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CV for leaving academia after PhD
I am soon finishing my PhD in computer science and I decided to leave academia for the industry (not industry research).
I am not clear about what to include in the CV.
I currently structured it like this:

Education
Work experience (including teaching positions and internships)
Selected Honors, Awards & Fellowships
Programming Skills
Selected journal publications
Selected Workshops, Schools  & Conference Talks

which in its current version results in a two page CV.
I am neither sure about the ordering of the above items as well as the importance of each.
For example while I have ten publications I only mention two of them in the CV. On the other hand I mention about eleven Workshops, Schools  & Conference Talks. I think this is not the right balance. On the other hand I am not sure how much companies (like Facebook, LinkedIn, ...) care about theoretical publications. I also do not mention any research visits I did.
So my question is, what academic information do you include in a CV for non academic positions and how important is each of the items?

In http://www.chrisstucchio.com/blog/2012/leaving_academia.html on academic CV versus resume.

Many universities have a career services office   which can provide advice to students on preparing a resume or CV. That might be a good way to get personalized advice.

A gut feeling kind of comment: a two–page CV isn't really too long, as long as you place the important things up (what you've done as opposed to what you were talked at about) on the front page. I'd say hiring managers don't toss a CV based on length as much as pay less and less attention over time.

There several sample CVs available over the net, moreover, you may take a look at your own professors and advisors to see how they have organized their CVs. They are in your field and their CVs are the best examples to you.

The current structure of your CV looks like an academic CV to me. You put too much emphasis on the academic credentials. You definitely need to rewrite it.
What the industry (not industry research) companies are looking for are your skills and experience. They are not interested in how many publications you have or how many conference talks you gave. They are interested in how much you know about solving problems so that you can help them to make money.
I would suggest you to emphasize your programming skills, the contents of your publications (what kind of problems you solved in those papers), the internships, etc.
Don't under-estimate your teaching experience. Emphasize it. Many hiring managers had told me that they like the teaching experience on my resume. I asked them why. They said I must know how to communicate because I can teach. Knowing how to communicate to others is an essential skill in industry.
Good Luck!

I felt compelled to sign in and +1 this for teaching experience. I am in a similar position, and my CV was in ok shape, but I had completely discarded my teaching experiences, and what better proof of communication skills than teaching. Thank you

Teaching experience as an asset is surprising. I thought to leave these things out, as I would not be able to support such claims properly.Do they really consider teaching experience at the low skill level of TAs, rather than proper teaching that is supported by formal education?

@gschenk What they really care is that you are willing to transform the teaching experience into the communication skills. The teaching experience itself is rarely useful unless you work as a training instructor. But, to make people understand highly technical stuff requires some communication skills you gain while you teach.

I am not sure if you are writing a CV for particular position or a CV to put on a web-page.
A common advise is to fit the CV to the particular position (What makes a good CV? section) you are applying for. So lets assume that you are writing something like your CV template.
In such a template I would suggest to put as much papers, experience, skills and relevant information as you can think of. This may significantly shorten the time of CV preparation for any particular position in the future.
Later on, when you will prepare a version of your CV for particular job, you will delete all points which are not relevant as you want to keep your CV as short and as relevant as possible.
So to answer the question: you should put that academic information which is relevant to the application. In some jobs, it can be relevant that you are able to write long texts, in some others that you are able to lead a group of people, speak in public or your innovative thinking and so on. So put everything now and choose the relevant content for each CV later.
If you feel that the list of the conference talks, or the papers is way to long you can include only 5 the most important or the ones which can be easily checked. In case you really want to emphasize the quantity of your work, put list of the papers/conferences on a separate paper or provide a link of such information in the accompanying letter or mail.

tl;dr: The industry hiring process is entirely different from academia.  You'll have to adapt but it isn't that hard.
Note: It's not clear from your answer whether you're in the US or elsewhere so please translate my US-centric answer to fit your situation.
I received specific advice on this subject when I was doing the same thing years ago.  It's a variant of "speak to your audience":

A one-page resume is for the human resources filters.
A detailed CV is for the people with whom you want to have a detailed conversation.

The human resource filtering problem is a serious one.  From the point of view of HR, everyone in the world is applying to the job, regardless of experience, requirements or even location.  HR might not even know what all the technical jargon means but they're looking to filter that pile down as fast as possible.
So, you need to write the one-page resume carefully to fit the position description and set of requirements.  Yes, they're looking to see if you've ever held paying work and who they can call to confirm that.  However, they're also looking for certain called out buzzwords and key points.
For example, if they use the phrase "required experience elements" in the position description, make sure that your resume has a bold "Experience elements:" section.  If the description asks for "Java", make sure your resume describes your use of Java for each position or project that you list.
In short, the resume is all about taking away their excuse to say "No."
The CV is an entirely different thing.  Someone who's interested in your CV knows a lot about the details of the position and wants to have a detailed conversation with you.  With the CV, you have the ability to reduce a lot of the friction: you're already volunteering plenty of the "tell me about this project..." content up front.
Here's what I did:

Rewrite the resume from scratch for every job, tuning the words to fit the position description.  It's not that onerous: it's only a page.
Offer the CV in correspondence.  These days, I would probably point them to LinkedIn or careers.stackoverflow.com
If I was called in for an interview, I would brought several paper copies of my resume and CV tucked in to my portfolio of previous work.

Repeat all of the above far more times than I like to remember and eventually you find a paying job....

This.  Even with substantial experience working in the field, 1 page resumé is quite possible.  Your detailed CV is nice but shouldn't be given to the HR folks.  The only time I'd give the CV first is if I had a personal contact in the company; then I'd either ask that person which they preferred (the overview or the detail).  HR reads a ton of resumés for every job; make sure the few points they really care about (from the job description) are clearly marked in the resumé, so a non-technical person can understand you're clearly qualified.

@Joe, another great example. Your personal contacts are likely already asking for your CV so that they can market you internally inside the company.

I don't see any reason to omit your publications, since in your proposed ordering they are at the end. You definitely want to indicate your programming prowess as soon as possible. It might also help to insert a line above the Education section indicating your areas of expertise and interests. This is useful for bots that look for keyword matches.

I'll just add a few points a couple of friend as recruiters told me.
The Interviewing process usually goes through HR first, believe me, they could not care less about your publications.
That is the short form CV, is the one you usually give out first. And since is HR people who will be looking at it first, you have to put emphasis on WHAT tools you know how to use.
For example:

My research consisted on the optimization of distributed systems

That is mute for an HR, and more than one TI manager. But if instead you rewrite.

During my research, I used extensively tools like HADOOP and JAVA in a team setting, using collaboration systems like Github (even saying subversion might not help at all).

Both sentences are saying the same, but in the second one you are specifying which tools did you used.
Remember that academic buzzwords like "parallel computing" , "probabilistic inference", etc. Do not mean much for many recruiters. They care about the tools, and how long have you worked with them.
If you have a github repository with some examples, that might help them as well (I'm assuming you are a programmer)

You may find the website Versatile PhD helpful, as it provides guidance on how to transition from an academic research track into the non-academic market.
The most important thing to keep in mind, though, is that you need to stop thinking in terms of the incentive structure of academia (i.e., firstly publications, secondly grants, positions, and awards) and start thinking in terms of skills that you can offer.
This usually means you need to organize your resume in terms of employment or projects and the skills and competency you demonstrated therein. If you have project management skills (supervision of research assistants, for example), programming skills put to use in projects, or other skills (meeting deadlines, working collaboratively with others, etc.) these are the things to emphasize as bullet points under jobs/projects rather listing out academically-valued output (pubs, presentations, grants, visits, etc.).
Also, if you're applying for entry-level jobs in industry, I see no reason why your resume should be longer than one page. If you have an online presence, you can always have a longer CV online that possible employers can look at if they're intrigued by what you have to offer from your short-form resume.

Assuming you're looking into joining a Dev Shop, I'd ensure that your CV includes your engineering skills.
What do I mean by engineering skills?
Which source control tools are you familiar with?
Which test frameworks have you used?
Have you used any CI tools (i.e. Hudson)?
Which Agile methodologies do you use?
Have you contributed to any open source projects?
Do you have a github account so that interviewers can see your code?
There is a perception that developers from Academia tend to be a little light on these skills, so it's important to ensure your CV describes them.

If you already have industry experience, then highlight it prior to your academic achievements. Given that you don't have any industry experience, exploit your PhD thesis as an actual project in term of how did you manage, designed, developed and why it is significant especially to industry. It automatically qualifies as a project if it was not in theoretical computer science, otherwise you need to justify how the theoretical aspect is valuable for industry. From this point of view, you can add your PhD time frame as your work experience and demonstrate that research was actually working on a project. For many tech companies, even personal pet projects are considered valuable, so in that sense a good research project is invaluable.
Your CV should flow from a Summary, Skills, Experience and then Education. Remember, the industry is interested in your computer science skills not your qualification. The final and probably most important point is that you should aim for organizations closer to your field or at least the jobs which are closer to your skills rather than applying to every single developer/analyst position.

