is no need for a teaching statement.

I thought I would add some further comments, which aren't exactly relevant to your question but which came to mind since you mentioned UK vs NA.

For a standard "lectureship in pure mathematics" (presumably entry level?), I was told by a 3rd party, when I applied for my current job, that in many UK places a list of courses in the CV, plus remarks of the form "my teaching was rated in the kth decile by student questionnaires," would be sufficient.

The important thing is an up-to-date CV, which should emphasise the extent of previous teaching experience. Success in getting grants, either as a graduate student or postdoc, is probably also worth including. Other information such as conference participation and refereeing work is rather secondary; you can include it, but I don't think it would make much of a difference.

Due to the sheer volume of applications, it may be worth including things like the publication list at the end of the CV rather than in a separate document. You might also wish to highlight your four best papers in an early "Selected publications" section; sadly the spectre of REF-fability is always on the minds of committees. The CV is often what is circulated when drawing up a longlist. The research statement should probably remain separate, and is roughly speaking the same kind of thing that one would prepare for a North American application.


Is it possible to ask 2 professors to write a joint-letter of recommendation? I have been working with 2 faculty members on the same project. I took a class from each of them, and the three of us meet in person on a weekly basis. I think it's reasonable to assume that they've seen the same level of research ability from me.

I am planning on applying to graduate school, so I was wondering if it's appropriate to ask them for a joint letter? My motivation behind this is

the two of them mentor me on the same project, so 2 separate letters may have unnecessary overlap?
applications typically require 3 letters (I already have 2). For schools which you can submit > 3 letters, I would think they still value quality > quantity
may be slightly less work for both of them (?)

I don't want to come off rude by asking the two of them to co-write a letter of recommendation for me. Is it generally deemed appropriate to ask two faculty members to do this? I think this is quite uncommon because on applications I only get to designate one writer per letter of recommendation (i.e. provide just one name, his/her title, email, phone, etc). If so, how should I phrase the question of asking both of them to co-write a strong letter of rec for me?

I have received applications that have had such a letter in them (well, at least one).  It came from a lab director and the applicant's immediatiate postdoc supervisor in that lab.  I thought the letter conveyed the student's experience in that lab very well, provided a nice bottom-to-top view, and it was more clear than if it were two letters, as I didn't need to put the connection between two letters together in my own head.

The letter did not raise any eyebrows, and it seemed entirely appropriate to me.

It's probably not the right thing to do more often than it is the right thing to do, but when it's right, it's right.

To directly answer the "how do I ask" question, something along the lines of "given the limit on the number of recommenders allowed, it occurs to me that there may be certain advantages to getting a joint letter from you and Dr. X, especially because ... [reason goes here].  Do you think this is an OK approach, and are you amenable?"


Publishing erratum to arXiv and other best practices Is publishing a single page erratum to arXiv an acceptable practice? And does it violate the copyright of journal who published the original work?

Has the original paper been posted on the arXiv?

If so, I suggest updating it with a corrected version, and communicating clearly in the Comments field that this new version is a corrected one. (Also, I'd change the Journal-Ref to indicate that it doesn't exactly correspond to the publication.)

In terms of copyright, this may be in a grey zone in case you've signed away the rights to your preprint to the publisher. But if so, it is a grey zone academics have been comfortably treading for years.


Emailing a professor about a potential research idea, is there a risk? I am an undergrad who worked at a computer vision related lab. The lab I used to work at raised some red flags by saying that even if I contributed, my name could not be on the paper. I also transferred schools, so I left. The problem is, I have this potentially great research idea that I'd like to test. I still have the data (a one hour video) and was either a. going to ask if I could use it for solo research, of course crediting them b. try to find a new professor at my school to supervise me.
I decided I want to find another professor to supervise me, cause I have never written a paper before and this is kind of a big project. I have been reading papers and research this for 5 months now, and I have never seen my idea done before. It basically takes something from a different area of the field and applies it to the research area I am interested in. I have seen it tried before, but not in the exact way I plan on doing it.
My concern is, what if I email professors about this and they steal me idea? Sure, if your ethical you won't, but could that happen? I want to email this professor with my idea, and ask if has any data / ways I can explore this at their lab. What if he says no and runs with my idea? either way, I am hoping he can offer me some perspective, but even if he says no he can be wrong - and isn't that the point of research to explore things that may not work?
Another reason I want to work with him is because all though there is another professor who would be able to help, he publishes a lot in IEEE and Civil engineering journals. I am trying to get noticed by the AI/ML and deep learning community, and that is where this other professor mostly publishes in. Would it be bad to ask him if he knows of any professors I can work with, if my idea doesn't suit his lab?

Unless by mischance you are contacting people who are not actually respectable (on the world stage), the sorts of issues that worry you are non-issues.
The more genuine issue, assuming the above, is that more-expert people will not immediately have the same enthusiasm for your ideas as you do. For many possible reasons, including that they and their group have already thought about that, maybe many times, and/or they are aware of other peoples' thinking in such terms decades earlier, etc.
So don't be offended, and don't be suspicious, if/when people do not hail your ideas as revolutionary, etc.
In real life (in academe, in my 40+ year experience), although, yes, sometimes unscrupulous advisors and others do indeed steal their advisees' ideas/work, ... this is (mercifully) quite rare. In particular, again, unless you are unwittingly involved with nasty losers, this worry should by far not be your first consideration. Indeed, thinking in such terms would corrupt your thinking in many ways.
And, in any case, as Michelle Obama recently said, "when they go low, you go high".
Obviously morally ideal, ... and, yes, not always easily feasible in reality... but thinking in those terms is a much better base point than thinking in terms of endless dishonesty.


Are there downsides to speculative applications for academic jobs? Speculative applications, i.e. application without a job announcement being published, are common (well, at least normal) in non-academic jobs. But I am not sure the situation is the same in academia. Somebody has suggested me to send speculative applications to different departments for teaching or research jobs. I was thus considering the pros and cons of this type of applications.

