Recommendations for maths courses choice to study AI I study computer science at the Charles University. The undergraduate study (baccalaureate) in "general computer science" programme provides several focus areas, which are followed by corresponding programmes in the graduate study (master). I chose to go for mathematical linguistics in the undergraduate and artificial intelligence (Probably with machine learning focus, but I'm not sure yet.) in the graduate study.

My problem is: There are some mandatory maths courses and some optional. Some of the optional ones are recommended, but not for specific focus areas. So I wanted to ask for some advice on which areas of mathematics are recommended for this area.

Most courses are split into multiple semesters and completing only the first few is usually mandatory, continuation of the other ones is optional. So far (first year of undergraduate), I have completed these mandatory courses:

Mathematical analysis I, II
Discrete mathematics (Continues as Combinatorics and Graphs.)
Combinatorics and Graphs I
Linear algebra I, II (No more courses available, only applications in computer graphics etc.)

Mandatory courses for next years:

Probability and Statistics
Propositional & Predicate logic
Algebra I

List of some available optional courses:

Mathematical analysis III
Combinatorics and Graphs II
Set theory
Numerical mathematics
Algebra II

Mathematical analysis III

Probably overkill, but it depends on the actual content. You will need some multivariate analysis (partial derivatives, Jacobians, Hessians), but I suspect it's already in the first two courses.

  Combinatorics and Graphs II

Maybe not specifically for AI, but in general it should be a useful course for a computer scientist. Again, it may depend on the actual program; if it is set up as a very abstract course then it may be overkill.

  Set theory

Not so useful. Probably more abstract stuff that you'll ever need as a computer scientist.

  Numerical mathematics

Very useful. Matrix computations, stability and the floating point model, basic root-finding and optimization algorithms... That's all stuff that you will probably need.
 I'm surprised that it is not mandatory for a computer scientist (but I work in that area, so maybe I'm biased).

  Algebra II

Not so useful. Probably more abstract stuff that you'll ever need as a computer scientist.

Other courses: look out for a course on optimization (it might also fall in the "numerical mathematics" category). Neural networks are based on optimization/fitting algorithms.


Asking professor to provide feedback on academic articles? I sent an email to a potential supervisor whether I fit for him, he said yes, then I replied whether he ll be able to provide feedback on a paper I am writing on a topic of his interest, he didn't reply, was that a good move from my side?

Reviewing a scientific article for publication is time consuming. By asking a prospective supervisor to review your scientific article, you were asking him to take hours out of his or her busy day. The journal you are submitting to will have reviewers who are volunteers and will review your article.


How did Russia produce a comparable COVID vaccine with inferior resources? It seems that the Sputnik V is slightly less effective than the most effective vaccines (Moderna and Pfizer/BioNTech), but has some advantages as well (in particular it can be stored at higher temperatures, and it is cheaper), such that it is not clearly inferior.
How did Russia produce a vaccine of comparable quality to its competitors? I would've thought that money and talent are the two biggest drivers of quality research, yet Russia seems to be well behind its competitors on both these metrics:

Russian R&D spending is way less than the US/Germany, as well as Belgium on a per capita basis; and
Russian universities do poorly on international rankings, implying that the best brains do not work in Russia

Only other thing I can think of is luck, but I intuitively dislike luck as an explanation since it is applicable to many things.
I'm asking this on Academia.SE because it's more a question about research process than about politics.

Ranking or spending money is only secondary metrics how to evaluate and compare performance e.g. among universities or countries or continents.
But I think fundamental is society, it's history and its attitude. I had opportunity to live and experience research in "western" country institute for couple years. This experience may apply to general research as well as to hunting vaccine competition:

Oh your idea is great, let try and start
we give you some time and administrative support to enhance the idea
big pharma as well as small startups are close to university labs, so it's not hard to do quick experiments, trials, prototypes. Some networking events, conferences are common.
you're good in what you're doing, we're among the best in the world

Now back in "central & eastern" european country usually underestimated. I now experience this attitude:

Oh your idea is interesting, but somebody (from western countries) already works on this issue
administrative support? Write proposal by yourself and we will only evaluate if the 'quota' was not reached so you won't compete with "more preferred" teams.
usually big pharma or small startups are not close to university labs - if yes, that is "conflict of interest" and you "try to sell knowledge to nasty rich companies"
there are better teams in the world in the topic doing what you do.
you did unappropriate public critical comments about our dean, prime minister, president, ..., so forget for support

So as a result I can guess that in countries and societies from first group ("western") there are e.g. 20-50 teams trying different approach despite their political or other context. 2-5 succeed, the others that fail - they are not usually prosecuted but gain valuable experience. Some earn money and pay taxes, some become rich and invest again to western business and all society in general profits.
I guess that in countries and societies from second group ("eastern") only 2-5 teams try to make  vaccine, other were disqualified by any point mentioned above. If 1 succeed despite condition - it is big success! Congratulation to Sputnik V! They earn money, probably pay taxes, some become rich and invest where? Do they rather to emigrate to west, not to be imprisoned like Navalnyj or Khodorkovskij? What about the other teams that do not succeed - are they prosecuted?
So in case of western approach - the luck is just statistical success rate.


CRediT contribution statement: Pros and cons of including non-author contributors? An increasing number of journals require a CRediT – Contributor Roles Taxonomy statement for, among other things, "Enabling visibility and recognition of the different contributions of researchers, particularly in multi-authored works – across all aspects of the research being reported (including data curation, statistical analysis, etc.)."
Here's an example provided by Elsevier:

Zhang San: Conceptualization, Methodology, Software. Priya Singh: Data
curation, Writing- Original draft preparation. Wang Wu: Visualization,
Investigation. Jan Jansen: Supervision. Ajay Kumar: Software,
Validation: Sun Qi: Writing- Reviewing and Editing.

However, the ICMJE recommends that authorship be based on fulfilling all of 4 criteria (including 1) contributions to the conception/acquisition/analysis, and 2) critical contribution to the actual paper). Most journals (in my field, psychology) follow this recommendation regarding authorship. Based on these criteria, none of the "authors" above warrants authorship. Yet, they all contributed to the paper in critical, but different (even complementary) ways, and should be acknowledged meaningfully.
A common scenario is that students providing critical contributions and substantial time commitments don't end up coauthors because they do not fulfill all four criteria (e.g., Conceptualization, Methodology, Investigation, and Project administration, but not Writing of the paper, which could be written by another, graduate student perhaps). It feels weird to acknowledge the minor contribution of one author (e.g., minor part of analysis, minor contribution to writing of paper) but not the student who did all the legwork. Or even the student who ended up spending dozens of hours collecting a large proportion of the data (Investigation).
Given that the ICMJE recommendations are not expected to change anytime soon, I wonder whether the CRediT contribution statement could also be used as a convenient tool to formally acknowledge non-author contributors, since right now, their contributions are often buried in obscured, unstandardized (even meaningless) acknowledgments sections. This way, non-author contributors meta-data could eventually be picked up and indexed quantitatively on different platforms (ORCID?).
Question
What would be the pros and cons of using the CRediT contribution statement to acknowledge non-author contributors more formally and transparently? Could it coexist with the current coauthor system or can only one of the two survive? Should you do it even if journals don't expect it?