Since others have this covered fairly well, I'll add only this: make sure that your main bullet points are recent!
Here's a few examples:
When you're applying to colleges, they want to know what you did in high school.  They don't care about K-8(in the US).  They want to know extracurricular activities, standardized test scores, etc.
When you're applying for grad school, they want to know what you did in college.  What's your overall GPA, what's your major's GPA, GRE scores, extracurricular activities, undergrad research positions, internships, etc.
When you're applying for your fifth job in your career, they want to know what you did at your previous jobs.  They may still be interested in knowing your Alma Mater, graduation date, and GPA, but they're less interested in all of the details.  You've had 4 jobs since college, and they want to hear about your successes in those jobs.
Likewise, when leaving academia for industry work, they will want to hear about your grad work first and foremost.  Others have mentioned the kinds of information you should include - such as skills - so I won't say much other than to say these look good:

Education
Work experience (including teaching positions and internships)
Selected Honors, Awards & Fellowships
Programming Skills

Teaching experience can easily translate into communication experience.  Communication is a great skill to have in the industry, and if you're able to communicate with technical and non-technical folks alike, that is a huge advantage.
Honors, awards and fellowships are proof that you're not lazy, that you're motivated, have initiative, etc.
On the other hand, your last two bullet points about publications and workshops probably won't gain you much, if anything.
In short, make sure to highlight your accomplishments in college, nothing earlier than undergrad, and focus on your graduate years.


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Why do potential reviewers take a lot of time to reject the request for review?
I understand that reviewers are quite busy and have not only a single paper to review. But, no matter how busy someone is, it should not take more than 2 minutes to reject a review request.
How did I get this question to my mind?
Well, it is a common question for everyone in academia, I guess. I am quite frustrated with the peer-review system and yes, I am impatient. Because after doing a lot of hard work on something and then achieving something real good out of this, which would lead to potential dissemination, turns out to be depressing.
We had submitted a work back in December 2016. Since February 2017, It was Under review. Suddenly, I see that it is Reviewer assigned. This system is really pathetic. Other parts of my question can be inferred from this.
As a reviewer, I don't reject the requests for review after 4 months. I would do the same within at most a week.

This doesn't seem that long to make you frustrated. There could be a gazillion of reasons for that. In academia, you should learn to be patient. I have a paper under review for ~18 months.

This site is not about agreeing on universally binding courtesy codes for academia. There are thousands of possibilities, ranging from the time of finding a reviewer that responds (yes, as editor I have had many review requests not even bothered to be responded to - perhaps they ended in spam, perhaps the reviewers do not read their email, perhaps they are disorganised, who knows), to one that actually says yes, to one that provides a useable review. Impatienceis not a virtue, either. Editors/reviewers do not get money, they do their job for the greater good.

Besides being a rant, I see a real question here, so I would not vote to close.

If you're managing your various responsibilities and due dates well, more power to you!  It will be interesting to see how you're doing with being well organized and on time with everything ten years from now.

In addition to the Kerkyras answer, here is what happens all the time when I receive an invitation:

The potential reviewer needs to find the time to skim the paper to form a well founded decision to accept or decline to review.

I want to accept a review when I am sure that I have the expertise and time to do a good review. It takes about 2 minutes to decide if I have the time for a review (usually my conclusion is "no"), but to decide whether I have the expertise is more complex (and if the answer here is "yes", I often agree to review, even if the answer to the former question was "no"…). Hence, a basic skimming of the article is needed and this may take some more minutes. Some days (or even weeks) are extremely busy such that finding just 10 minutes to skim a paper is hard.

A long time before review request rejection could come from a lot of possible reasons, which all basically translate to "the potential reviewer had something more important to do than answering a review request" (with his/her own subjective definition of "something more important").
Examples include:

the potential reviewer received the notification at a bad time and then forgot about it
the potential reviewer thought that a lack of answer would automatically be interpreted as a 'no', but it wasn't for several weeks
the potential reviewer deleted the email without reading it
the potential reviewer was out of the lab
the potential reviewer has been (sincerely) "meaning to do it tomorrow" for three weeks
potential reviewer #1 couldn't do it and said so in 3 days. So did potential reviewers #2, #3 .... and #58.

I made a provocative list on purpose, but most probably the long delays are partly due to people being busy and taking a few days(weeks) to answer (if you're in academic research, you should know about having a lot on your mind), and partly to several rejected review requests before finding someone accepting to do it. If you also add the fact that some people just plainly don't care, you're well into your 4 months of waiting time. As it is said in the comments: learn to be patient, there is no other option!

Maybe additionally a very important point would be that the person who got sent the invitation for a review is no longer in academics and thus simply doesn't answer. I think this happens very often with the highfluctuation of PhD students and Post-docs.

Regarding your third bullet point: these days you still can't exclude that the email got tagged as spam and autodeleted without the recipient reading it.

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How to ask, if at all possible, what part of my CV interested the interviewer to interview me?
I'm having a postdoc interview coming up, which is not in my doctoral topic or not so closely related to my previous postdoc research. While applying for it, I thought I'd not called for an interview, but luckily enough, I did. The reason I didn't think I'd get called for an interview, as I can see that I'd need learn quite a few things that'd take me easily a minimum of three months to get the hang of.
So will it be rude to ask my interviewer her/his motivation to interview me or what (s)he thinks I can do for her/him, or if not, then what's the best way to formulate my question, without sounding like I'm trying to hear some good words about myself from the interviewer? I guess one of the option might be "What part of my backgrounds can be useful to your project?" but I'm looking for a sincere, honest and a genuine reformulation of this. I'm interested in the project but my concern is it might take me at least 3 months to get myself up to speed to start to solve the problems.

This is really asking for opinions, so I won't answer. But it might be better to ask what you need to work on in the short term to "hit the ground running". The question you suggest doesn't have an "action" component.

I found that in my professional life being honest, clear, and direct have served me very well. So once all the probing is over, I would say:

I have an additional question: Even though I am very interested in this position, I was doubtful I would be invited for an interview since my background doesn't seem to match perfectly. Would you mind telling me why you think I would make a good candidate for this position?

Of course adjust the wording to your style and take the details with a grain of salt as I am a non-native English speaker.

Your example is fine English. I edited it a touch to be grammatical. I left it, but "Would you mind telling me why you think ..." is probably too much prevaricating. "Why do you think ..." would be fine

Thanks Azor. It's a permanent struggle for me to read my emails/comments and edit out useless filler words and phrases.

I'd bring it up as wanting to optimally contribute your skills to the project and understanding the vision/goals of the project. "I know you are an expert on X. I'm good at Y which isn't exactly the same thing. What were your goals for using Y to accomplish X?"

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A specific question on writing research statement
I'm applying for a postdoc position at a university that asks to write a research statement taking into account possible interactions with research groups/faculty within the different departments (e.g. math, physics) of that university. I'm trying to understand whether this means:
a) I should write how my research connects to the different departments, i.e. I should point out how my research has some connection to the research of faculty X in department Y of that university, or
b) It's enough to mention my own research or their connection to different areas, without the mention of the faculty X in department Y.
So to be specific, say my research in math corresponds to quantum physics and say a faculty named John Doe in the Physics department wrote a paper in quantum Physics. So is it better to mention in the research statement "my research has connections to this area of quantum physics" or "my research has connection to this area of quantum physics, carried out by faculty John Doe in department of Physics"?
I tend to think it's b), because in a research statement, people don't normally mention how it can be connected to some faculty's research, which can be done in a cover letter. Advice appreciated!
P.S. After contacting the job poster, I was told that there'd be no requirement to contact a faculty member separately and hence submit a joint proposal together. The applicants won't be required to submit proposals anyway. Just thought of mentioning that in case it helps!

Is it possible to for you to get examples of what others have written for their statement?

I'm concerned that "interactions" might mean existing professional relationships with current faculty. Perhaps you should clear that up? Or even previous contacts with them.

They don't only want to hear what they will be working on, and what topics this is related to.
They would like to see how hiring you would lead to new interactions, that is, discussions, collaborations, joint projects and papers, and so forth, in the department and at the university.
So you should outline your research interests and planned research, discuss how this is connected to topics covered by other researchers in the department/university, and highlight where you see possibilities for collaboration.
So no, just connecting to the field, not the person, is not enough.  You collaborate with people, not with fields, and this is what they would like to see.  (Note that this means that you should ideally have a specific look at the people you might want to work with, and make it concrete where you see room for collaboration ("this opens up the possibility for collaborations with Prof. X, e.g. on the topic of [specific idea 1 and 2}".), rather than staying very general. Ideally, i should be a statement tailored to those people, not a generic statement.)