The pros are almost evident (more exposure). However, I worry about potential downsides. In particular, how would potential employers look at such an application? Could it make me look bad? Is there any other downside I haven't thought of?

Here is my standard advice to PhD students applying for academic jobs:

First, look for departments that are advertising for faculty in your subfield.  Apply there.
Second, look for departments that are advertising for faculty, but not in your subfield.  Apply there anyway.  There is no way to tell from the advertisement whether the listed fields are requirements, preferences, or mere examples, or if they just recycled last year's ad without reading it first.  (Yes, I have seen all these alternatives.)
Third, look for interesting departments that are not advertising for faculty.  Apply there anyway.  There is no way to tell from the lack of advertisement whether they are really not hiring, or they just aren't advertising widely, or they just haven't posted their ad yet, or they thought they posted the ad but didn't.  (Yes, I have seen all these alternatives.)

Before anyone objects: Obviously, I'm not talking about your department.  Everyone  knows that your department's advertisements are precise, timely, and highly visible.  I mean other departments.

Of course, if you're thinking of applying to any department, whether they're advertising in you subfield or not, it's a good idea to contact someone you know in that department to find out what they're really looking for.  If your contact says "No, really, we aren't hiring X," you can save yourself the trouble.  But if you (or your advisor) don't know anyone well enough to ask?  Fire away.


how to bring into full play what was prepared during faculty interviews A faculty interview is short, whether it be a skype one or an onsite one. Esp for the former, as interviewers have tight and non-negotiable time limits, it's so short that there's little space beyond answering the interviewers' direct questions. In a short interview, as one invariably improvises, no matter how well they were prepared, it seems. Many rehearsed lines (not necessarily the exact wording, but topics planned to highlight) are forgotten. How to bring into full play what was prepared?

Don't overthink it.

In a skype interview, you're right, it is mostly their questions. Answer them directly, and maybe keep 2 points in mind that you really want to make when they give you a chance to lead the conversation for a few minutes.

For on-site interviews, it's a long day or two, and you'll have plenty of opportunities to say the things you want to say.

I suggest you trust that the important things will come to light during the interview. If you forget one or two things you wanted to say, that omission is very unlikely to determine the success or failure of your interview. The overall picture that the department gets of you is much more important -- is your research strong? does it fit well with the department? will you be a good teacher? a good colleague? I suspect that the "rehearsed lines" will be less important, in the scheme of things.


What to do when you find someone else is working on the same masters research You've been hard at work for lets say a year on your masters research and you then discover that someone else has been doing the same research as you have. (Let’s assume it’s a coincidence that the same research is done). What do you do in that case? Should you hurry and and get to the “winning line” ASAP? Should you or the other person change their research proposal?

Masters projects generally do not aim to produce top-quality original research, rather they give masters students an introduction in the art of doing research. So the fact that two people at two different institutes are doing more-or-less the same thing does not matter. It would only become a problem if

One student plagiarized the work of the other.
The two students collude, reducing their workload to produce one thesis that will be submitted twice.
Both students tried to publish their work – whoever gets in first will receive the credit and the other will possibly not get published.

Even in the last case, it is not unheard of that parallel submissions of the same results by different parties occurs. Sometimes it is worth publishing both, especially if they approach the problem differently. I have heard of one case where the editors asked the two parties to produce a single combined paper.


No reply from the professor after the follow up email There is a PhD position at a university. I have sent an email and also a follow-up email (after one week from my first email) to the corresponding professor and I haven't got any reply yet (it has been 4 days from the follow up email!).

somewhere at the personal webpage of the professor it is stated that to apply or if you are interested to postdoc please first email your CV to Prof. X. On the other hand, the "Apply online" button in the open position list is active. What should I do now? send another email to the professor?

My answer will be general -- not specific to the particular institution you want to apply to.

You could contact the department and ask, "I sent my CV to Prof. X, as suggested at the application instructions page (provide link), on [date], but have not heard back yet.  May I go ahead and submit my application, or do I need to wait for a response from the professor?"
Note that four days is not very long.  Depending on the application deadline, you may want to give this a bit more patience.
You have submitted your CV as instructed; unless the instructions say you must hear back from the professor before submitting your application, I suppose you could go ahead and submit your application.


Will a professor get annoyed with frequent requests for recommendation letters? Just last month I asked three professors to write me recommendation letters for my graduate school application. They all agreed. Then today I found an internship that also requires recommendation letters.

I am interested in applying to the internship, but I worry whether I would be asking for letters from my professors too frequently, especially since they might need to rewrite the letters to accommodate the nature of an internship.

A related post here, although in that case the two requests are one year apart and the letters are for the same purpose.

It is fine; don't worry about it.

This is a very common situation: many graduates will apply to more than one program that needs recommendation letters.  They almost certainly are going to be asking the same few people for multiple letters, because they are unlikely to have a large number of contacts to draw on to ask for recommendations.

I think the question you have linked very much applies to this case.  Particularly the top answer, which points out that this is part of professors' jobs, not some kind of exceptional favor you are asking for.


Certificate in data mining I am interested about getting a certificate in data mining. I found three so far, and these are the following:

MIT - Data and Models in Engineering, Science, and Business
Stanford - Data Mining and Applications Graduate Certificate
UCSD - Data Mining Certificate

Has anyone taken any of these courses, and are they worth it? Would I benefit in terms of career opportunities with one of such certificates?  I already have a background in data mining, however nothing is on paper, so I thought it might be good idea to get a certificate.

As with any certificate course, it really depends on what you intend on getting out of the program. All of those are well-respected universities, and the coursework will almost certainly be extremely informative. In that regard, you'll learn a lot. On the other hand, there exists a frankly ridiculous amount of high-quality, freely available information online related to data mining from many universities, including some of those you listed above, so you can definitely learn all that without paying a not-insignificant sum for the experience.

Regarding job prospects, it really depends on where you're looking to be hired. This answer from Workplace.SE is an excellent overview of how useful a certificate can be in helping you get hired, and this question from Programmers.SE has many useful answers discussing how certificates like the ones you mention are viewed in industry. Long story short, they're usually not that useful for jobs unless they're industry standards, which the ones you list are not.