However, the ICMJE recommends that authorship be based on fulfilling all of 4 criteria (including 1) contributions to the conception/acquisition/analysis, and 2) critical contribution to the actual paper). Most journals (to my knowledge) follow this recommendation regarding authorship.

I do not think that most journals do follow the ICMJE recommendation regarding authorship, at least outside the medical field. To take the journal Nature as an example

Each author is expected to have made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work; or have drafted the work or substantively revised it

To take another example away from the medical field, the American Physical Society say that

Authorship should be limited to those who have made a significant contribution to the concept, design, execution or interpretation of the research study. All those who have made significant contributions should be offered the opportunity to be listed as authors. Other individuals who have contributed to the study should be acknowledged, but not identified as authors. The sources of financial support for the project should be disclosed.

Again this is much less stringent than the ICMJE guidelines.


What happens to the reviews that people write for journal articles after they're sent back to the author? Are they almost always kept confidential? Or is there protocol for sharing them?

In my experience, the contents of the comments of other referee reports are only made indirectly available. Since the authors are normally expected to provide a response to the reviews, the relevant criticisms and comments of the other referees are typically mentioned or discussed in that document. Outside of that, however, there's often little direct sharing of referee reports. None of the eight or nine journals for which I've reviewed (physics, chemistry, chemical engineering) have allowed me to see directly the reviews submitted by the other referees.

At any rate, the results are almost always kept confidential, unless it is an "open" referee process by design. (There are a few journals now that make the refereeing process a part of the publication record for a given paper; an example is The Cryosphere.)


Is it a good idea to write to some researchers for some help on my own research? I am a Ph.D student and I am currently working on my research project. In this moment I am stuck with it because I suspect there is some error in the algorithm, but I can't recognize it. Unfortunately my supervisor cannot help me at this point. However, I know that in my city there is a good professor who is working on the field, so I was thinking to write to him and ask for a meeting, where I could explain my issue.

Do you think is it a good idea? Would it be better if I ask to my supervisor to intermediate for me? How this kind of email are considered by professors?

I would ask your professor first. Not to arrange a meeting but rather for advice. Maybe he thinks it would be best if you write yourself, maybe he thinks it would be best for him to establish a contact.

Next, remember that professors don't have infinite time, so be properly prepared. You claim that there is an error in the algorithm. So work it out exactly, have multiple examples ready to show that for these examples, the algorithm produces the wrong result, have proofs ready to show what the right result is, etc. You might not need all of it, but it is always better to be able to say "yes, I have it right here" instead of "well, I didn't think of that, maybe I will look at it...". On the other hand, don't send everything in your first email, if the prof thinks he has 20 pages to read to understand your problem, he will most likely not.

All in all, it is not a bad idea. Worst thing that could happen is that the professor has no time for you or doesn't answer your email, then you are at the same point you are right now. So go get some advice from your supervisor on how to best contact him, what to prepare in advance, etc. and write him a message.


Fine to put as an appendix to my statement of purpose the paragraph explaining the gaps in my transcripts? I am applying to doctoral programs in the US, and, because I have two breaks in my studies as what shown in my transcripts, I want to find somewhere to explain these.

But I am concerned with that if I simply put this short paragraph explaining my breaks in studies somewhere in my application package as a supplemental material, then it may be ignored (would it?)! Thus I decided to include it in my statement of purpose as an appendix.

The number of the words in my statement of purpose is not a problem, for even when the paragraph is included, my statement of purpose still contains less than 800 words.

So would such deed of mine have any chances to annoy any member of the committees?

This would be fine. One fundamental point of the personal statement is to allow you to comment on anything unusual in your records (gaps in education, a semester when you got sick and had low grades, etc.)

In general, you can format the statement of purpose however you like. Using clear signposts (such as section headings) can make it much easier to follow.

Remember that the person reading your personal statement probably has a large stack of them to read, so making their job easier can only help you.


Can I ask letter of recommendation to my undergraduate thesis supervisor for PhD in other lab I am doing my bachelor's thesis (4th-year 1st semester) in one of the top 5 research group in my field in the world (but not a renowned university). I want to do direct PhD (also called Masters track PhD) after this and my supervisor is extremely impressed by my work and wants to convince me to do it in his group.

He also offered me one more funded semester (4th-year 2nd semester) of research internship which I have accepted.

But, I have friends in some other labs and also, I want to explore some other options like doing a PhD in the top research group as well as a renowned university. Hence, I have decided to apply for direct PhD to some other labs too (top 5 and also university wise top 5 universities). Is it okay to ask my bachelor's thesis supervisor to write a recommendation letter for me? How can I ask him to write a strong letter without disappointing him?

Yes, it's perfectly fine. He should be encouraging you to seek other opportunities as well as staying in his own lab. It take a very jealous and vindictive person to refuse to write a reference for a good student applying to other places. If he is such a person, it would not be a good idea to stay working with him anyway.


What do we know about working times of great living scientists? I am looking for two kinds of data about the great scientists of today,

Their average daily routine of work. Like how many hours and when?
Their average length of time of being able to think continuously.

I vaguely remember seeing a post by Terence Tao about this - like he mentioned that it takes him some x-minutes to focus on a question when he begins working. Though I don't remember if he mentioned any specific length of time for which he can concentrate at a stretch. [..sadly I can't find that post...]

I am more looking for examples among mathematicians and theoretical physicists though other theory fields might also look more or less the same.

This popular book http://www.amazon.com/Daily-Rituals-How-Artists-Work/dp/0307273601 contains precisely descriptions of working routines of various creative people, including several scientists and mathematicians.


What do the middle digits of course codes represent? Take the course code PHYS 3054 or PHYS 354. The physics department doesn't offer 54 courses at the 300 or 3000 level.

I imagine some universities subscribe to a set of common best practices for course numbering. So I suspect that there might be an answer that applies to the numbering systems of a number of institutions.

I suspect it really depends on the university. But in my university, it represents the subfield in the department within which the course is offered.

For example (I'm in electrical engineering), EE X1X might be courses on power systems engineering, EE X2X on communication networks, EE X3X on  signal processing, EE X4X on electronics...

But in my department at least, there are enough misnumbered courses (for "historical reasons") to confound anyone who doesn't know it and is looking for a pattern.


Should I be suspicious of a conference that invites me, a recently admitted graduate student, to be an invited speaker? I'm a recently-admitted student to graduate program, albeit possessing a considerable roster of research papers in known conferences and journals.

I'd just, recently, received an email from the chairman of this conference to deliver a technical presentation, as an invited speaker in the target field.