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Two questions regarding submission of reference letters for INRIA postdoctoral application in France
Please let me know if this questions doesn't abide by the rules of the site and I'd be glad to take it off. In this case, I'd also appreciate if you can tell me where I should post this question to get the best answer.
I'd like to apply for a postdoctoral position at INRIA, France, and I'm noticing that the places for recommendations are optional, see this link for a screenshot of the application page. I'd like to ask two relevant questions:
1) Are they truly optional for INRIA postdoc position applications?
2) In case I decide to submit my recommendations anyway, is it possible that I ask for the references to be sent to me, and I upload them myself, as opposed to the referees uploading them for me. And in the second case, it's apparently not clear how the referees will upload their letters to my application file?
P.S. I already contacted the job poster (= potential postdoc mentor) and the team's administrative secretary, by email and phone, only to get no response.
If you work at INRIA as a researcher or had a successful postdoc application at INRIA, your answer will be ideal but I'm happy to hear from all of you.


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PhD - How dependent are public universities on funding from the US Government?
I had a conversation with a potential PI regarding the funding situation from a public university and he left me with the following - "There is a threat of funding cuts for science (due to Donald Trump's policies) but the department will fight to ensure that this doesn't affect students"
That sounds good but in the end, is there now a strong reason to opt for private universities to avoid issues with funding? I'm an international student picking between a very strong (top 10) public program and a top 25 ish private program. Most other decision factors are roughly similar for the two.

The "public" part of public universities is about funding from the state government, not the federal government.  Federal funding is more often in the form of research grants, etc, which are received by both private and public universities, and federal funding cuts would affect both.

As Nate explained, these cuts aren't relevant to whether a school is public or private; the factors are much more complicated than that.  Public schools in many states have gotten serious funding cuts in recent years, but that's not a decision that's made by the president, but by the governor and legislature of those states.  You can research whether they've been doing so at the public institution you're looking at, but of course, the situation could easily change after the next election.  I think this is just too complicated to really try to game out how things will be impacted; I think probably the best source of information is talking to other students at the institutions and the precise financial details in your offer.

As one example, Cal Berkeley now gets only something like 15% of its budget from the state of California.

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Unfunded UK PhD offers - both deadlines imminent
I have two offers for a physics PhD in the UK. Both are great choices and I don't really have a preference. However, neither is funded so far and on both sides, the PIs are actively looking for funding and I think the chances are very good that I will eventually get it.
Both universities have a deadline for acceptance by the end of the February and the funding situation certainly will not be resolved by then. What do I do? I'm essentially ready to commit to whoever has funding. Should I accept both offers now and withdraw from one later (assuming this is allowed) or should I ask for an extension from both?

this is highly opinion based question, I think moderators will not allow it, I suggest you to add more information in order to improve it. also I would add. dont accept anything without funding

What field are you in? In sciences I would strongly discourage accepting an unfunded offer.

I wouldn't recommend it. I started a PhD when I had my own funding for the first year. The second year some money was scraped together, but after that there was a complete failure to find funding. Things got ugly.
If you are really intent with working with one of these two PIs, make sure they have a solid and extensive track record with funding. If these are new labs, forget it. But since you don't seem overly interested in working with them, I would say find a safer option.

Sorry, I think my tone came off the wrong way - these are my top two choices and they're both really really good places. But it's simply that their funding will not be sorted before the decision deadline. So ask for an extension?

Sure - see if they give you an extension, it wouldn't hurt. In the UK, it doesn't really matter what time of the year you start a PhD anyway. They should understand that accepting a position without funding is risky. In the meantime, if you can find somewhere with funding as a plan B, I would do that. But I wouldn't accept anything without funding.


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PhD or physics as a hobby?
I completed my undergraduate degree in physics in a good university (outside the US). Because of financial commitments, I couldn't leave for grad school straight away. So I worked for a couple of years as a research assistant at the same university after I graduated. I did very well, got three papers out in around three years and picked up a master's by research for that. I loved my time working in physics but the research assistant job was a temp job at best and I eventually had to leave it.
Now I work at a well known engineering company. The job is relaxed and spare time is plenty and I'm being paid well. There are good opportunities for growth because the company is about to expand in a big way. I also love having enough time for hobbies, fitness and just life in general.
I also applied to PhD programs in the US and was accepted into several good ones. The reason I applied is primarily because I miss physics and I am interested in being really good at core physics. I have this feeling that my education is unfinished in some way. I want to be that guy who has a deep understanding of fundamental physics. That guy who can easily answer questions on the physics stacks. Maybe I'd even like to write a textbook someday. I liked research when I did it but to be honest, I'm not sure I have that same fierce passion for it as I do for learning. In addition to this, I know I'm not cut out for the academic tenure track - Even if I were smart enough (and this is not impostor syndrome or anything, I am self aware enough know that I am good but not great), I have no interest in chasing low paid postdocs and living with the general instability of post PhD life. In five years, when I complete my PhD, I will likely end up in a very similar job to what I have now.
With this in mind, should I simply stay in my regular job and do physics as a side hobby or actually do the PhD?
TL;DR Is it worth doing a PhD if learning and mastery of physics over research is the primary motivation and sacrifice a great career for it?

This really depends on your personal preferences. We can only help with information, not with decisions. Is there anything you need to know?

when I complete my PhD, I will likely end up in a very similar job to what I have now Based on my over 30 years of industry experience, I am not sure about that. I mean you may not be able to find another industry job that can give you enough time for hobbies, fitness and just life in general.

Primarily goal of PhD is to learn independent research. That is something you don't care at all, so why would you do it?

I realize a lot of people who participate in Academia SE feel that PhDs are all about doing original research.  However, a PhD is also a path to teaching at the college level.  Furthermore, full-time physics grad studies might lead you to conclude that at a certain point, you feel satisfied, at which point, you could withdraw from the program (perhaps with a master's).  Or, you might get interested in a research project and keep going.
Why not start by putting a foot in the water -- taking one physics course at a time while you continue in your current job?  Perhaps your company will even pay your tuition.
Taking some courses in this way might make your decision easier.


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Abbreviating authors' names in a paper
I'm writing a rebuttal to a paper that was recently published. Since I refer to the authors very frequently, I've abbreviated their names to WW for their last names Williams and Wang (I made up these names, they aren't the real names). Is this appropriate for a scientific journal? Should I write W and W or W&W instead of WW?

W&W might work if the journal permits it. But Williams & Wang is likely better.

It depends entirely on the journal's style - each journal should have a 'style sheet'/'style guide' that says exactly how they expect everything to be formatted and cited. You should check the journal's website for this.
(IMHO, unless you're really short on space, I always think it's nicer not to abbreviate... but there are different opinions on this both on a personal level and on a field level.)

I hope they are not Williams and Coleman, or that you are not writting a rebuttal on Holocaust themes on the paper of Schutz and Saponer ...
Jokes apart, I would say that if you have so much to rebutt on one single paper, either you are spreading out the discussion of some sentence/ideas on too many sentences/part of your rebuttal, or that you should investigate previous work of Williams and Wang to understand why they say something.
Be concise, rebuttal works are often desk rejected because too long, then refused by editors, and finally required to be way shorter than you would possibly, so saving some hundred of characters from the names is not what will help you ...

On the other hand, if this is a reply to Cox and Zucker's famous paper, perhaps, CZ would be better?

@XanderHenderson I am sure there is a joke, but I am missing it :D

At least in economics, it is fairly common that a paper which extensively discusses another paper will abbreviate the authors' names in such a manner. It would not be unusual to see a paper cited formally at the first mention along with an abbreviation for subsequent mentions, for example, "Williams and Wang (2022, henceforth WW) ...".
It would be difficult to say if this style will be accepted in a different field (or even a different publication), but it is evidently accepted in at least some places.

Good to know that this is common. I ended up using WW and waiting for the Journal (which didn't have any published advice on this) to potentially ask us to change it.

Another way to deal with this is through the use of a) Pronouns (they, them, their) and b) Terms such as "the authors" or "the article" and so on.
But the ultimate answer, of course, is what @PFD said: "It's up to the journal". And if their style sheet doesn't cover this, then I wouldn't worry too much. The journal isn't going to make their decision about publishing your rebuttal based on whether you abbreviate their names. They'll just tell you to revise.  This would be a very easy revision.


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How do I cite this 3D teapot model in my BibTeX file?
I am working on some data transformations that work in finite dimensions. To help motivate the reader I would like a simple, but not too simple, example to show how the transformations work. A 3D teapot is available on Khan Academy that would suite the purpose nicely (one might even say it was my cup of tea, but I don't drink right out of the pot!). I see that it is the intellectual property of user Peter Collingridge under an Attribution 4.0 International (CC BY 4.0) license, so I do not see why I could not use it provided that I give credit.
What should go into my BibTeX entry within my *.bib file for something like this?

What I have put together so far:
@misc{
    title = {3D Teapot [Data Set]},
    howpublished = {https://www.khanacademy.org/computer-programming/3d-teapot/971436783?qa_expand_key=ag5zfmtoYW4tYWNhZGVteXJCCxIIVXNlckRhdGEiJXVzZXJfZW1haWxfa2V5X2subi5ibHVlc3RhckBnbWFpbC5jb20MCxIIRmVlZGJhY2sYmXUM},
    owner = {Peter Collingridge},
    note = {Accessed: 2022-02-21}
}

I found this @dataset entry type, which I will have to check if it is compatible with my TeX environment.