Non-English language papers submitted to REF for evaluation? So this is a little U.K. specific - I'm just curious whether any of you have seen or heard about such submissions. Now I'm completely aware that in many disciplines this seems unlikely, but how about in the fields of Arts & Humanities? What was the value of such submissions, if any?

Non English language outputs are addressed in section 128 of the REF Documentation. Excluding Welsh, for which there was a special system, basically, the output needed to be accompanied by an English language abstract. The abstract is only used to identify an expert capable of evaluating the work and not in the evaluation itself.


How to cite the supplemental material from the main text? In order to meet the page limits of a journal, I am placing the appendices in a "supplemental material" document for the purposes of the initial submission.

I'm wondering how I cite the supplemental material from the main text (I need to do so because I am referring the reader to some equations and pseudocode).

For example, the main paper's title is:

  A Really Lengthly Paper

The supplemental material's title is:

  Supplemental Material: A Really Lengthly Paper

What should the reference look like? Furthermore, how should I refer to the material ("As seen in Eq. (S1) in the supplemental material [X]...")?

There are many different ways how to cite supplementary data/supporting information - whatever you'd like to call it. In general, your title for the supplementary data is perfectly valid. Within the supplementary data, tables and figures including pseudocode are typically numbered in a similar way as in the main text with the exception that they are labeled with the prefix "S" for supplementary/supporting.

Say you have figures (Figure S1, S2, ...), table (Table S1, S2...) and some equations in the supplementary data, there are several possibilities to cite them:

If you want to refer to the supplementary data, you might just do so, i.e.: For detailed information, see the supplementary data/supporting information.
If you want to elaborate on an aspect with further data in figures and tables, you refer to them similarly to main figures and tables, i.e.: see Figure S1, or cf. Table S1
In the case of pseudocode, the best way probably is to format them as figures and label them as such including the appropriate references (see above).
In the case of equations you might refer to them as follows: for detailed calculations please refer to the equations in the supplementary information

Another approach how to enumerate data in general in the supporting information is the prefix "S" followed by a running number, i.e. S1, S2 and so on. This way you can give each part regardless of figure, table, pseudocode or block of equations a title with section index.

If you want to refer to a section in the supplementary data, you might cite them as follows: see supporting information S1, or for detailed calculations refer to supporting information S2.

EDIT:
As suggested by jakebeal, journals also offer guidelines for authors including formatting of text, and labelling of graphics and tables. If there are not explicit guidelines available previous publications in the same journal are a good indication as well.


Citing draft papers found on academia.edu I have noticed an article published in a peer-reviewed journal in which the author cites a draft paper posted by another person to academia.edu. The former gives the whole bibliographic information of the aforesaid draft (including the URL) at the exact place where it is cited, but does not mention that draft at all in the bibliography, even though she does give all other sources she has cited in the bibliography.

Does it mean that a draft paper can be cited but should not be included in the bibliography? If it does mean that, is this because it is not yet peer-reviewed? I am rather curious here.

(For those who need to know, the field is religious studies.)

In my experience, absolutely anything can be cited, but not everything should be cited. Papers uploaded to Academia can often be what's called post-print, i.e. they are the version that has been peer-reviewed, accepted by a journal but not copy-edited by the journal [this is the point where the article still belongs to the author, after copy-editing it is the property of the publisher]. In this case it would still technically be a draft, but quite a long way down the line.

Of course the paper can be cited, as long as there is enough evidence that the research is of good quality [if it's been accepted by a journal then it generally would be]. Things that should be cited are works like academic books, journal articles; whereas things like Wikipedia should not. Then there are grey areas such as drafts and online articles: basically if you know the researcher and field, and you trust the quality of the research, I see no reason not to cite it and include it in the bibliography.


Use of Acronyms in the thesis I don't want to use acronyms in my thesis. but i have table which i am showing some data. I have to put acronyms in the table to make it inside the width. So i am using acronyms only in the table area. Can i do it in the table if i want and not at any other place.
for example Let say

I am measuring speed(S) test(T) for instance .

and then in the table can i have  S , T ?

Note speed and test are not first occurrences. I only want to use acronyms in the table and not any other part of the thesis. Is is ok to do that in thesis ?

It happens quite often that you need abbreviations only within a figure. In this case, you will usually just note the abbreviations in the figure caption.

So you could caption your table something like "Table 4: Some data showing the influence of speed (S) on test (T)."


Presentation: Is using cartoon slides un-professional or fun? I am close to graduating and am going to an assessment center for a very large tech company. One thing we need to do is hold a presentation about one of their products.

I want to stand out a bit from the crowd and show that I spent a lot of time on this presentation. So I had the idea of drawing my own characters and using them in slides to help explain my reasoning etc. (A lot like in the youtube-videos you see nowadays where stuff gets drawn while a person talks).

I find this type of presentation fun to listen to, but is it unprofessional? It is my first time at a global giant like this and I'm sure they are fine with more than others since it's in tech, but is this too much? Should I use the normal "boring" slides with one idea/slide etc. ?

In general, the person talking to your slides should be you, not a cartoon character.

Now, I've seen things like this work for people who are very good presenters and stage performers as well. For example, one of my grad school compatriots was also a serious performing storyteller, and he understood the performance aspect well enough to do all sorts of fun, risky, and showy things in his talks.

If something like this isn't already you, however, then I would advise not trying it for the first time in a potentially high stakes presentation like this. Conservative may be relatively boring, but it's also safer, and it won't be boring, if your material is good.


How much professional assistance can I receive on an undergraduate capstone design project without cheating? I'm taking the undergraduate capstone design course in electrical engineering at a university in the U.S. and I've been receiving some programming help from a friend who is not, nor ever has been, a student at the school. I understand that a certain amount of professional assistance is acceptable, however, there was a significant programming snag that I encountered that I would not have been able to solve on my own without this person's help. I have not asked my professor directly about this yet (there's still time, though!) since I've been afraid of self-incriminating and that I may be asked to remove the code which would put me back to my major snag that I can't solve. At this late point in the course, this solution is essential as removing it would likely force our group to alter direction/scope. This is a design project and not a programming project (I'm currently using plenty of acceptable open-source code from GitHub) and I feel my group has legitimately created original design work. Obviously, I have no problems at all citing any sources I used for the project as my goal is to avoid cheating.