Typically, invited speakers are the well-known heroes in their field. I am, noticeably, ambitious enough to taste such experience, but this offer's made me suspicious about the credibility of the conference, to the bone.

Should I accept the offer?!

It seems it is a junk conference, which will not bring you anything, but waits for your money!

Don't go, it is a waste of time, you will get nothing good from it, since no one really involved at a high level in your field will come.

It is not unusual for those kind of conferences to invite "anyone" as an invited speaker.


Number of recommendation letters? If a department places no limit to the number of recommendation letters, how many are appropriate?

Are 5 OK? Are 7 too many?

Of course this depends on how strong the letters are - but let's assume that all of them are equally strong.

Go with three strong LORs like everyone else and call it good.  No one needs five and seven is ridiculous.


Several questions about Master Applications I'm a last year student of Mathematics (and Physics) in Spain and I'm going to apply to some masters degree programmes in pure math in Europe this month and I have a couple of questions:

In one of the universities I intend to apply they say that they are expecting good marks, about 7.5/10 . My marks are about 7.45 at the moment but I have 6 subjects to do this term. I'm seriously expecting to get good grades in those last subjects of my degree. Two of them are the thesis, which I have already done and have really good critics. So if everything goes as expected I could go over 7.5. The thing is that the deadline is in two months so I won't be able to show those results.

Should I talk about this in my application letter? In that case, what should I say? I'm planning to send my thesis in the application to make them "forget" about the GPA a little. If my thesis is good enough could this help?

I'm simultaneously doing a degree in Math and another in Physics. The amount of work obviously affected my perfomance. Should I stress in the letter the two degrees thing? My thesis in the Physics University is about Entropy in mathematical physics should I include it too in the application?
I know that in American Universities they tend to appreciate if you have done some non-academic activities. I've been working as a jazz musician intensely since I started university. I received some grants and I've played in some national events. Should I omit this in my CV? Is this considered irrelevant in Europe? Maybe in some countries more than others?

Where does that kind of information usually go in your application? In the CV or in the letter?

Thanks a lot for your time.

Send them the facts, if available partial grades. Do not go speculating on your future grades, it should be enough to list future classes. Do not swamp them with stuff they probably aren't qualified to digest (last draft of your thesis-in-progress). Do concentrate on getting strong letters of recommendation.

Committees which look over applicants normally aren't staffed with specialists in the area to which applications come in, they get lots of applications to process, but also know that some of them won't be able to provide everything asked for for a variety of reasons. Explain the reasons, give firm dates for completing missing data, provide an alternative where it isn't available (unofficial/partial transcripts instead of official, complete ones).


Avoiding conferences: Potential effects on an academic career and mitigation strategies The following question is triggered by reading this recent question as well as by a recent case of an organizing committee member approaching me with invitation to present at a well-known (at least, within my discipline of information systems and a larger management sciences field) conference.

Unfortunately, I had to politely decline his kind invitation and an exciting opportunity for academic research career building and networking, especially considering that I am a beginning researcher. The reason for why I had to decline that promising invitation is twofold:

1) at this time, I'm a non-affiliated (independent) researcher with no financial support for research activities, including attending conferences - needless to say that I simply cannot afford to attend them on my own (but, even, if I would be, say, a postdoctoral researcher with some research budget, as far as I know, funds for attending conferences or similar events are quite limited);

2) my current life circumstances are not too favorable in terms of traveling (though, it is possible); moreover, I tend to agree with the "time lost" point, mentioned in this nice answer (though, I realize that it is a matter of assessing and balancing between time and effort spent on preparation for presenting at a conference and a potential academic and career value of a prospective event).

Considering all the above-mentioned points and circumstances, my questions are as follows:

Is it possible to build a good research academic career, avoiding publishing for (and, thus, presenting at) conferences and, instead, focusing at disseminating research artifacts via journal publications (in addition to working papers, industry articles, workshops, etc.)?

To what extent, if any, it would be damaging to a researcher, especially in early career, to use the strategy above and what are some potential mitigation strategic and tactical measures other than attending (and presenting at) conferences?

Note: My questions above imply conferences only, as workshops or similar smaller events seem to be more affordable and, sometimes, even, free to attend and/or to present at.

The primary argument against your strategy arises when you go up for promotion: if senior people in your field can't really "tie" you to your work—in other words, if you're someone who has published some really good papers, but are otherwise "invisible" in the community, it will be hard to write the positive letters of reference needed for a successful tenure case.

However, that is not to say that the strategy of focusing on disseminating research is not important—indeed, the two strategies need to go hand-in-hand! So I would argue that networking will become more critical once you have independent work of your own to share.


Does my supervisor want me to do my Ph.D. with him or elsewhere? I am currently doing my master's under the supervision of an assistant professor. He's brilliant, professional and an amazing mentor. He is supportive but at the same time knows when and how to be tough on me enough to challenge me intellectually and push me to get out of my comfort zone. For all these reasons, he would be the perfect supervisor for my Ph.D. The only problem is that he doesn't work on the same topic as me (and doesn't really have much experience with it either) and seeing that it's a new and tricky topic, I need someone experienced in this particular area.

I spoke to him several times about my plans for my Ph.D. and mentioned that I planned on applying to several major universities and that I was looking for supervisors working on my field of interest. He would keep bringing up the Ph.D. programme at his departement and would tell me that I could work with him and also someone else from another university (co-supervision). I said it could be a good idea, but of course, I was still considering the Ph.D. programmes at other universities (which, I think is normal, I'm only keeping my options open). Of course, he knew that I could enroll in better programmes elsewhere, but he still asked me to stay, more than once (which is flattering since I respect and admire him). The Phd programme he's suggesting is the best option for me ONLY in terms of funding, because it has a special offer for foreign students paying extra fees (which he also knows...).

Now, I recently had a meeting with him and I mentioned that I wanted to do an internship in one of the universities I'm interested in. He said "It's a good idea and if you like the experience, you can decide to stay there for a Ph.D.". That was one hell of a slap in my face... He basically told me "Hey, I changed my mind, you're not a worthwhile student, finish your master's, then you're out". So at the end of our meeting, I decided to be honest and asked "okay, so if I understand correctly, you no longer want me to stay here for my Ph.D.?", to which he answered "No, I do. But I want you to explore your options. I don't want you to stay just because you think it's your only option but because you believe it's the RIGHT option for you."

So now I'm confused. Does he want me to stay or does he want to get rid of me?

As Peter said in his comment, ask him.

However, having said that, and based on what you have said, it is very clear that he is not 'kicking you out' at all - on the contrary, he is demonstrating a very positive and constructive approach - by telling you that you have to pursue what is best for you.

Having said that, you need to consider a key question:

What is/are your goal(s) after you complete your research?

The professor is, as you say not an expert in the field you are interested in, and what he is suggesting is that, as this is the case then the internship may lead to opportunities that are more in line for your plans.

He is also seemingly suggesting is to pursue the internship and then decide where and what you want to study for your PhD.