It is no different from citing any other online source, really. And there are plenty resources on the topic of citing online sources :) See if this helps, for one: https://academia.stackexchange.com/questions/151533/how-to-cite-a-github-repository-that-i-used-for-data-collection-research-paper/151557#151557. As for the format of the bibtex entry, that depends on the citation style. But as far as I understand, yours is not a technical question.


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When to submit to viXra (rather than arXiv or not at all)?
arxiv has the description:

arXiv is a free distribution service and an open-access archive for 2,146,943 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

viXra has the description:

An alternative archive of 39635 e-prints in Science, Mathematics & Other Scholarly Areas serving the whole scientific community

I have anecdotally heard that "viXra is a venue for crackpots to publish their bad ideas". I don't know if that is strictly true, but I was shown some highly speculative and low-quality papers that exemplify that there are low-quality submissions on viXra.
Even so, is there a use case for submitting to viXra?

To show effort, I have tried to brainstorm some possibilities and some countering points of view to using viXra.
Here are some speculations of use cases:

Failed simulations, experiments, or attempted proofs: something went wrong, and you cannot use the results. But you can describe what you did and the outcomes, and speculate on what went wrong. Maybe someone could learn from your mistakes.

Not a substantial contribution: you produce some statistics on an easily-collected data set showing an unsurprising result. Or similarly prove some mathematical results that are technically novel but would be considered obvious by professional mathematicians (e.g. found the derivative or integral of a function which didn't require much insight).

Course replication experiments: You're a student, and you've done an experiment following laboratory protocols provided by your lab instructor. If you had done this experiment 100 years ago it would have been ground-breaking research, but yours is just a modern replication. You've done an excellent job, it just isn't remotely new.

Bottom-of-the-ladder: No one else will accept your submission. Maybe you are a crackpot, or maybe you are not. But you've tried everything you were willing to try, and this is you sending out your message in a bottle.

Some counter attitudes:

The chances that the above provide value are low, so don't clutter the internet with them.
If you do something of value, put it somewhere people will notice. Otherwise don't bother.

Does this answer your question? What are the differences between viXra.org and arXiv.org?

In particular, this is a good answer: https://academia.stackexchange.com/a/105520/13240

I'd add to the counter attitudes that putting your work on vixra can harm your reputation, by associating you with a lot of cranks.


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How to find the work/application related to a paper?
I am doing my PhD research on AI. One paper I read was very interesting for my research, and I feel I should compare my result with theirs.
Datasets we use are different for testing and the only way to make the comparison is by using their application/library with my dataset. Therefore, I need to get the application/library they built in order to use it for comparison.
I searched for their work anywhere online but could not find it. How can I compare my method and theirs in that case? What shall I write in my paper in that case I cannot find their work?

To get the obvious question out of the way, have you tried contacting the authors of that paper?

@Anyon yes, there was no answer

If they didn't publish code with the paper and they don't respond to contact, you're out of luck. You could implement their algorithm based on their written methods.

Perhaps How should I proceed if the author of a paper doesn't reply to my query? could be useful. Also, it is often the case that the authors may be more responsive to emails from your advisor.


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Is it academically allowed to change authorship when resubmit and equal contribution?
We had a paper rejected where I was the first author. The second author and I almost had the same level of contribution to the paper.
Now we are resubmitting the paper to another journal. However, due to my personal business, I cannot work on this paper and its future revisions full-time, hence, we would like the second author to take most of the responsibilities. Consequently, the second author would have more contributions than myself and would take the first author position.
I would like to ask if this authorship change breaks the academic honesty/morality?

There is nothing wrong with changing the order of the authors in a resubmission of the paper if additional (intellectual) work is invested to get the paper to a publishable state, especially if the change is needed to reflect the changed authors' contributions.
What is seen as problematic is a change of the author list during a reviewing process or after submission -- this makes it look like that either the original or the new author list do not reflect the actual contributions of the authors, which is problematic in any case. As a consequence, during revisions of a reviewing process of a single paper, changing author order may look fishy. In certain circumstances, such as major revisions with substantially added content, they can still be done by explaining the change to the editor (and the reviewers), though.

There is nothing wrong with updating the authorship of a paper (or changing the order of authors) when revisions are undertaken where new authors add to the paper or existing authors make a larger contribution to the paper.  Since you are submitting to a new journal you can make this change without any explanation; if you were submitting back to the same journal then I would recommend explaining the change.


text:
Pattern of the question paper
To pursue a Ph.D. in Mathematics in India, one must clear the central entrance exams (written) like CSIR-NET, GATE, NBHM or institute specific exams such as ISI, CMI, TIFR first. After that, the students are eligible for an interview for the Ph.D. position.
In almost all the exams, the questions of different topics are jumbled up together. However, I believe if the questions are categorized (all questions of algebra at one place, all questions of analysis at one place, etc.), it is easier for students to score better. (Example of type 1 exam, Example of type 2 exam).
What is the philosophy behind setting a paper where the questions of all topics are mixed up? Is it just made this way to make it more difficult for the candidate to ace the exams or anything else?

You can always do the algebra questions first, then the analysis questions next, then linear algebra, .... Is there ant rule that says you must start from the first question, then the second one, sequentially?

@Nobody There is no rule, but it would be nice to have all at one place!

"However, I believe if the questions are categorized (all questions of algebra at one place, all questions of analysis at one place, etc.), it is easier for students to score better". You believe based on what?
The philosophy may as well be to help candidates, so they immediately realize that if one question is difficult or of a difficult (to the candidate's feeling) they do not get paralyzed and stuck by fear of failing. Vote to close

Personally I think the question is OK. People may have experience in or know literature about the construction of such tests. It's a valid concern and I can imagine useful answers to be given, even though I don't have one.


text:
Order of authors in the paper, Elsevier
I wrote a paper, and my supervisor is the corresponding author of the paper, but in the PDF of the manuscript the order of authors is different (not the text we wrote as the paper, the first page of the manuscript which is downloadable).  I am the second and my name listed after my supervisor's name. Also, I am listed as co_author.
How is the situation?

I'm not sure I understand. Are you listed twice?

No in the pdf we uploaded im listed first, but in my profile my supervisor's name listed first.  I dont know its because he is corresponding auther or really he listed him self first in the submission process ( not in the pdf)

What you write is confusing, “Im and listed after...” is not clear. Should be I’m for a start.

Possibly they take first and corresponding author to be the same. Forget, it it was fine that the supervisor is the corresponding author then all is all right.

Is this perhaps a journal in field with alphabetical ordering of authors (pure math, theoretical computer science)?

If you're unsure, you can double check with the editor, they should be able to clear it up quickly. Mistakes do happen with the names though, in one of my submissions, the editor switched the order of my first and last name. I wouldn't assume that your supervisor did this intentionally, just check with the editor (and then with your supervisor, depending on what the editor says).

I'd say check first with the advisor and then with the editor. If the advisor changed the order (for whatever reason) asking the editor is a little awkward.

Dissgree with it being awkward. If the advisor did change author without discussing with other authors then that is unethical. The editor can give definitive answer whereas an unethical advisor may twist the truth to exploit a student. Not saying its the case but I also know there's plenty of people like that.


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Should citations be included in funding applications
I am writing a funding application for the development of a scientific technology, should I include references to back up the most important aspects of my proposal? Is there a standard procedure for this?

Yes, include references. They serve a twofold purpose in your application:

They inform the reviewer about the state of the art in your field, and allow him to judge whether your project would advance it in a meaningful and cost-effective way.
It shows the reviewer that you know what you are doing. Nothing worse than a grant application for a project where the PI did not read the literature thoroughly and does not know that his exact question has already been thoroughly investigated.

The funding body you apply to may well have very clear-cut guidelines for your application. (Because applicants have a tendency to write up everything they know about the field they are excited about, and no reviewer wants to read a 200 page proposal.) These guidelines will very likely have a strict page limit and explicitly note whether references should be counted against that page limit or not, along with what citation style to use.
If there are no guidelines for references, use whatever is common in your field, e.g., in common journals or conferences. Use conventions that make reading your proposal easy for the reviewer.


text:
Get Information about NSF grant with grant number
Papers funded by NSF grants usually contain a phrase like "This research was supported by the National Science Foundation under Grants ENG-XXXXXX".
I wonder if it is possible to find some information about these grants with the grant numbers. I am interested in who applied for the grant, original proposal etc.
I tried to search on the NSF website with the specific grant number, but did not get any results.

https://www.nsf.gov/awardsearch/advancedSearch.jsp

Visit research.gov

Research Spending & Results gives the public, the scientific community, and Congress insight into federally funded research. Research Spending & Results provides information about how federal research dollars are being spent, what research is being performed, and how the outcomes of research are benefiting society as a whole. Anyone can easily access, search, and sort information in new ways through Research.gov. Currently, information is available for NSF and NASA awards.

Search the award data.

Thanks, as far as I understood, this site contains data from 2007 onwards. Is there any database for awards from the 80ties?

@arved - I suspect nobody has thought it worthwhile or cost effective to go back and add that information. The 80's were a long time ago, particularly with respect to putting things on the internet...

@arved Many older grants are in the NSF award search.