My question is this:

Can I use code that was created specifically for my capstone design project by a knowledgeable person (with my assistance) without cheating if I cite the source? Would it make it more acceptable if this person posted this same code to GitHub as well since other GitHub resources have already been deemed acceptable?

I have not asked my professor directly about this yet (there's still time, though!) since I've been afraid of self-incriminating and that I may be asked to remove the code which would put me back to my major snag that I can't solve.

There is not a lot of guidance that we can give you on this question as outsiders.  Your professor is the one who has set the assignment, and he/she is the proper person to determine what level of assistance is allowed while meeting the learning/assessment goals of the assignment.  In cases like these, where you have doubt over the allowable scope for assistance, you need to speak to your professor for guidance.  Since you have already received assistance, this conversation will involve disclosure of previous assistance, so you should be open to the possibility that you may have to discard some of that work.

The other issue here is the importance of learning how things work.  If you have been provided with code by an outside professional that solves some problem in your assignment, then you need to take the time to understand how and why that code solves the problem.  You say that if you are asked to remove the code then that will put you back to a point where you can't solve the problem.  This suggests to me that you don't actually understand what that code is doing, and so it is not appropriate for you to use it in your assignment.  The best approach here would be to take the time to learn the reasoning behind the code that was used, and why it works to solve your problem.  Once you understand this, it should not be a major problem if you had to remove that code and write your own replacement code in a different form.


How to quote bulleted lists using IEEE style? I found two very useful bulleted lists in my sources and I want to quote them directly in my thesis. For example:

  Sentence 1
  Sentence 2
  Sentence 3
  Sentence 4

Nevertheless I only could find how to do it using APA and MLA. How can I do this using IEEE style?

EDIT: I was following the approach proposed by the accepted answer, but I found two awkward consequences while doing this. I would appreciate if someone can confirm if this approach is okay. I explain the problem with an example.

Consider this list in the original source:

sold, leased, or licensed to the general public
offered by a vendor trying to profit from it
supported and evolved by the vendor, who retains the intellectual property rights
available in multiple, identical copies
used without modification of the internals

Lists are automatically indented. Quoting this list directly using the IEEE guidelines will increase the indentation of the list:

  sold, leased, or licensed to the general public
  offered by a vendor trying to profit from it
  supported and evolved by the vendor, who retains the intellectual property rights
  available in multiple, identical copies
  used without modification of the internals [1, Sec. 1.1]

Furthermore we have to add the in-text citation at the end of the long quotation, but because it is added at the last item in the list it might confuse the reader regarding what is actually quoted: the complete list or the last item. Is this okay?

Put it in a block quote and cite it like you would any other quote. The fact that it's a bulleted list doesn't necessarily  make it special.


Should references in the supplementary information be included in the main text? I have been cutting some sections out of my article and moving them into the supplementary information section so my paper will fit within the journal's length requirements.  However, some of the information (particularly the methods section) has citations.

Should these citations only be referenced in the supplementary information section or in the main part of the article as well?  And how would the numbering work for that?

Citations that do not appear in the main article should not appear in the bibliography section of the main article. Instead, you should create a separate references list in the supporting information, and use a separate numbering scheme. Usually you can use the same numbering scheme as in the main article; it will be clear that references apply to the supporting information, rather than the main article. (You could add a footnote to that effect if you want to make this clear, since supporting information is usually handled "as is" by the publisher.)


Time taken by department to offer the admission decision How much time does it take for getting the admission decision after all the required documents are submitted at a university that offers admissions on Rolling Basis? I had my application and all required douments submitted before 10 days for Fall 2015. Also, my appliacation has been forwarded to the department before a week. How much time should it take for the department to review my application?

Thank you.

The waiting time for a decision depends on the admission process. The admission process itself can vary broadly depending on type and size of the institution.

I can point out two different examples from the German higher education system. I graduated at a public state university of applied sciences where I was member of several committees. Now I work at a private state-recognized higher education institution. The admission processes and concerns, may also apply for US universities.

For public state universities dealing with 10.000+ applications, all of them have to be checked for formal correctness (documents complete and valid etc.). After checking a local numerus clausus have to be calculated to find the limiting grade needed for admission. Especially in Germany some laws and regulations enforce to fulfill target percentages of e.g. women or handicapped persons. These tasks performed by a handful of staff members can last more than a month. Sometimes German universities publish target dates of submitting the admission mail in the same way they publish application dead lines.
For private universities, business-, management- or law-schools the application process often is more selective. Admission committees decide not only on base of grades and formal criteria. Some require letters of recommendation, motivation letters, CVs pointing out working experience or social engagement. All these documents must be read and for everyone the committees have to give a recommendation. Depending on the number of staff members concerned with this, the period until one receives the final decision can last weeks up to months.


master thesis structure My question is about master thesis structure according to MIT Thesis Format.

I am working on a computer system that comprises of several components. The focus of the research is how to implement the components of the system. Each component can be researched separately. I've implemented all the components and made a progress in improving the performance of some components.

For each of the component I dedicate a section. The question is about an introduction and a conclusion sections. What is the best way to organize them. Should I put a single introduction (about all the components) just after Abstract or separate this big introduction by components and put them in corresponding sections.

The same problem with conclusion.

Sorry for the naive question.

Mosy probably, your thesis is not supposed to read like a collection of unrelated articles. Therefore, you will need one general introduction. It could contain information on

which components exist
how each component is connected to the whole
why components were separated as they are.

This does not preclude additional per-section introductions to explain more in detail what the upcoming section is about.

Proceed analogously for the conclusion and, of course, talk to your supervisor for any specifics.