Ultimately, the decision is yours to make - he is helping you to help yourself in this regards.

But, a piece of advice, do not assume to know the intentions of anyone - take his advice on face value and in the spirit that it has been given.


How to list a series of related experiences in CV Problem

I am applying for Ph.D. in electrical engineering. Since the first few deadlines are coming, I am making final revisions to my CV.

There are two related questions

I have a rather long (about 15 months) research experience that yield several preprints and a thesis. Is it fine to list all of them under one entry (see below). The issue is that the items (a, b, c...) become too many (8 in my case).
Or maybe I need to split them base on milestones (based on preprints and thesis results).

  My Awesome Research Topic

  a
  b

I have taken two projects-based courses, where the professors talk about details about each particular algorithm and we need to do projects which use the algorithms. The same question re-emerges, do I split these experiences project by project or maybe organize under one common entry?
If the latter is preferred, what should be the entry called, maybe something like "xxx Project Series"?

Appreciate any input.

The issue is that the items (a, b, c...) become too many (8 in my case). Or maybe I need to split them base on milestones (based on preprints and thesis results).

Perhaps have a single list entry per publication. (Each list entry can highlight several points.)

  I have taken two projects-based courses, where the professors talk about details about each particular algorithm and we need to do projects which use the algorithms. The same question re-emerges, do I split these [two projects-based courses] project by project or maybe organize under one common entry? If the latter is preferred, what should be the entry called, maybe something like "xxx Project Series"?

You could list all the courses you've taken. (Under the title 201X-201Y, Degree classification, subject, university, country, for instance.) You only need to discuss those with particular relevance, e.g., related to your PhD field. It seems unlikely that you'd need to discuss particular algorithms, unless they are in the field of your PhD and you are interested in pursuing them further.


Recommendation letters for "good enough" students I'm a math professor. I get asked to write a number of recommendation letters to graduate schools where my honest view of the candidate is "this student would fall somewhere in the bottom 25-50% of their student body. I expect there will be dozens of applicants of similar quality and I have no  reason to favor this one except that I have a good personal relationship with him or her."

Logically, this candidate deserves to go as much as any of the dozen similar people in the pool, but I feel that a letter which said the above would be a real disservice to them. Should I refuse to write them?  Describe their accomplishments and pointedly ignore that (if my estimates are right) they don't particularly make them stand out?

I've only been a student, so take this with a grain of salt.

Be honest to them about their abilities and your perception of them before you write a letter for them. Grad school is not a small commitment. See my answer here also, for an answer to a related question. An excerpt which I feel is very relevant:

  Be very honest. You have information that they don't have that will
  be useful for them. I would rather you tell them what you know and have
  them make the decision for themselves, rather than let them keep doing
  what they're doing and seeing them fail.


Copyright in academic software in the UK I work on statistical data analysis in neuroscience at a university, and to that end regularly develop small pieces of software. Most of that software I also publish on GitHub under the GNU General Public License. This implies that I claim and retain copyright.

I used to work in Germany, where in my (possibly mistaken?) understanding of "Wissenschaftsfreiheit" (academic freedom) this was a correct procedure. I now started to work at a UK university and stumbled across a passage in their Intellectual Property Policy:

  Scholarly Works

  a) The University waives its rights in the copyright
  in scholarly works produced solely in the furtherance of an academic
  career. This includes books, articles in journals, papers for
  conferences, study notes, original literary, dramatic, musical or
  artistic works, sound recordings, films, broadcasts, and typographical
  arrangements, multimedia works, photographs, and drawings, provided
  the material does not form part of a course or teaching materials for
  the University, and has not been commissioned by the University.

  b) The University does not waive its rights in the intellectual property
  in any underlying materials on which the scholarly work is based,
  including software, data, databases, designs and patentable
  inventions.

(emphasis mine)

If I understand paragraph (b) correctly, I cannot continue to publish code under the GPL, because the copyright of the software isn't mine to begin with. The same holds for data from neuroscience experiments, and one might argue that it holds for experimental designs. This does not just seem to prohibit my personal practice, but also to stand in the way of current efforts towards Open Science (open source, open data).

My questions:

1) Is this policy (b) correct under UK intellectual property law as it pertains to academia?

2) Is such a policy usual at UK universities? If yes, how do academics publishing software usually deal with it?

3) Are there organisations in the UK which could help to convince the university to change the policy? (Open Science advocacy groups)

Many academics in CS publish their software and sometimes even their data, blissfully ignoring whether they are allowed to do so in their institution or not. It's unlikely to cause any trouble because institutions usually don't care too much: nobody will ever check, unless there's a potential commercial opportunity at play.

However my understanding is that IP rights for any outcome produced in the course of academic work [edited] might be shared between the institution and the author, depending on the institution/country (but IANAL of course). This doesn't mean that the institution forbids academics to publish their software/data, actually it's even very unlikely that the institution would oppose publishing open-source software, but the proper way to do this would be to ask the IP/innovation office for permission (afaik most institutions have one nowadays).

In my research centre there is an official process that we are supposed to follow whenever we want to make something publicly available. It's a simple software disclosure form where the author indicates what the software does and what kind of license they want to apply to it. The form is supposed to be reviewed by an IP officer who in my experience always validates the request.  I've done it a few times myself: this additional administrative step is a bit annoying but it's not such a big effort.


Publishing someone else's thesis work without their consent Finished my MRes recently. My supervisor has told me that their ex-PhD student (graduated a year and a half ago) had some results in their thesis that they hadn't published. He asked me to complete some additional lab work and tweak a draft paper the student had put together, then I could be looking at getting a lead author position.
It sounded great initially, but I was a bit curious about the situation with the old PhD student and asked one of the post-docs (who is connected to this work). They explained the ex-PhD student was working on the paper after they graduated, but after some personal situation (unsure what but sounded serious) they basically vanished and were uncontactable.
I was a bit uneasy about this. I asked my supervisor and whilst they said the PhD didn't confirm they were happy to have someone else write their paper they didn't respond to emails saying that the supervisor was planning this. So from my supervisor's perspective this is all above board.
For extra info I looked up the university's policy and it says that the copyright for the thesis, and all of the data described, is owned by the PhD student.
Could writing this paper potentially get me in major trouble? Wanting a career in research and a paper would be good but this feels like this could easily go bad given the universities position on IP ownership and it using the work carried out by the PhD student.

I think in this case, the easiest solution would be to publish your paper with a reference to that other student's thesis (or unpublished work).


Sign application cover letter with "PhD" or not? For an application cover letter, is it better to sign it with just my name, or with "Ph.D." after my name?

What I am not sure of is that at the beginning of the letter, I do state when and where I got my PhD from. For reference, I am applying for positions in mathematics.

In the U.S. mathematics departments I'm familiar with, writing "Ph.D." after your name would not be disastrous, but it would be a bad idea.  It can look insecure, like you are worried readers will assume you don't have a Ph.D. if you don't remind them frequently, or pompous, like you feel having a Ph.D. is an important distinction that must be emphasized, and I see no upside to balance the risk of appearing insecure or pompous.