Often, you can find the relevant pages from the NSF by simply googling the grant number. That never failed for me, at least.

Is there any database for awards from the 80ties?

This is more difficult; you probably won't be able to find things on the web. Maybe you can check with your university's library to see if they have any (physical paper copy) books of historical NSF grants. I am often surprised by what physical books, journals, etc. they have on hand in storage somewhere at my university.


text:
Is there a special name for a contributed talk given longer time slot?
A conference symposium I'm attending has all contributed talks, no invited or keynote talks.  But in each session, one of the [contributed] talks is given a longer time slot than all the others (40 mins vs 20 mins).  Is there a special name for these types of talks?  How would one denote this on their CV (and should they)?

If the conference doesn't assign a special designation to the talk, I would not try to do so.

It might be called the "featured talk" for the session.

Why the  downvotes?

Haha, I was wondering the same about the downvotes.  Oh noes, what did I do wrong?!?!

I'm confident that the conference organizers are using some designated name for these talks among themselves. Ask them what term they use.


text:
Do graduate school admissions committees care about an official bachelors degree, or just the relevant coursework?
I am a second year undergraduate in in Math+CS interested in applying to some CS graduate programs (in the US).
Since I began my degree I purposefully put off taking a series of general education requirements with the intent of instead moving quickly through my main CS and Math coursework so that I could begin doing undergraduate research as soon as possible. If I continue this strategy then by the end of my third year I would have finished all the core coursework for both a Math and CS degree, along with a significant number of graduate courses in both departments. I also am actively working on some research projects which might lead to publishing as a first or second author in a relatively good journal, and some good recommendation letters.
Overall I feel like I could have a pretty competitive graduate application by next fall, except that I would not have the necessary general education requirements to be officially granted degrees by my university.
Would a graduate admissions committees be at all concerned that I did not officially complete my degree? Are there any reasons to hold out on applying until my fourth year (other than the possibility of taking more coursework, doing more research, etc.)?

Maybe they would be concerned that wouldn't officially complete your graduate degree, either?

@MadJack Right, I had not considered this. In my case, I am not quitting my current program because it is too hard or because I don't want to finish it. Rather I am skipping some formalities to get ahead and get to the interesting stuff (research) faster. I can obviously see an admission committee being concerned with the first scenario, but do you think they would also find the second scenario a red flag?

Yes, what I mean is graduate school has also it's own formalities, and one must hurdle through these as well if one wants to officially complete the degree.

In my experience they do care, and in the program where I was a graduate director not being close to completion of you current degree would get your application rejected. If you can't be bothered to satisfy the requirements for a your current degree program, why would a graduate committee have a reasonable expectation that you will complete their program?


text:
Statement of Purpose or Statement of History?
I am applying for graduate programs in Physics (at the US universities) for Fall 2018. I am writing my Statement of Purpose and I read a few successful SoPs before writing my own and it made me all confused. All of them talked all about what they had done and had only a few sentences here and there talking about what they liked or what was their purpose. In the end, they talked about what topics or research groups they would like to work with using just one paragraph. It is safe to say that more than 90% of each of the SoPs I have read talked about what they have done rather than talking about their purpose. So, I want to confirm whether it is the custom or they were not really good SoPs? I understand that stating only the purpose does no good and one must back it up by showing a corresponding background but I think a ratio of something like 60% background 40% purpose is the maximum I would like to lean towards the background. Is this a wise thing to do?

It really depends on the country. In the US you probably won't know precisely what you're going to end up researching, and you likely wouldn't be expected to. In the UK this would be similar, but you would be applying for a particular project, so you'd have to write a little bit of both. In Europe it would vary as well, although mostly be biased toward writing a bit more about your proposed project.

@lafemmecosmique Shouldn't the whole point of an SoP be to gauge how much does the applicant know what he wants to do or what he thinks he would end up doing? I mean my background is already there in my CV and my LoRs. Shouldn't the focus be on the ''purpose'' part in an SoP?


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Popular Science References in Statement of Purpose for Ph.D
I am currently in the process of writing my SoP for applications to PhD in Physics programs starting Fall 2018 (in the US schools). I am definitely writing about the content that I have studied rigorously as well as about the research projects that I have been involved in and so on. But I also want to involve something about a paragraph (not a specifically small one) about some of the colloquial talks and articles that I have read during my undergraduate years that have played a significant role in shaping my interests inside theoretical physics. I have been quite a YouTube buff and have watched a lot of semi-popular level talks and have been quite motivated by them in my interests. These talks have been very useful in making me aware of the current frontiers of research as well as in narrowing down my interests for good. Of course, these are not the only factors but these are among the non-negligible factors. So, I wanted to ask whether mentioning this part would be considered good or it would give my statement a non-serious and a childish tone. Or worse, might it look like I am confusing real physics with what is shown in the popular level talks?
Along with anyone interested or knowledgeable about this kind of a situation, those with a first-hand experience of looking at someone’s statements with such references or those with a first-hand experience of writing such a kind of statement are particularly requested to comment/respond.

The title suggests "Popular Science References" and your question suggests "semi-popular level [YouTube] talks," can you be more precise? You go on to mention "[t]hese talks have been very useful in making me aware of the current frontiers of research as well as in narrowing down my [research] interests," which suggests that these talks might be beyond "semi-popular." Are the talks aimed at undergraduates/postgraduates/researchers, rather than the general public (which is suggested by your use of popular/semi-popular)? If they are, then I think they are worth mentioning, albeit only in passing

@user2768 I apologize for the inconsistent use of words. But, in fact, I am not entirely sure what they should be called collectively as I believe the set of talks I had in mind were spanned on the spectrum. But I get what you are suggesting--I can consider briefly mentioning the true semi-popular talks or the talks more rigorous than those. Thanks!

To make a more concrete suggestion: if the talks were academic in nature or part of a lecture series, then they might be worth mentioning, perhaps along the lines of the following: I studied Prof. X's ABC e-course (mentioning why that is relevant to the PhD that you wish to pursue).

From my experience, telling the tale why you became so fascinated with one particular topic is to be kept to a minimum. It does not add any weight or edge to your SoP, other people will have their more or less interesting story. You can use maybe one or two sentences and I don't see any need to have a "not a specifically small" paragraph on why you became fascinated with a topic. It might sound harsh, but they will not care. You have to use the limited space in your SoP for other things. But that's another question/answer.
In short, I would avoid citing pop science to a very bare minimum, especially in a field as rigorous as physics. Unless you use this reference to show something you have achieved. For example, I read pop science X which inspired me to run experiment Y which has produced Z.

First of all, let me emphasize on the CV part. Because your statement of purpose is usually considered as a whole with your CV.
My personal preference is to list these things.
I divide my CV in half. In first half, I list all the academic-related things. Such as publications, reviewerships, academic awards etc.
The second part contains non-academic things about me. Such as my hobbies, life achievements, my educational YouTube videos about algorithms, and even my reputation in this very website!
This achieves two things:

If people do not care about my personal life, they can just not read that part.
By a tiny chance, they might find something interesting about me to put me a few inches ahead. It might be an answer I gave in Academia.SE, or some point I've mentioned in my YouTube video.

In your case, you might put another section entitled Slightly academic related. All in all, your CV is you in a nutshell. Thus, if you think that one has to know something, then you better put it in your CV.
As for the statement of purpose, after you clearly write your research plans and your interest area, if you think some of these activities support your purpose, then putting them usually shows your ambition. Of course, I would not suggest you to put any single thing, but you might mention them in case someone finds them interesting.
If your research related statements are strong enough, I would not think that the whole statement of purpose will be childish.

This is a partial answer, to supplement what @user4050 wrote.  As s/he explained, you probably should not use up valuable space in your essay for tangential content.
But I can think of a few possible exceptions:

The instructions ask you to talk about how your interest in your field began or evolved.
The instructions ask you to talk about Science Outreach (which is becoming a hot topic these days).
You yourself have a serious and abiding interest in Science Outreach.
You have a serious and abiding interest in Science Pedagogy, and believe that the right sort of youtube video fits integrally with the teaching of science.
You have made videos of the type you described, you're proud of them, and you want to continue this hobby while in grad school, and you have some way of explaining how this hobby connects integrally with your studies and your research.

I can offer some advice, but take it with a grain of salt. Firstly, I suggest that a decision of including such content into a SoP should be primarily driven by relevant expectations from schools you have decided to apply to (many schools likely even have guidelines on preparing SoP and other required or desired documents). Secondly, if the relevant expectations from SoP are flexible, I suggest you to have a section (instead of a paragraph) dedicated to explaining your motivation. IMO, it should include not only motivation specific to your chosen domain (theoretical physics), but also motivation to dive into science, in general. However, to prevent this from being interpreted as less serious / too lightweight, it is important to find and use relevant solid references. One example of such semi-popular, but solid and well-known, source is the famous talk by Dr. Richard W. Hamming "You and Your Research" (text of the talk is available here and relevant video of the talk - here). Thirdly, such semi-popular references ideally should be complemented by references to solid research papers (seminal and/or survey papers) on specific aspects of your research interests. Good luck!