How to appear legitimate when asking authorities about sensitive data for research? I am a graduate student, and I am interested in doing my thesis on the modeling of utility networks, and how they are related / dependent on each other.  A specific case I would like to model is the effect of simulating the effects on water treatment and delivery networks, from interruptions in electrical networks.  I have located some open water network data, and I can also extract electrical network data from sources like OpenStreetMap, but I would still need some information about where water treatment plants are located, and if they also happen to be connected via underground cables.

I thought about contacting the city on which I am planning on doing my modeling, but I feel as though it may be alarming to them to have a random person (currently going to school in a foreign country) suddenly asking questions about their critical infrastructure.  When asked why, my truthful answer of "I want to assess where the network may be most vulnerable to interruption" would likely not settle any uncertainties.

I am wondering if anybody has any experience in approaching this kind of situation.

Academic fieldwork is often a political game and appearing legitimate is certainly a key issue. I think if you are legitimate and upfront about where you work and what you want to do that aspect can be covered quite easily. But if there are sensitive data that they are not allowed to share, it will not matter who you are.

I think the first thing to do is to disclose your affiliation and explain what your are working on and how this organization's data are relevant to your study.

There are other aspects to consider so I will go slightly off topic here. It's sometimes very difficult to explain academic imperatives even to highly educated staff who work in other types of environments. They might perceive your work as an audit of their practices and can interpret your analysis as a challenge to their expertise. They might also want oversight on your writing and ask you to present their work in a positive way. You will have to be very diplomatic in that regard.

I think it safer to discuss data policy in advance: what you want to gather, what you will be showing in your thesis. They might ask for control over how their data will be published. You need to know in advance, ideally in written, what is OK and what not. The last thing you need is them to give you trouble when you're finishing up your thesis or after a paper is published.


I'm feeling discouraged after getting tenure; should I quit? A few months ago, and seven years after I obtained my PhD, I finally got tenure.  Hence I have a permanent position in academia.

After a few months in this new position, I find myself thinking of quitting academia. I do not know if this is because of my new status but I am quite discouraged and not motivated to do research. Meanwhile, it seems that I now face even more teaching, more administration and more research pressure than before.

Have you passed through a similar phase, and if so could you describe your experience?  I wonder if all these thoughts are caused by the transition from being a postdoc/assistant professor to being an associate professor, but I do not know.

Many faculty get post-tenure blues. There are several causes:

Burnout: You've been running at full speed for almost 30 years (k-12; college; grad school; post-docs; tenure track). Your brain needs a rest. It's perfectly acceptable for you to take a break. Many faculty have post-tenure slumps.
Survivor's guilt: Many of your grad peers didn't get jobs, you might have seen other faculty not make tenure. The tenuring process can seem capricious. You've just been through the sausage machine and you didn't like what you saw.
Imposter syndrome: Related to the above, you can't quite believe that you made it and you're doubting yourself. Were you really qualified to make it? Maybe there was a mistake in your file that they might catch?
Fear of commitment: You look at the other tenured faculty and are deathly afraid that you're now committed to be with them for the next 30 years. Oh god, what have you done. Your dreams of leaving academia and opening a bookstore-cafe by the waters of Lake Michigan are maybe just that, dreams.
Fresh fish: At many places, newly tenured faculty are fresh fish for burdensome committee assignments. e.g.: No one really wants to be the MA grad advisor but it has to be filled by a senior faculty member, thus the 'new guy' gets it. Some senior colleagues may actually tell you that you "owe" them because they "gave" you tenure. Bollycocks. You earned your tenure. You owe no one. Just try to remember the 'just say no' skills that you had as junior faculty and wriggle out of any and all commitments until you can figure out which ones you can tolerate.
Peter Principle: The Peter Principle ("people rise to their level of incompetence") is often misunderstood. It's not that you are incompetent, it's that you've been competent in one domain but promoted to a higher domain than where you've shown competence. Associate and full professors often have to do much more administrative work and intrauniversity politics than assistant/untenured faculty. When you're tenured, work becomes less fun and more bureaucratic.  And you wondered why your senior faculty were all sourpusses. Key to your sanity here is to remain in domains that you're passionate about (teaching, basic research, etc.) and enter into new domains only on your own terms. For example, if the provost wants you to be chair of XYZ onerous committee, then you need $x research funds or to go to y conference or get z course relief (h/t to J and Captain Emacs).
Paradise Syndrome also known as the dog who actually caught the car syndrome. You've been working so hard for so many years for something you finally achieved and suddenly you don't know what to do with it. You have to come up with new life goals and purpose for living (thx Pharap).

The most important thing to remember is that they can't fire you without serious cause. Take a break, say no, piss some people off by not taking on work. Let your brain stretch. Go kayaking. Work on your bucket list. And then after that, try to remember what made you so passionate about your field.

Finally, if you really, really, really want to quit and you can't take sabbatical or get a grant to buy you out for a semester then: take an unpaid leave. The provost should be willing to work with you - if not, you can use FMLA or sick leave if you can get your doctor to agree you need time off. It's better than quitting as it leaves you with your Plan A when you recover.


How to organize my papers and notes from the beginning of my PhD? I'm a first year PhD student.

I'm in my first stage (doing a literature review) but I face problem in organizing the papers I read and the notes I take for all papers. Should I put all that in one MS Word file for example, or different MS word files, or maybe use a different software?

I don't want to come after month from now and get confused about the way I organize my papers and notes in.

So, any helpful ideas?

First of all, a graduate school is a learning process so finding what is perfect from you from the start is a valiant endeavour but not necessarily sure fire.

You should start to use a data base system, some (mentioned in comments) that come to mind are Mendeley (free), EndNote (commercial), RefBase (free) to mention a few. If you consider going into LateX (which many of us swear by) then I can recommend JabRef (free; BibTeX format). There is also a Wikipedia comparison page that can be of assistance.