To clarify, I don't think merely listing "Ph.D." after your name would undermine an otherwise great application.  Nobody is going to take it that seriously.  However, it can be tricky to get the tone right in academic job applications, and some applicants inadvertently write things that could be read as insecure or pompous.  (Indeed, it's natural to feel insecure, and it's easy to come across as pompous if you try too hard to convince the reader that you'd make a great hire.)  The danger is that the reader might piece together several small things into an overall negative impression, maybe even subconsciously.  From this perspective, it's safest to eliminate issues you can identify, even if they wouldn't be decisive by themselves, just in case they might reinforce other things you're unaware of.

Note that conventions for the post-nominal use of "Ph.D." may vary between countries or even universities, as well as between fields.  This is a matter of culture, and you'll need to figure out what the culture is like where you are applying.


Can online recording of work area at home be made a mandatory criterion for passing exams midway through a course? Right now with the COVID-19 pandemic in Canada I believe most Ontario universities and colleges have their classes online, and my university decided to do that as well. With this in mind, many of our final exams are now being taken online with a camera and microphone recording, a lockdown browser to make sure you cannot access the web, and a proctor watching you over the internet. Before the exam begins, you must do a 360 environment scan of your entire workspace (your entire room, table with nothing on top, your wall and ceiling, etc). Recently my prof made an announcement saying that if a student did not do an environment scan properly, did not have their eye on the screen the entire time, or as long as they felt that a student is cheating, they can reject and invalidate the exam without any proof. Out of curiosity, is this actually allowed?

Another thing that was ridiculous about these online exams is that on the exam information document, it said “if you do not wish to be recorded, you should not take this course.” But this decision of everything going online was made after 3/4th of the term and some profs decided to have online exams a week before the exam weeks, so why do we have to do an online exam when we never had chosen for it to be online? Can I interpret this as "either do the exams online or drop the course, and we will not refund you any tuition"?

I really felt uncomfortable showing my room to people I don’t know, and I think that it violated my privacy. (I live in an off campus residence and my room is the only place where I can make it like an “exam hall”). Is there a place I can complain about this, and will they actually listen?

Universities around the world are trying very hard right now to find ways to balance students’ rights to privacy and dignity with difficult practical questions concerning the transition to remote teaching and testing.

Regarding testing, the reality is that cheating is a common occurrence in many places even in normal times when testing is done in the physical presence of and under the supervision of the instructor. There is little doubt that many students will take advantage of a remote testing environment in order to cheat, making the problem potentially much worse. This hurts honest students, hurts the university’s reputation, and devalues grades as a signal containing meaningful information. So, to put it very mildly, it is to everyone’s benefit that cheating be prevented to the extent possible.

All those things considered, if the choice is between a small intrusion on your privacy and closing down the university or cancelling all tests and grades, I think it’s clear that these sorts of anti-cheating measures are simply the best we can do at this moment in time, and you just have to accept this indignity as a necessary (and hopefully temporary) evil.

You can complain, but unless your complaint is accompanied by some solution to the remote testing problem that is so ingenious and innovative that it will make photographing your room unnecessary and prevent cheating at the same time, I wouldn’t expect your complaint to particularly impress anyone. Sorry, I don’t mean to sound harsh but that’s just the way it is.

Anyway, you have my sympathy. Keep in mind your professors are also stressed out and are also called on to do things many of them are uncomfortable with during this difficult time.

Edit: after thinking some more about this issue, I think a much bigger problem with these testing restrictions is that they seem to prohibit students from using the bathroom during the exam. This strikes me as a much bigger deal than the privacy intrusion, as it conflicts with basic human physiological needs, and raises significant issues of fairness and equity (as certain populations of students will find it much harder to comply with such a constraint than others). So if you are thinking of complaining, I would recommend making this the focus of your complaint rather than the privacy intrusion. It wouldn’t necessarily lead to the cancellation of the 360 degree scan requirement, but I can see a decent chance that the professor and/or university might reconsider some of the other somewhat draconian restrictions, as well as their general approach to the whole remote testing issue.

As for who to complain to, you should go through the usual channels for complaints within your institution, whatever those are (the professor, department chair, college, ombudsperson, student union, etc).

Edit 2:

To address a few of the objections to what I wrote that were raised in the comments:

The privacy intrusion is not “small”: perhaps; it depends on your frame of reference, and in ordinary times I’d totally agree. But my point is that these aren’t ordinary times, and standards for what constitutes an acceptable level of privacy intrusion are changing out of necessity. So when I say “small” I really mean “as small as can practically be achieved while still allowing the professor to do their work at a level of effectiveness the professor considers acceptable.”
It’s not clear that the professor was required to use this method of testing. Other professors are doing things differently. I never said the professor is guided by university rules. It’s possible each professor only receives general guidance from their university and has to decide for themselves about specific rules for remote testing. As long as their decision is generally reasonable, the fact that other professors made different decisions is a very weak argument. Although a bit of consistency is a desirable thing, there is no rule that all professors must handle all situations in an identical manner.
Your argument is premised on the assumption that this method of testing can be proved to be the only effective solution to the assessment problem. Please provide proof that this is so. It’s not premised on that assumption at all. There isn’t a scientifically proven, ideal method of testing. Professors have to make real-life decisions about real-life situations and do the best they can based on their intuition and experience. They don’t all have to agree on the best way of doing something, and don’t need to have a rigorous scientific basis for any decision they make. Sometimes they even make wrong decisions. There is room to debate and question each decision, but just saying a decision is illegitimate because the person making it can’t scientifically prove that it’s the best decision is not a valid argument.
I am outraged! So am I. This situation sucks! But instead of complaining, offer workable solutions. Believe it or not, professors also do not want to see anyone’s bedroom, and would be happy to switch to an alternative system if you can simply show them one and convince them that it satisfies the need to maintain a minimum level of integrity and effectiveness in assessing students’ knowledge. Professors are not evil people trying to oppress students. They are just trying to get a job done to the best of their abilities under difficult circumstances.


How to see citation contexts of all the papers that cite a paper? Given a paper, I'm looking for a quick way to see the citation contexts of papers that cite that paper, to gauge both the direction and intensity of sentiment towards the original paper and help me decide what to read first. The need this would address of mine is somewhat related to this question but specifically I want the citation contexts.

Since a few tools allow you to get the 'cited by' list after searching for a paper, eg. Google Scholar and Semantic Scholar, and the former actually lets you search within the citing articles, a natural next step seems to me to see the citation contexts in the summary of the search results. Is there any feature to toggle this? Or another tool that does it (whilst still being a critical platform where lots of papers will exist/have been indexed on it).

Ideas appreciated. Thanks!