I'm no expert, but your question gets at some very broad self-marketing considerations, so here's my thinking. If you're talking in your SoP about why you got interested in the first place or what motivated you to actually go into the field, I'd just make a brief reference to popular science reporting and science outreach sparking your interest. If there is a particular video or article, you could mention the specific topic it covered as an example of this outreach, but I wouldn't talk about the delivery format (especially if it was a video, unfortunately). Absolutely, if the speaker was a well-known scientist, you could say you were inspired by a talk they gave. It doesn't have to be a talk you heard in person, and probably these days, people would assume it was a video. But, to me, it's a little like the difference between getting some initial info from Wikipedia and actually citing it as a reference.


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Writing a short paper pointing to a mistake in a 2012 journal paper that got significant citations, while discussion with the author not successful
I've very convinced that an author made a serious error in the main theorem in one of her 2012 papers in Statistics and Computing, which is a reputed journal in machine learning. I contacted the author, and we did have a respectful conversation, in which she neither agreed nor disagreed with me, but didn't seem to know a mathematically fundamental step mistakenly used in the proof of the theorem. Now, since I'm convinced that this is indeed a serious error, what should be my next step?
Along this line, I followed this question, and ideally I wanted to collaborate with the author, who did very kindly give me half an hour to discuss in real time, but I understand that there's no hope for writing a corrected version of the paper with her, since she neither agreed not disagreed with me.
Now since I'm in the beginning phase of my research career, I'm thinking of leveraging my discovery into writing a paper that'd be along the line of "Notes on the paper X", which'll mostly focus on discussing why the theorem  and the proof is wrong. I do of course want to acknowledge the discussion with the author. How can I make this possible?
See the thing is: since the main theorem of the paper is wrong, it makes the subsequent experiments wrong as well, so I can't really do much to improve the results into something to make a brand new paper. However, I do want my contribution to the community (that catching the mistakes and explaining them why it's wrong with potential counterexamples) noted. This is the reason I want to publish my finding. Also I'm wondering even if I write to the editor, they acknowledge that it's a mistake, will they necessarily publish my notes in the same journal? Intuitive it seems no because it's just a correction (albeit to the main theorem), but yes, as this should be the appropriate choice, as this is the very journal the paper was published in. How should I go about it? Thank you!

The first thing I'd do is try to talk to another expert (an advisor maybe?) who can help make sure you're indeed correct in your analysis.

Sure I'm all up for that, but finding such an expert interested in another person's work seems a difficult task: I'm not part of a university at this moment but I did finish my PhD in a different area. So speaking with my PhD advisor or department people might not seem feasible.

Regarding your last paragraph: journals regularly publish corrigenda/errata, which are often short notes.  Normally these are written by the original authors, but they don't have to be.  In your situation, you could still try to make one written by both of you.  My suggestion is to write a polite draft, send it to the author and invite her to work with you in making a corrigendum.

@Kimball Thanks for the suggestion, and I'm glad to know that they do so. But do they publish the errata as separate paper(s)? I've already sent her a polite draft detailing the errors. But I'm not sure she went through that in great detail, as was apparent in our real-time meeting.

At least in math, errata are considered separate articles, and indexed as such in publication databases like MathSciNet.

If you are sure of your work, there is little reason not to write the paper and submit it. Cite the other work properly, of course, and make your case clear. If the editor of a journal doesn't reject it out of hand it will be passed to a couple of referees who will give their judgement on the work.
But you don't jeopardize your career by doing this. Your paper isn't public until it is published. But asking the editor first is probably a  mistake, since you can't develop your argument without writing the paper.
And, it isn't impossible that in writing it up formally you will find an error in your own work. Make the case. Submit it for publication if it is strong enough.

Thanks, that sounds like a good idea - will do so!

The problem is that though, the paper will say, "this statement is wrong as this is a counterexample". But what will it really establish? I mean, the real contribution will be (if I'm correct) that: people who didn't read the math thoroughly before, now will find a significant mistake. The paper will do just that - and not establish a new result. My concern is: is that enough to form a paper alone?

It is hard to say from a distance. But if the paper is widely cited and subsequent results are also wrong, it is important to put it out there. But a statement of what can be proven would be stronger, of course.

@Science Man indeed is a comment on paper x rather than a normal paper. Is the error in paper x a seed for future mistakes and propagating troubles? Or it is just cited but at the end no one uses that specific erroneous point? This would be the main criterion for taking a decision and proceed.

@ScienceMan That will depend on the particulars.  A paper that says "here's a counterexample to Theorem X" but fails to specify what the logical fault in the proof of Theorem X is may be a difficult pill to swallow, especially if no one can find a logical fault in the counterexample.  It could be years before a consensus develops and someone presents a solid enough argument for which of the theorem or counterexample is valid.  It wouldn't be unprecedented. There's a somewhat famous story with Voevodsky and how he came to favor computerized proof assistants with exactly this situation.


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I'm confused and frustrated by my postdoc mentor's stubbornness and not caring for my future at all. What should I do?
Background: I did PhD in pure math, then postdoc in medical imaging for 2 years. Because of funding running out, I started a postdoc in France in mesh processing since last 6 months. I'm somewhat proficient in Matlab, which is the only language I'm comfortable in so far. I want to work in R&D of the image processing/computer vision industry.
Facts:
1) It takes a solid 75 minutes each way from my house to my university, and initially we agreed on my showing up 3 times a week. However, sometimes I feel and am way more productive working from home. I tried to discuss this multiple times with my mentor, but he wouldn't listen: he says I've to come 3 times, since other team members might need me, which is NEVER the case, me being in my first year of mesh processing, even the PhD students probably know part of the subject better and I've never been asked a question.
2) My postdoc advisor knows from me that I'm looking for the above type of jobs in industry. Now, for industry purposes, I want to (and indeed started to) learn NumPy and Scikit-learn to perform machine learning. However, he's not familiar with these libraries, and wants me to look at a certain Matlab package he sent me to perform ML, and got offended because I didn't yet. Now, from talking to industry people in imaging/vision, I know Matlab is rarely used compared to Python. I tried to discuss this so that I could use Python to solve his problems, and being better it at the same time. He said "Learn Python on your own time. Since you're not very strong in coding, I can't give you couple of weeks to learn a new language".
3) My postdoc mentor has a specialty in mesh processing in computer graphics, and most of his papers are about mesh geometry. I get the feeling that he doesn't know machine learning(ML) very well. Now, for my future, and also for our project that involves ML, I want to learn certain algorithms from the scratch, so that it serves me the dual purpose of solving his problems and also strengthens my ML knowledge. He, on the other hand, wants to get fast results, and just wants me to use the above matlab package he sent me, because that's what HE is more comfortable in.
4) My postdoc is initially for a year only. So basically, I've to either find a job by the end, or get results so that I can renew my postdoc. I did give him some partial results in the first 6 months that didn't involve ML. Now, learning more ML (I know some ML) is taking time, and he's angry about it, accusing me of not progressing fast enough.  So in essence I want to learn the ML algorithms I use from the scratch, but it's not HIS interest, so he'd not just support that. He also said he'd not renew my funding if I don't give him significantly more result.
My mentor has a permanent position, where I don't. I thought postdoc mentors should somehow look after their mentees, but I feel he really doesn't care. Also his stubbornness of making me doing things his way really makes me helpless, and frustrated about my own future. He imposes his stubbornness, since he's not very good in Python, and that he doesn't know ML from scratch.
I've tried to discuss these issues in person, but he literally blew me off. I'm confused what to do. I invite your opinion.

I post as a comment, as I don't have an answer to your question (what you should do). It looks like like the problem here is that you see a postdoc as a preparation for a career in industry. Hence, the mechanics of the postdoc are broken. If you were seeking a career in academia, your main goal at the postdoc stage would be improving your CV by publications and in this case your goals would perfectly coincide with those of your hosting professor (who seeks to list some outputs in the report). Instead you prioritize improving your skills for the industry; why would a host be happy with that?

@greenb He should be happy because I'm not prioritizing my skills without paying any attention to his problems. I'm learning new skills to solve his problem that I'm working on, not mine.
Also, it's not that I'm planning to apply for a very different industry, say quant. I'm working on mesh processing in academia using ML, and I'm applying for R&D where they also use ML for image processing-very related. I don't think a true goal of academia should be to ignore the practical problems and software used in solving those problems. People should be open minded to other languages/techniques.

@greenb Regarding "your main goal at the postdoc stage would be improving your CV by publications...". Again, it's not that I'm not working on his problems. Of course I'm, but using different tools that also bolster my industrial CV. Yes, I agree that it slows down the process a bit, but I don't think a mentor should be upset because of that, specially when he works in an applied area.