To sort your references concerns managing some form of structure where you  group or "mind map your articles. In the old days you simply kept them in piles. With a data base software you can start providing key words in the data base and also keep some short notes for each paper which makes everything searchable and ready for sorting. I think the process or sorting articles is one that changes with different tasks and also persons so you are best of taking some advice from others and looking into it. Hopefully you also have peers around who can provide their insights. In the end you will develop your own set of tools that suit your needs and to keep trying different ones at an early stage, and discarding many of them, is far better than trying to do it later when the mass of information is much larger. Another option is to simply start using something and sticking with it regardless of weaknesses.

The bottom line is that with experience you will rely less and less on note-taking and be more efficient at seeing structure in what you read and so keeping a reference database is the main tool you will use. Even if this may not sound very constructive, I also say that the time you spend now on testing different solutions will pay back later, putting it off is only pushing problems forward.

A final personal note. If you want a free, platform independent, and completely versatile way to author documents you should look into LaTeX-writing (for example through TeX.stackexchange). I recommend it to everyone unless you are in a complete Word-environment, being alone with a different system can be hard. You should nevertheless look into it.


How do I find researchers to collaborate with online? I am looking for researchers with whom I can collaborate online. Some ideas are hard to implement by one person. So, how can I find and cooperate with other   research students from other universities online?

First, you need to clearly identify your field of interest (for instance, Bayesian meta-analysis of clinical trials).

After that, it is up to you and your time and resources. These are some suggestions:

Look at other SE websites and visit the profile of leading
contributors (eg CV);
Check recent and impactful scholarly papers, retrieve
the email of the corresponding authors, and write to them (eg Chatterjee et al, JAMA Neurology 2013);
Look at
leading academic institutions in your field, and write emails to
selected contact people (eg David Spiegelhalter at the University of Cambridge);
Ask a local or nearby opinion leader for key selected contacts.

You need to clearly state your goals, your expertise, and your commitment, and then see if these fit. Try multiple times and multiple venues, eventually I am sure you will be able to create a fruitful collaboration.


When should I stop including talks on my cv? When I was applying for grad school, I felt that my CV was pretty empty and so I included all my research related presentations (posters/talks) from conferences/competitions/etc (11 of them at the time). However, I am not sure how much of a role they played in my acceptance at that time (I feel I mostly got accepted based on my papers and two very strong reference letters).

Now I keep a semi-complete (semi- because of infrequent updates) list of presentations on my website; this is mostly so I can post slides. However, I feel the list has gotten too long for a CV (~25 items; about a full page) and other more important parts of my CV (such as publications) have grown to need that space more.

When should I start omitting or shortening the talks on my CV?

If I include a 'selected' talks section: How many talks should I select? Should I select them based on prestige of venue, or uniform-covering of my interests, or uniform-covering of my time (show that presentations are a regular activity)?

More context: I am at the graduate-student level in my academic progression. A related question: Do presentations given during interviews count as invited talks?

First of all: note that there is a difference between an academic CV and a resume.

An academic CV typically lists everything you've done related to academia; every talk, every conference paper, every award, every grant, every mentored postdoc, grad, and possibly undergrad.
A resume is a two-page document that summarizes your work/academic experience.

(Terminology may differ, some may refer to the first as a resume also; semantics aside, there is a distinction between the two documents.)

That being said, the answer to your question depends on which document you want to complete. The first should have everything, no matter how old. The second should list your most important, more recent accomplishments, in the interest of space. Regarding the second, the answer to "when should I remove stuff" is simply "whenever you have newer and better things to put in it's place".


How to read Eigen factor and AI for a journal in specific field? I am trying to understand the reputation of a journal in specific field of science. I am looking at this journal CHI Paper. How do I read the information from the graphs and figure out how this journal compares to other journals?

Look at the entire list of journals in the field Information theory, where this journals belongs. There you see that ACM Transactions on Computer-Human Interaction is at place 53 out of 248, ranked by AI. By combining this number with knowledge of the field you can probably draw some conclusions.

In general, both eigenfactors and the Article influence score (AI) are reported by Thomson ISI as well, so they are well known. Look at the FAQ at eigenfactor.org and read the wikipedia article on eigenfactor for more info. In general, AI is more comparable to the impact factor, while the eigenfactor scales with the number of papers published in the journal. Also have a look at SNIP and SJR if you are interested in journal metrics, info can be found at journalmetrics.com.


Career advice: How can I move on from my probable PhD flop? So thing aren't going well for me with my PhD and I sort of think I'm not going to get there (hard deadline is September and frankly I think I'm fairly close to having a breakdown). I'm in the UK and the hard deadline is university policy.

How soon should I start looking for work outside academia? How should I go about explaining my (likely) failure?

I'm not sure I know what to do from here.

I don't feel confident about bringing this up with my supervisor. If I did, he would brush it off (he doesn't really get me, I don't think) with something along the lines of "What else are you going to do? Just get on with it.". He has expressed concern about my progress before now. Also, part of the motivation for asking this question is feeling well-researched on this topic prior to having a conversation, which I'm hoping will show my supervisor that I'm serious about it.

If this information is useful I'm based in the UK, I have a pass at Master's level already and a 2:1 BSc in physics and I am in an allied field at the moment.

I am going to answer from a rather different perspective, that of someone who has been involved in technical hiring, the sort of person who is going to be looking at your job application and possibly interviewing you if you go into industry. I'm a retired computer programmer and computer architect, and have spent many hours trying to pick the right people to hire.

I had a colleague who started on a PhD. and decided after a few months that he was not suited to that path, and would do better in industry. That was absolutely no problem.

On the other hand, quitting at this point, or later, in a 4 year project is a potential red flag. It would make me worry that you may throw up your hands and quit a few months before a deadline if the going gets tough, rather than rising to the challenge. That would be a serious negative for most technical jobs. Moreover, even if you think you know what went wrong, why you did not complete the PhD., you would have nothing to show that would give me confidence in your analysis.

On the other hand, suppose you continue with the PhD. through September, putting together the best thesis you can in that time. If it is accepted, great, carry on with the academic path.

If it is rejected, you still have something to show a potential employer. You would need to analyze what went wrong, and understand your strengths and weaknesses. You either need to correct weak areas, or pick a job that plays to your strengths and does not need your weak areas. For example, if your thesis has insufficient original results but is well written and presented, you could apply for jobs where original research is not required, but organizing and presenting technical information is important. There are plenty of those.