From my experience, I think ResearchGate is the only platform currently offering exactly that. Wherever there is a paper fully available in its database being cited by another fully available paper, it shows an excerpt of the citation. Example below:

"... The number of cases where these approximations are used is vast. For instance, among many, 1[2][3][4][5][6][7][8] for the single- or few-mode approximation, or, e.g., [9][10][11][12][13] for the usage of 1+1D cavities. While simplifying the problem, some- times the rationale for these simplifications remains to be justified, above all in relativistic regimes. ..."

Reference: Interaction of a moving two-level atom with a single-mode quantized cavity field

Citing: [6] Relativity and quantum optics: accelerated atoms in optical cavities

The above was copied from the platform's citation display of a random reference.

I believe this is an interesting and powerful feature, however it would rely on everyone having a ResearchGate profile plus all references uploaded to the platform. And I do not see that happening any time soon.

Hope that helps? Good luck.


Where can I pay professional researchers online to verify my results and answer my questions? I am looking for professional help to verify some results I am working on and maintaining in a write-up. However, I can't get anyone for free since I was forced to leave my old university, Case Western Reserve, (due to disagreements) and I don't know if I can find an online program that assists undergraduates in their research (I should have graduated my senior year with a bachelor's degree but am technically a freshman. I have studied rigorously up to differential equations; It's complicated). Moreover, professors are busy and would most likely ignore my requests no matter how much money I offer.
Therefore, is there a way to pay for professional research help? How can I receive feedback on what I am working on?
Details: My field is mathematics. I think the work may be complicated enough that graduate students won't be able to rigorously answer everything. I need someone with a Ph.D. on the level of professors.
(Technically, I am working on developing a finitely additive measure and sum that takes the average of functions defined on countably additive measure zero sets. I am looking to verify if my measure and average on a function gives in fact what I am looking for. For reference, the link to my pdf is here).

The harsh answer: You probably can't. At least, unless you are somehow quite wealthy, and if that was the case, I suppose you could simply pay for enrollment at another university. Let me try and clarify a bit.
As a researcher I get many requests from people who want me to look at their particular problem. This ranges from

Fellow researchers who want to discuss - I most often oblige (at least if I have time, and their request is interesting or relevant).
Students who I don't know in advance, who wants guidance - I help if their question is well researched and not too polemically phrased.
Students from my own institution, not under my supervision - I always help, as this is my job.
Amateurs who have invented the a new method or theory for something, and wants it checked - I rarely do more than skim it.
etc. etc. etc.

You are in the last category. If you are to convince me that I should prioritize your request over the others, then I should be immediately convinced that your idea is really something special. My field is not mathematics, so I can't tell here. But judging from comments from professional mathematicians, neither can they. The second option you mention is money, and this is where I think you need to be fairly rich. If a purely monetary argument should convince me to push you to the top of the stack, you would need to pay me the equivalent of my going rate when doing freelance work, around 200 €/hour.
My best bet is to either:

Try and get re-enrolled into a university. There people get paid to answer your questions.
Try and find someone who would be really interested in your specific problem, and write them.
Undo whatever you did to get banned at math stackexchange, and try again there. Being nice gets you a long way, being polemic and insisting that only a professor can answer your question, will get you few friends.


Is it a good or bad idea to list declined fellowships (for a PhD program) on one's curriculum vitae? E.g. as shown in the example here.

  2011—Centennial Fellowship, Princeton University Department of Atmospheric and Oceanic Sciences  (accepted)
  2011—Top Student Award, University of Washington (declined)
  2011—Program in Climate Change Fellowship, University of Washington (declined)
  2011—Faculty Fellowship, Columbia University (declined)
  2011—Charney Prize, Massachusetts Institute of Technology (declined)
  2011—Regents Fellowship, Scripps Institution of Oceanography (declined)
  2011—Chair’s Award, Stanford University Department of Earth and Environmental System Science (declined)

Bad idea. If you turn down an award (or an acceptance to a univeristy, etc), you don't get to reap the benefits of that award.

No one cares about the universities you could have gone to or the fellowship programs you could have worked for, they care about what you have actually done and that is all you should include on your CV/resume. Period.

To me, the resume linked to above reads "I had no one else edit or evaluate my resume before I posted it online."


How formal should a recommendation be in the US? I am a lecturer in a European university. A student from my department asked me to write a recommendation for a program somewhere in the US that he wants to attend.

I have read the horror stories about American recommendation letters, where apparently "He is not only quick at learning and good at solving complicated problems, but also with a logical and creative mind that enables him to raise some insightful views. I was also deeply impressed with his diligence and outstanding communication ability, compared with my other students." is considered lukewarm(!) and grounds for rejecting the applicant.

I have found a few sample recommendation letters and advice from different universities/people around the internet and I've used them as inspiration to spruce up what I had initially written. I have also asked colleagues, but understandably they mostly write letter for other European universities, where such superlative language would usually be reserved for sarcasm or toadying.

However, one thing that is rarely consistent is how formal the letter should be.  More precisely:

How should I start the letter? "Dear colleagues"? "To whom it may concern"? "Esteemed organizers"? Similarly, how to end it? "(Best) regards"? "Sincerely yours"?
How to refer to the applicant in the letter? "Jane"? "Jane Doe"? "Mrs. Doe"?

I would rather not penalize the student because I do not understand foreign cultural norms.

Formality is the wrong parameter to worry about.  Write at whatever level of formality you are most comfortable writing to your target audience.  (But err on the side of formality, unless you know your reader personally.)

The parameter you should worry about is credibility.  Your readers don't just want to know that you think highly of the student; we want to know why you think highly of the student, and why we should trust your judgement.

  He is not only quick at learning and good at solving complicated problems, but also with a logical and creative mind that enables him to raise some insightful views. I was also deeply impressed with his diligence and outstanding communication ability, compared with my other students

This is not a terrible recommendation letter because the praise is insufficiently strong; it's a terrible recommendation letter because the praise is vague.  Which complicated problems?  How do you know he has a logical and creative mind?   What insightful views?  How did he show diligence?  How and where did he demonstrate his outstanding communication ability?  (And do you mean speaking, writing, or both?)  And why should we trust your judgement at all?  Be specific.

Without these details, this letter looks like flowery boilerplate that could be applied to anyone.  The letter says nothing specific about the student, which makes me think the writer knows nothing specific about the student.  Moreover, the letter says nothing about the writer's expertise, strongly suggesting that he expects to be trusted merely because he's old and tenured.

In short: Show, don't tell.

The "horror stories" page you link to gives similar advice.  (Did you actually read it?)