The way you describe your relationship, it sounds like manager and subordinate employee. Regardless of anything else - if that's the dynamic, it would not be surprising he expects you to follow his (effective) orders, and not very interested in promoting your independent future.
I know that many research groups have this dynamic; so it's not as though it can be easily rectified in favor of something else. Still, that's not how a post-doc is supposed to be like - and that depends on him, but also on you.
The way it's supposed to be (*) is:

You're an independent researcher on your own right. Even when you're part of a group, you're supposed to have your own agenda regarding what you'd like to study.
The post-doctoral researcher position is not the same as a 'senior research assistant' or a 'research support engineer' position. In those, the researchers' needs and desires define what you occupy yourself with, almost solely.
As a post-doctoral research you should already have developed, or should now be developing, independent relationships with others in the research community, outside of your group, and the collaboration with them - direct, not just through your research group.
(the part you like) A senior researcher should help his post-docs with their personal development as researchers - but not in a close follow-my-lead-closely relationship as s/he might have his/her MsC/PhD candidates.

So, he's not upholding his side of what's supposed to happen, but frankly - I believe you might not be, either, and what's more, it seems you had not clearly agreed beforehand on a reasonable modus operandi between you two; so you're expecting one thing to happen and he's expecting another.
The bottom-line suggestion is to try to arrange to have a "state of our relationship and mutual-expections-alignment" talk with him that's independent of any specific single issue or grievance any of you might have.
It's hard to make other concrete suggestion without information about your research group, your field, your departmental/university politics etc.
(*) - Again, some would argue that post-docs as plain subordinate grunts with a brain is a valid arrangement. I disagree.

"Still, that's not how a post-doc is supposed to be like": I disagree on this. What a post-doc is supposed to be like depends a lot on the specific system and on the source of funding. See also this answer.

"Still, that's not how a post-doc is supposed to be": I agree with this 100% despite @MassimoOrtolano's correct observation that that's not always how it actually is.

@einpoklum: that's exactly how I feel: as if he's my senior manager and I'm his subordinate employee. Now, I've done postdocs both in France and the US, and never my mentors treated me with such disrespect! Indeed all my previous postdoctoral mentors were pretty happy with me, and gave me strong recommendations. With them, I was given a project, and was asked to solve it, with occasional discussions, that's about it.

@einpoklum:  They of course suggested me to read certain stuffs, but nobody accused me if I took an alternate approach. It's true though, right now, I'm designing my research more than ever to suit my application needs, but yet, the way my mentor is acting is really unjustified.

You two are butting heads.  As you will not be working with this person very long, you might want to gracefully give in on the bulk of these things.  For example, you might consider trying some of the following ideas:

find ways to be able to be more productive when you're at the lab
make the commute more palatable (for example, use public transportation time to be productive or sleep, or if driving, listen to podcasts and call it "stress reduction time")
use some weekend time and some of your work-from-home time to work with Python
pick one ML algorithm to study at a time (weekend and work-from-home days), but use the library you were given in order to hit the productivity targets


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What makes a good physics/engineering poster?
A more general form of this question has been answered here for example, but I want to know what makes a good poster presentation in physics and/or engineering conferences.
Obviously the poster must be visually appealing as discussed in various posts here, but I have seen cases where the most stunning posters (looks really good and well-written) did not win poster prizes when judged by professors at the conferences. Can you give reasons as to why this happens? Are there some special conditions or requirements in physics/engineering for such presentations?

You say the "most stunning posters" did not win.. So, who chose these "most stunning posters"? If that is your opinion, you are entitled to it, but the judges made a collective decision based on their criteria not yours... The answers given seem relevant to all subjects...

The academics and organizers usually choose the winning poster. At one conference, many participants I spoke to noted that there was one or more "stunning posters" - these ultimately didn't win any prizes. My question is: what criteria (other than the poster itself) do academics look for when judging a poster? I should note that I have mostly attended conferences (with poster presentations) in the UK and EU.

“The judges made a collective decision based on their criteria” - untill you ask the judges exactly what they were looking for at each and every conference which could / will be different at each then you won’t know - anything else is just a guess

I don't believe that this is actually any different for physics and engineering than it is in general for scientific posters.

Some might suggest that a "good" poster and a "prize winning" poster, while not orthogonal, are not necessarily well correlated.


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How to go about finding a Thesis advisor for Master degree
I'm currently enrolled as a graduate student pursuing my masters. I'm wanting to eventually pursue a PhD, but in order to do that, I believe I need to do a thesis for my graduate degree, and for that I need a thesis adviser. What would be the best way of going about this?
There is a long list of professors, and it would take a long time to go through all of them to see what they are currently researching. I thought someone might have some experience with this and be able to offer some thoughts.

Please indicate more of the setting you are in, otherwise your problem description may not be well comprehensible, and suggested answers may not be helpful. To illustrate this: In the standard setting in my place, you would not just "need to do a thesis [because you want] to eventually pursue a PhD", you'd have to write a thesis to get the degree you are currently pursuing in the first place. Likewise, "finding a Thesis advisor" would simply consist of checking all the offers for open Master thesis topics posted on university employees' doors.

Often departments will have a few specialisations that most (if not all) of the academic staff will fall under in some way. If you can find out what they are, then that's a good start. Then it's a matter of talking! Often one academic will have some idea what others are working on, so you can narrow it down quite quickly that way. Then it's just a matter of deciding what projects appeal to you the most.

The list of professors can't be that long to just see their general research interests. This is just something you'll have to do. I've looked through all the profs at various schools with large departments and it probably took a max of 30 minutes.
But just reading about them isn't enough. If you can get your list down to 2-4 potential advisors then you can (A) ask for a meeting with each or (B) try to take a course with some of them.
If you have a general idea of what you want to study, it should be relatively easy to find a few that you are interested in. The harder part is convincing them to take you on :)

It's important that advising a student is usually something that both the student and the professor have to agree to.  You may want to work with professor X, but he/she might be too busy or simply not be interested in working with you.  In MS programs with thesis and non-thesis options, it is frequently the case that there are two many MS students wanting to do a thesis and not enough faculty to advise them.  In such a situation it can be hard to find a willing advisor.

Do as Austin Henley's answer says, but make sure to explain you want to go on to a PhD (and be prepared to be asked why you want to pursue a PhD, and a master's for that matter!). There might very well be paths to a PhD without a master's, or after a master's without thesis. Which ones do exist (or even might be created just for you, as an exceptionally bright student) is very much a local matter, which we know nothing about.


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Citing a source that is yet to be published in a conference proceedings
I wanted to ask how IEEE cites a paper that is submitted to a conference, approved BUT is yet to be published.
For example, Author A gives a talk entitled Title B in Conference C which is supposed to take place 5 months from now. But the article is accepted already by the conference organizers.
I tried googling it but I was confused on how the answers came about.

Just cite it as you would normally, but add a note stating it will be presented in the future.
Just make sure you get an advance copy or a final draft to have some solid basis for any claims you do on it. You might want to state this in your note in the bibliography. Also make sure to update the reference as needed.


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Is it ethical to reconstruct a dataset without permission?
I have reached out to a researcher about using their dataset from a paper published 20+ years ago, but they have not responded to my email. There are a variety of reasons why they might have not responded, ranging from being retired, data is destroyed, not trusting unsolicited emails, coveting the data's future research potential, and probably a myriad of other possibilities.
Because their study

used a constrained scale (Likert [1,5]),
used a relatively small sample size,
used a small number of questions,
reported multiple statistics giving location, scale, and correlations,
and model fit statistics,

it is possible for me to recreate a dataset that is identical to the original.
The purpose of creating this dataset would be to provide a hypothetical analysis with updated modeling and statistical methods to compare if the conclusions would be similar with new methods. The original dataset would have been preferred, but a reconstruction would provide an equivalent result for the newer methods.
The measurements are survey responses, so on the face of it one might be concerned about privacy. However, the sampled population is large and the survey questions are not specific, so actually identifying individuals would not be possible from this reconstruction.
Assuming that I am transparent with what I am doing in my reporting of the data and analysis, is it ethical to reconstruct a dataset without explicitly obtaining permission?

What makes you even concerned that it could be unethical? That's what's routinely done in replication studies. One way that science progresses it by testing existing hypotheses and models on new, yet-unseen data from reality.

(To be clear, what you have in mind here is technically not "reconstructing dataset X" but "constructing a new dataset, based on the methodical setup of X".)

@lighthousekeeper I think it is reconstructing the dataset. OP is using the statistics that were reported and not just using the same methodology.

@gib The part that made me concerned is the use of Likert scales - these are normally used for measuring subjective impressions (of human respondents). But I now see that OP says they can create an identical dataset, which is then a bit confusing for me, I guess.

Do you actually mean "identical" or "identical in summary statistics"?

"able to reconstruct their dataset" this probably makes a number of assumptions about the original researchers' methods w.r.t. rounding, handling of outliers, other data-wrangling stuff that they may or may not have mentioned in their report.  You should just be aware that, due to all of this indirection, your analysis is now subject to such limitations of THEIR study, and that you should discuss this in your report.

@AzorAhai-him- it seems as though the OP means to imply that "identical" and "identical in summary statistics" are the same thing for this particular study.  If the sample is of size, say, 15, and at least 15 summary statistics are reported, then solving the set of summary-statistic equations for the original data is generally possible.

@Him Yup, that's why I asked them to clarify, as it's not always possible.