In a comment on another answer, you say "my supervisor has had a lot of successful PhD candidates". That means he is both good at picking students, and good at shepherding them through the thesis process.

I think the time to start looking for industry jobs is after the very best thesis you can write by the deadline, taking full advantage of your supervisor's advice and shepherding skills, has been rejected.


As an inexperienced/unknown recommendation letter writer, what should I do to make my letter stand out? It is generally acknowledged that one should try to get recommendation letters (for grad school, jobs, etc.) from well-known experienced members of your field, if at all possible (for e.g. see some of the answers to this related question: Do letters of recommendation typically include a biography of the writer?). Of course, sometimes this is not possible.

I am a first-year postdoc (in mathematics, but perhaps this is not relevant), and a masters student in the graduate-level class I am currently teaching approached me to write a letter for them when they apply for PhD programs. I am a natural person to write a letter for them since they are interested in the field that I teach (topology) and I'm teaching one of the three courses they are taking (since application deadlines are quite soon, they won't have taken any other courses here before applying). Of course, I am also a poor choice (which I mentioned to them) as a relatively unknown person with little experience.

While it makes sense to me that recommendation letters from senior research-focused faculty are worth more (since they have greater experience interacting with graduate/soon-to-be-graduate students), there are a fair number of students from relatively obscure 4-year universities who apply to graduate school. They might not have had any access to senior research-focused faculty.

  What are some things I should keep in mind when writing a recommendation letter for graduate admissions as a new entrant to my field, or perhaps as an instructor at a relatively obscure primarily teaching-focused school?

Statements like 'they are in the top 7 of all graduate students I've ever taught' carry little weight, since I've only ever taught 7! For what it's worth, the student in question is doing quite well, and my goal is to write a well-deserved relatively glowing letter; I would like to make sure, as much as I can, that my letter is not ignored.

My advice is to start your letter by explaining who you are and your background.  For example, you could mention where you went to graduate school and that you think the student could succeed in that graduate program.  This will give the reader a sense that you have some idea of what will be expected of the student in graduate school.

Beyond that, you should focus on the same things that more experienced letter writers do.

You need to explain how you know the applicant and give the reader some sense that you've had enough interaction with the student to be able to judge their chances of success.  Simply having had a student in a large class isn't really enough here.  On the other hand, "I was Johnny's instructor in a senior level topology class with 12 students.  Johnny frequently met with me during office hours to ask questions about aspects of the subject that we were not able to cover in class." tells me that you have had many discussions with the student and really know the student well.

You should comment on both the applicant's intellectual ability and their work habits.  Ideally, we want applicants who are smart and work hard.  An applicant who isn't very smart but smart enough and who works very hard might be a good candidate for admission to a master's program but might be a very poor choice for a PhD program.  An applicant who is brilliant but lazy might start to work harder in graduate school and could turn out to be really successful.  Some faculty are willing to take a chance on brilliant but lazy students.

You should talk about the applicant's personality and how they get along with other students and faculty members.  No one wants to work with a student who is not fun to be around because they're argumentative or depressed all the time.

You should talk about the applicant's communication skills (both writing and oral presentations) and in mathematics you should comment specifically about their ability to write mathematical proofs.

If it's relevant (and it would be for any area of applied mathematics) you should comment on the applicant's computing skills.  What languages and specialized packages have they used in their work with you?  Have they been able to produce programs of any substantial size?

You should check that what you've written matches up with the student's transcript and their statement of purpose.  For example, don't say that they're one of your top 5% students if their GPA is 3.0.  Don't say that Johnny would be a great master's student if he's applying to a PhD program.  If the "story" told by the applicant's application file isn't consistent, then I'll be much less likely to admit a student.


How to unintrusively distance myself from control-freak advisor and ride out the end of my PhD? I am the PhD student of an advisor who is known within my institution as extremely strict, controlling and prone to temper tantrums, making undergrads cry in lecture halls, etc. I am in my final year of writing, 12 months to go with all of my experiments completed and 60% of my writing done.

I have found my own ways of managing our relationship (i.e. to grin and bear it), but now, in my final year of thesis writing, I am finding it increasingly difficult to cope. He is extremely controlling of my personal time: making it clear that he expects me to work 12 hours a day, 7 days a week 'just to keep my head above water'. Though he always cheerfully reminds me that 'deadlines are flexible', on the rare occasion that I do try to take him on his word (this has happened twice in 4 years), he completely flips out and makes me work to the deadline (even when this has meant me working 20 hour days). This happens even though the events are out of my control (a problem with an experiment, the death of a friend) and though I have never asked for more than 7 days extension. The death of a friend thing happened recently and is the straw that broke the camel's back, I just can't understand how I couldn't take a week to deal with that (it was over Christmas, when I was still 'supposed to be working'...).

I would almost understand his behavior if I were a terrible PhD student in need of a kick up the backside, but by all objective accounts I am on track to finish well before schedule. My advisor tends to go through periods of bombarding me with compliments and praise for my work, teaching, etc. until I feel totally great about our relationship, only to completely flip and treat me like a child in need of chastisement. What disturbs me about this is that he will often make me agree that he is in the right, and that he is 'not a horrible advisor, just has my best intrests in mind'. Two friends of mine have left our research group because of difficulties working with him, telling me personally 'I don't know how you are able to work with him, I feel sorry for you.' A friend's advisor has said: 'I hope Anon is OK and has someone to talk to, their advisor is really tough'. I'm including this context because I consistently doubt my own perception of this situation, and need to justify my feelings to myself (and anyone reading this) by remembering that others corroborate my perception of my advisor. I am also extremely paranoid about him finding out about this (hence not using my usual SE account).

Usually, I would make my feelings clear and ask for a mature discussion about our needs, but I think my advisor will take that as confrontation and I don't want to jeopardize my thesis or my job prospects in these final stages. I am too apprehensive to talk to other staff in the institute about this in case somehow word gets back to him.