Ways of developing non-core skills during PhD studies? Working on a cross-disciplinary project, in an increasingly cross-disciplinary field, I often find myself wondering whether or not I am developing skills in multiple different areas of my work. I intend this question to be as general as possible, but for the sake of clarity I will give my case as an example:

I have a MSc in applied mathematics, and have been working with biomedical research for three years now. Being branded as a bioinformatician I feel very appreciated on one hand, and absolutely disregarded on the other. In many cases I am expected to learn more of the biology and develop an understanding of "the real science" while all the tools and analysis should just work. I mean many of the seniors have absolutely no idea of the time and effort it takes to develop at software tool, maintain and further develop it. It appears as all that is given once and for all in the engineering school, after all programming is just programming... (please note the sarcasm here)

Be as it may, I have been trying to improve my knowledge and experience in the technical aspects of the work on my own; learning new algorithms, new languages, new tools... It is surprisingly hard to get accustomed to these when you are not in the university anymore. Consequently, I have given up on learning Maven for my Java projects, or Perl for speeding up my day-to-day scripting.

So my question is; what are good methods for learning or developing techniques that are not immediately in the scope of your project but is still very relevant in your development as a scientist?

Follow up question: am I mistaken in thinking that I should develop a broad set of skills in order to become as efficient and competent as possible?

My goodness, but this is a tough one.  We all learn and maintain our skills in our own unique way.  Especially in industry or when operating independently, so it's difficult to say what would work for you.  I'm in a similar situation except that I'm a developer first and I've been tasked with 'just making security happen'.   Much like with you and bio-med, there is an awful lot that is changing in the landscape of info-sec and staying sharp in both domains is a real challenge.

That said; your mileage will vary but here are some techniques that work for me.

Find overlapping areas:
When I started to move toward developing a new aspect of my skill set I looked for areas where the old and the new overlap.  Luckily for me; this was a pretty easy thing to do with infosec and software development.  The benefit here is that it allows you to leverage your existing skills in a new area.  If can can find areas where you can turn two jobs into one you can ease your way into it, rather than just sitting down one weekend and deciding "I'm going to learn X.".

Sit down one weekend and decide "I'm going to learn X.":
Sometimes there is no easy overlap to ease your way into a new tech or topic. In those cases I've found that a couple of days in power study mode can be a real benefit.  Strap on the headphones, coffee up it that's your thing, and just read the literature & work problems.  If it's tech then do tutorials.  If it's topic then vacuum up as much as you can.

Find mentors: Maybe you can't find the all encompassing guru of everything you want to do, but that's OK.  Someday that guru will be you.  In the meantime find people with expertise in your subject areas to help you fill in the gaps.

Keep it fun:
If at all possible and whenever possible. If you hate what you're doing then you're not going to do it well. At least that has been my experience.

Don't give in to the temptation to 'dumb it down':  You're a smart person.  You've taken the time to learn a new skill. You've actually read the materials.  You work hard to develop and maintain a system that crosses a number of subject matter domains.  Don't let people off easy when they ask hard questions; give them hard answers.  My approach is to ask them 'do you want an answer or a response?'  If all they want is a response that's OK. I give them a short and succinct response.  If they want an answer then I do my best to provide the most exhaustive and thorough explanation of what I do, that I can.  When I work hard to learn a new skill I don't need to show it off but I won't let it be taken for granted either.

Well, that's what I've got. All the best to you in your endeavors. If you ever need Java help feel free to grab me on chat and I'll get you an email address.


Replying to professor who said that I can join his research group as a PhD student next year In search of a Ph.D. position, I emailed a professor and he replied me that I should recontact him next year as he does not have any available position right now. Also, he said that it will be too late for me as I will be wasting one year. Actually, deep inside, I do want to take a break of one year to spend some time with my family as I lived away from home for two years of my Master's study.

My question is, is it okay to tell professor that you want to take a long break before starting your Ph.D.? In other words, what is a proper reply to the professor who is saying that I should contact him next year?

He hasn't made any commitment to take you on next year. I would simply write to thank him for his consideration and say that you will re-apply if circumstances at the time permit. You don't need to say more now.

Saying too much might be a mistake. But thanks should be expressed, certainly. Use the year to find another position or use it profitably otherwise. Reexamine your options if you are still available in the future.


What can a student do regarding conflicting meeting times for desired courses? As it currently stands, my department offers two necessary courses at the same time every spring. One of them I must take before I am a senior, and another I must take before I graduate (I will soon be starting my third year). So I must take the former next spring, and I will have to wait until the spring of my senior year to take the latter. The problem is that the latter is a course that is very relevant to what I wish to study in graduate school. I'd hate to apply to graduate schools before having taken such a necessary course in my desired field (I feel it would weaken my application), and at the same time, it bars me from taking more advanced courses in the field before I graduate.

Of course, these courses are always taught at the same time by established professors, so I'd hate to ask the department to change all of that for one student. Is there any course of action I can take? Or would this be regarded negatively?

I hope that this is not off topic (merely because I am an undergraduate), as perhaps the desired rescheduling of course times is something that would be relevant to graduate students as well.

This is an issue that can also impact graduate students, so I do think it's appropriate for this group.

Unfortunately, once a class hour schedule has been published for the next semester, and particularly after students have started to register for classes, it is usually not easy for a department to change class times.  Thus it's important to deal with such a scheduling conflict as soon as possible and preferably before students start registering for the semester in question.

I would suggest that you send a polite email to the person in the department responsible for course scheduling (perhaps there is an undergraduate coordinator who does this, or perhaps the department chair supervises the scheduling) and explain your situation and desire to not have these two courses scheduled at conflicting times.  This is a reasonable request to make, but don't be surprised if your request doesn't result in a schedule change- in many departments courses are scheduled to satisfy the desires of the faculty rather than the needs of students.


Why would a grad school reduce fees to a trivial amount rather than reduce stipend? When I applied to grad schools I was accepted with full tuition wavers and stipends to all but one. That one gave me a good stipend and reduced tuition to a trivial fee ($300). They say you can even defer the fee until payday.

In general, why might a university not reduce stipend amount by the fees rather than charge the trivial fee?

It seems bureaucractically harder to have a fee.

Actually, it’s almost certainly easier bureaucratically to simply charge the fee and increase the amount of money they pay you. You have to think of this from the point of view of budgeting. Each of the different fees you pay gets deposited in a different department or organization’s budget. Let’s say it’s a fee to the gym. The gym has a responsibility to manage its own budget in the university, and it pays for its services out of those fees.

Your stipend is being paid by the graduate school, and yes technically the grad school could just pay the gym automatically and give you less money. But what would happens if something goes wrong and the grad school doesn’t pay the gym for your membership?  The director of the gym now has to go figure out why the grad school didn’t pay. But how is the director of the gym supposed to know how many grad students were supposed to have been paid for? How is the dean of the grad school supposed to be able to verify that the gym didn’t receive payment for the full complement of students?

It’s way easier, from the point of view of both the gym and the grad school, to just make you responsible for the fee, and to give you the money to pay it with.


Studying medicine after PhD in nuclear engineering I am a PhD in nuclear engineering and I am mostly expert of mathematical modelling:
1)neutron and particle transport;
2)fluid dynamics;
My methods are finite elements, finite volumes, lattice Boltzmann, machine learning.
My other dream is also becoming a MD (I love psychiatry, but nuclear medicine is certainly closer to my background). I am talking more about medical research than clinical practice.
Do you think there’s a way to reach a ‘synthesis’ between the two paths (in which each can benefit the other) without wasting away 10 years of studies?
IMPORTANT: I am talking about becoming a MD, and not doing something more medical-related without becoming one.