Honestly, this whole approach sounds concerning: using a small sample size study's summary statistics (that's 6 s- in a row!) to then use some "newer methods" on it without having access to underlying distributions... Ouch!

You can even reconstruct an image and publish it,;  it is ethical. Recreating a dataset is absolutely fine too.

Yes. This is published work, so you are free to do whatever you want with it, modulo the usual caveats. The fact that you are "reconstructing their dataset" is irrelevant; the key point is that you are building on their prior work using only published, publicly-available information. As you mention, you'll have to be transparent in both directions: give credit for the parts you take but be sure not be imply that you have any "inside information" about the original study.

I agree, but first I think OP should tell the researcher that they are able to reconstruct the dataset and what they are planning to do with it. The researcher might reply when told this, and might even give the original data, which would be useful as a check, or some other useful information.

I would also mention the methodology/steps/code you followed to reconstruct the data set (maybe in apendix) and explicitly mention the reconstruction.

Talk to your IRB.
The original participants in the study may or may not have had some expectation of privacy w.r.t. their data.  This existed as a real, official agreement between the original researchers and the participants, and likely went through some kind of IRB approval process.  The authors almost certainly never even considered the possibility that the data could be perfectly reconstructed from the summary stats they provided, and anticipated that not providing the raw data was sufficient to keep the participants' individual responses anonymized.  Possibly, the participants were explicitly told that the raw data would not be publicly available!  You say that determining identities is likely not possible, but this probably depends on various things.  Often, small studies are convenience-sampled, and the participants are easily identifiable as the students taking Psych2053 at PolyTech U under professor Study Author the semester before the study was published.
Anyhow, all of this is something you should probably bring up with your own IRB.  I'm sure they'll be fine with it if you take the usual precautions of not making the data publicly available, or what have you.  Still, it would suck to have the fact that you didn't get approval to come back to haunt you.

I can appreciate this answer, but would also be a little bit concerned that IRBs tend to be extremely conservative. The OP did say explicitly "the sampled population is large" (so the small sample is presumably a small sample of respondents from a large surveyed population). If the OP is really worried they could analyze the reconstructed data set and only publish summaries/results of the analysis (i.e., leaving it up to others who want the original data to reconstruct it for themselves). In any case, the information is publicly available now ...

Unfortunately I feel like any expectation of "privacy" the participants may have had is rendered moot once the information has been already published with their informed consent ("informed" to an extent reasonable at the time). In fact I feel that such a post-facto restriction would not only hinder the advancement of science, but potentially create a perverse incentive for future unscrupulous researchers to obtain poorly-anonymized datasets in a similar manner as the original authors, precisely to make it more difficult for future researchers to question their results...

From a standpoint of personal ethics, I think it's certainly kind of the OP to ponder this, and perhaps refrain from publishing if the data appears sensitive in his own eyes, but otherwise, from the standpoint of professional ethics, given the above, I don't see why an IRB should have any input in this.

Let's make some reasonable assumptions. Personal identities have been replaced in original publication. Original publication and deriving works use aggregates. OP wants to reconstruct original data. The only identities OP can use are the published pseudonyms. OP is surely not stealing the original un-pseudonymized dataset from a safe deposit! So, there seems to be no way for OP to breach the identities of the study participants. But there are two questions: Is it ethical towards the original study participants? And: Is it ethical towards the original paper authors?

"OP is surely not stealing the original un-pseudonymized dataset" this is fair, but the fact remains that the OP has no idea what the original study participants were told would happen to this data.  It's also not entirely clear from the description how identifying the data are.  Certainly this qualifies as some level of de-anonymization over and above providing summary statistics.  How un-anonymous is un-anonymous enough?  This is precisely the sort of thing that IRBs are for!

@BenBolker "In any case, the information is publicly available now"  For that matter, everything you've ever done online including passwords and such are publicly available.  They got sent out over the public airwaves!  Of course, teasing this info out of the data that you sent is a difficult computational problem, but the info was there.  If I manage to solve this difficult computational problem and now have access to your passwords and usernames, what is my ethical duty w.r.t. that info?  Certainly the attitude "well, it's public now!" doesn't seem correct.

I don't see how ethics is involved here, especially as the data set is 20 years old.
How can you be sure that any result (positive or not) is caused by the new method and is not an artifact of your potentially insufficient data set reconstruction?
Why do you cannot create a new data set, use the old methods, check that the result confirms the old paper, and then try modern methods? And publish your new data set. I think that would be the better, more scientific approach.


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Am I allowed to directly fix a typo about experiment results during camera-ready?
I have recently received acceptance notification from a top-tier AI conference. When I prepare my camera-ready version I realised that I wrongly pasted the variance for the cell before to the current cell.
E.g.
                         Dataset1         Dataset2
Model1          60±0.03         82±0.35
Model2          62±0.04         84±0.04
Where the variance for Model2 on Dataset2 should be 0.32 but I wrongly paste it to 0.04 unintentionally. This wrong variance does not change my conclusion, but I want to be accurate about the experiment results. I would like to fix this before submitting camera-ready version but not sure if this is allowed.
Should I email programme committee to explain this or I could simply make the change and submit the new version (worrying for this change involves experiment results)?

I'm confused, isn't the whole point of reviewing things for a camera-ready version to give a final check like this?

Yes, that is why I want to change it. What makes me to ask is that can I simply make the change and submit, or I should explain to the committee given this involves experimental results.

Is there not a place to explain changes with your resubmission?

Yes. Editorial changes are always possible as long as they do not affect the interpretation of things. So if the number you previously had was crucial to the interpretation of the experiment -- for example, if you stated that the temperature at which a material becomes superconducting was 280K -- then you probably shouldn't change it when you realized that it should really have been 28.0K because that would fundamentally change the message. On the other hand, if this was just an otherwise unimportant number in a table, then you can change typos, grammar errors, etc.
Of course, this sort of thing should not have happened, and it would be worth your time to walk once around the block and think about how it happened and how you should change your work practices to make sure it doesn't happen again.


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Can I directly cite a picture from Medium?
I'm writing my thesis and there is one picture from medium I want to use https://shreyusp.medium.com/multi-task-learning-f3ba67eaa836

It is Figure 1: Hard and Soft Parameter Sharing.
Can I directly use the graph by citing its web address? Or is it better to create my own graph?

You can always say "inspired by %url%", but here is nothing hard that could not be done from scratch in a reasonable time.

Note that the fact the figure is published in a Medium post rather than an academic paper doesn't really affect the answer, although perhaps the publisher's degree of understanding. Also related: Is it necessary to obtain permissions for copying figures from published articles in your proposal/dissertation?

I think you are better off citing it (and the article in which it appears). A cursory search didn't turn up any licensing information, so you have to assume that the image, like the article, is copyrighted by the author(s) or by medium.
I don't know enough about the field, but there is also the issue as to whether this information is "common knowledge" or not. I'm guessing not, which means that without a citation you are open to charges of plagiarism if you recreate it or use it without citation.
If it isn't common knowledge then I suggest that you ask the author for permission to reuse it (with citation) in your thesis. You can then just include the image. I'm pretty sure the author would allow it, if they hold the copyright. It is a bit more complicated if medium has copyright, in which case the author might need to work with them to allow it.
A difficulty with web citation, however, is that web pages disappear. You can include a "date last accessed" in a citation, or you can see if the Wayback Machine holds a permanent version.
But, keep in mind that both copyright and plagiarism are issues here and they are not the same thing.
And note that I'm using fairly strict interpretations of the applicable rules, which is certainly appropriate for a thesis.


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Is it polite to ask my mentor to recommend me to Professors she knows in the graduate school?
I am currently applying for a doctoral program. One thing I keep considering is if should I politely ask my mentor who will write me the ref letter to recommend me to professors that she knows in those schools that I will be applying to? I am having a good relationship with my mentor and she knows me well and I think she had a good impression of me. The reason I am considering this is because she was an alumni of two of my target schools and also used to be a faculty at one of my other target school. Could someone gives me some suggestion about whether I should politely ask her? I am a little afraid of making her feel like I am trying to rely on 'connection' but I also feel like if I don't ask and she would be willing to, I might feel very regretful for not asking.

Yes it is polite and it is actually proper to ask a mentor for this in most cultures, I suspect. Some professors might be reluctant to do this, but I think not very many.
But what it actually gets you depends on the admissions system at the universities you apply to. In some, say in the US, it might have little effect on admissions but it places (and fields) in which professors hire their own students it would be much more valuable.
But in any case, having been introduced will be a small (at least) advantage if you wind up at one of these schools and it is a good idea to go meet the people you were introduced to. You might even be able to pick up a new mentor at the new place.

Thank you so much! so should I just directly ask " I am particularly interested in xxx areas at xxx schools and I don't know if you know any professors at these schools are doing research in these areas, is it possible that you could recommend me to them so I could contact them to express my interests later? " Do you think this is appropriate enough?

I recommended a student to the school where I got my Ph.D. and the student was accepted into their doctoral program. Of course, it didn't hurt that the student had an outstanding undergraduate record.