At most, I'd like to get a good reference and bounce out. At least, I want to survive with my sanity and happiness in tact (I have self-esteem problems and am feeling increasingly awful about myself - I see a therapist so I'm accountable to someone and don't plan on hurting myself etc.).

TL;DR: Overbearing advisor, I feel increasingly bad. My strategy at this point of is to continue my mantra of 'grin and bear it', keep a low profile and ride out the end of my PhD. Please could you share some strategies for doing so in a non-confrontational way?

My advisor tends to go through periods of bombarding me with compliments and praise for my work, teaching, etc. until I feel totally great about our relationship, only to completely flip and treat me like a child in need of chastisement. What disturbs me about this is that he will often make me agree that he is in the right, and that he is 'not a horrible advisor, just has my best intrests in mind'.

Your advisor is abusive, and this is classic gaslighting. It can really do a number on your confidence, and "I consistently doubt my own perception of this situation" is exactly what this behaviour is designed to achieve. It is very difficult to keep/regain perspective within that situation.

Recommendations:

Minimize face to face interaction as much as possible. With e-mail, you can go back and re-read the past conversation, and confirm that things were like you remember them.
In the same vein, document all your verbal interactions, the positive just as much as the negative. Keep a journal or an advisor log. Re-read what you wrote during the last 'nice phase' when your advisor is being nasty, and vice-versa. This will help you keep some distance from both (giving you a better perspective of the whole situation). It will also be very helpful in case the situation deteriorates and you need to argue for yourself against your advisor with the administration or others. People like this are extremely good at convincing others that you are the crazy one - so good, they can even make you believe it yourself.
Read up on the patterns and techniques of abuse. There are few resources for abused grad students, but it fundamentally all works the same way, so looking into husband/wife or parent/child abuse you will recognize many facets. I highly recommend Lundy Bankroft's "Why Does He Do That", it's an incisive analysis of abuser mentality.


Isn't English the common academic language? In a question about university ranking, many people mentioned that language is a privilege for better ranking of English speaking countries.

Isn't a decent fluency in English the requirement for senior academic positions (regardless of native languages)?

Most ranking factors are about research activities. If a professor in non-English speaking country is not fluent in English, how does he supervise graduate students? For supervising/conducting cutting-edge research, someone should be able to read technical literature. Research papers are published in English (and there is no translation normally).

Most non-English speaking countries with excellent higher education (such as Scandinavia, Netherlands, Switzerland) offer the graduate programs in English.

I understand it is easier for native English speakers to read and write in scientific literature, but we don't speak their language, we speak an international language, which is their native language too.

I understand that this requirement is neglected in many countries, but is it reasonable and justifiable to give a senior academic position to someone who cannot read 99% of recent research findings in his field?

Is it acceptable for a professor or even a PhD student to have no understanding of English language? To avoid confusion, consider STEM fields.

In this answer, I will respond to some of the points raised in the question, however without any expectation of completeness.

  Isn't a decent fluency in English the requirement for senior academic positions (regardless of native languages)?

To some extent, it is, although there are probably many different interpretations of what "decent fluency" means around.

  If a professor in non-English speaking country is not fluent in English, how does he supervise graduate students?

Maybe I'm misunderstanding this, but ... simply in their non-English language? There is no general requirement that communication with graduate students (including foreign graduate students!) would have to happen in English.

  For supervising/conducting cutting-edge research, someone should be able to read technical literature. Research papers are published in English (and there is no translation normally).

This is true, however I have noticed that there can be extremely wide gaps between the ability to read and understand complicated English texts and the ability to express complex ideas in English. Hence, a capable researcher can be perfectly able to understand technical literature written in English, and yet be unable to publish their own ideas in English.

Of course, this is not generally the case in all non-English-speaking places, but it probably depends on how English is trained or learned.

  I understand it is easier for native English speakers to read and write in scientific literature, but we don't speak their language, we speak an international language, which is their native language too.

If it is their native language, too, then we do speak their language. Whether our motivation for learning or using English is to communicate with native speakers or with the international community doesn't matter; the result is that, as you say, "it is easier for native English speakers to read and write in scientific literature".

  is it reasonable and justifiable to give a senior academic position to someone who cannot read 99% of recent research findings in his field?

As explained above, comprehension is not necessarily the same as expression. And even then, this statement possibly neglects that some fields might rely less on English than what I am used to from CS.

  Is it acceptable for a professor or even a PhD student to have no understanding of English language?

No, rather not.

Coming back to your titular question:

  Isn't English the common academic language?

Yes, in many fields, it is. But this mere fact has little influence on the effects you allude to. It neither means that English material is inaccessible to someone with low skills at writing in English, nor that ideas and surveys are always developed and conducted in English from the start.


citing company yearly reports in papers I am writing a conference paper and want to cite the following report by Symantec using Bibtex (https://www.symantec.com/security-center/threat-report). I am currently using @techreport which only needs author,title,institution, year and month, but I am having trouble getting the authors. At the end of the report it has team and contributors listed, are team considered the authors ? also is @techreport the right category to use or should I be using a different one ?

One alternative would be to use a corporate author.

Using Harvard referencing for an undergraduate course I did a few years ago I cited annual reports like this with no problems.

Taylor Wimpey, 2014. The Taylor Wimpey Annual Report, High Wycombe: Taylor Wimpey.

The Berkeley Group, 2014. The Berkeley Group Annual Report 2014, Cobham: The Berkeley Group.

Standard Life Investments, 2015. The UK Stewardship Code- Compliance and Contacts. [Online]
Available at:
http://www.standardlifeinvestments.com/governance_and_stewardship/the_uk_stewardship_code
/index.html
[Accessed 15 March 2015].

Key Note Reports, 2015. Bellway PLC. [Online]
Available at: https://www.keynote.co.uk/company-report/ownership/01372603
[Accessed 3 March 2015].

If it is a team of authors and you are adamant to put an author if there are many authors the Harvard system allows you to put Smith et al. even in the even reference list.

Microsoft word is great for references and should not be overlooked for a simple and effective referencing tool.