I don't see any conflict, actually. Nuclear medicine is a recognized specialty. Medical researchers often enough earn MDs as well as doctorates as it gives them more of an appreciation of the biological and clinical needs in medicine.
Moreover, it isn't necessary that a person have only one deep interest in life. Lots of doctors have other interests. Many are geeks and program computers "just for fun". Many are musicians, etc.
You might reach a stage, however, in which you need to choose, or at least emphasize, one interest over the other, so be prepared for that eventuality.
Since it isn't my field, I can't suggest an integrative path, but you might find one as you go along. Some medical practices are pretty crude, in fact and can benefit from the work of a researcher who can bring other ideas to bear.
Long road, though. Lots of sleeplessssss nights.


Would taking the GRE (when it is not required) be likely to help my application? I want to go to grad school for Applied mathematics, and I have a high GPA in my undergraduate of 3.56 in Applied Mathematics. I wanted to take the GRE. However, they are very costly around $200, which I am not sure if it is worth paying that much to take the GRE. I plan on applying for Graduate Assistantships. If I do not take the GRE, will that decrease my chances for getting into Grad school and a Graduate Assistantship even though the schools I want to apply to do not require the GRE?

If the school you are applying for does not require GRE than it is extremely unlikely that it will make any difference.
Certainly take a look at the discussion on the importance of GRE scores for graduate school admissions; as usually GRE scores most often are used to perform "cut-offs", not as a competitive measure (or at least with relatively low weight). Thus, if the school decides not to make GRE mandatory it does not make a lot of sense to submit one (especially, if you don't have one ready for other applications).
Some exceptions probably will apply if the assistantships/scholarships have a separate set of requirements (I am not aware of specific cases that would require GRE, but can imagine such to exist) or when GRE is an optional application package item and one wants to strengthen their borderline submission. Even though in the last case, I would spend more effort in writing a better statement of intent.


In a statement of purpose for a PhD in computer science in the US is it better to express interest in a single subdiscipline or multiple? It seems that if I were to just express interest in a single subdiscipline (computer networking for example), and none of the networking professors are taking on students, I would not be considered based on any other merits my application may have. But if I were to express interest in several subdisciplines it may be difficult to create a structured statement of purpose.

A PhD is about expertise in a narrow field. Showing too wide spread interests is counterproductive, you should have a rather clear idea what your principal interest is. It is OK to have wider interests, but you need a focus.

Do your homework beforehand, select prospective advisors and contact them for openings.


Found and corrected a mistake on someone's else paper -- praxis? 3-4 months ago I found a big mistake in a theorem's proof of a paper that had just been published (stats/cs community). I immediately notified the authors, who claimed to be aware of the mistake but admitted not knowing how to fix it.

This week I noticed that the authors didn't notify the community of the mistake (no updates on their arxiv paper, nothing on the author's websites, etc), even though the paper got a good visibility and already has quite a few citations. I went to check whether the mistake breaks the theorem, and found out that:

1 - the theorem statement is incorrect

2 - however, the statement holds under reasonable assumptions, but the proof requires a different technique (I have a full proof for that)

How should I proceed in this case? This theorem specifically is the main result of the paper, so I wouldn't be comfortable just sending them the corrected proof+statement and not getting properly recognized (e.g. only an acknowledgement). Should I write a short report on post it on arxiv? Send the proof under the requirement that I be added as a co-author? What is the praxis in this case?

EDIT:

Thanks for all the replies so far. I've contacted my advisor and have finished writing a short report (~4 pages) on the matter. I'm yet to decide whether I should contact the authors before posting the report, and whether a merger would be a good idea -- as some people said, it is a huge red flag that they admitted to be aware of the mistake and never took action, so I am not certain that I would like to be associated with the authors in a collaboration level.

1) The paper has already been published in a conference and its journal proceedings. I've contacted the authors after acceptance but before the proceedings were published, and they took no action.

2) The paper proposes a new algorithm B and states that it has the same running time as algorithm A, a classic method in the field, while having smaller memory cost and being easy to implement. The main theorem roughly states that T(B) = O(T(A)), which is wrong as for some inputs T(B) = infinity. The technical mistake is subtle and involves upper-bounding an infinite series, which in reality can diverge to infinity. I've ran the algorithm on a simple instance where it does not halt nor makes any progress.

3) It can be shown that, for some input distributions, T(B) = O(T(A)). The technical argument is a bit different from what they initially presented. Unfortunately, I think that for these distributions it can be shown that A has an even smaller memory cost than B, but I am not sure.

I have not been in such situation. However, I do not see what is the problem for you to write a paper complementing or correcting the previous paper? Isn't this how science works?

In my opinion, it is very toxic culture in academia to consider such thing as inappropriate. Those previous auathors are humans. Assuming good faith, that was what they knew and what was to the best of their knowledge, and to the best of the reviewers' knowledge, at the time of their publication. You got something, great, you have the right to get the credit for it. I feel it is unfair that you inform the authors offline. You should write it, and publish it too.

Also, we should not forget that you might be wrong too! I do not mean to offend anyone. But if we remember that we are all humans and have limitations in our knowledge about exploring this world, we would take these issues in a more relaxed way.


Is there a trollish/novelty/esoteric citation style? In programming, there are these so-called "esoteric  programming languages" like "LOLCODE" or "Shakespeare," which really have pretty much zero usefulness. They are just kind of a novelty, or if a computer science professor is feeling like being particularly obnoxious he can choose it as the language for one of his assignments.

I was wondering if there is anything similar for citation styles. Citation styles are a "language" of sorts, and in principle you could have the analog of "LOLCODE" for making citations. I have never heard of such a thing, and I was considering inventing one---you know, something for a Humanities professor to require if they are feeling like being particularly obnoxious---but I wanted to make sure that such a thing didn't already exist.

May I humbly suggest footnote labyrinths?

Alt text: Every time you read this mouseover, toggle between interpreting nested footnotes as footnotes on footnotes and interpreting them as exponents (minus one, modulo 6, plus 1).


Finding out if company founders are graduates for a dissertation In a nutshell, I'm thinking about doing research and analysis of founders of rapid-growing companies during the last decade or so, to see if there is an increasing trend of non-graduates successfully founding these firms, or if having a degree (especially in the same industry as the company) is highly recommended.

However, I'm afraid the sources from which I can obtain this data might not be valid in the academic environment (or in any environment). For instance, I could go and check a founder's LinkedIn profile, but:

Is LinkedIn a reliable source of data for a dissertation? I don't think so.
Many people decide not to show their entire education or job history, because it might be irrelevant or because having a degree from a university with a low reputation could be a negative thing.

Trying to contact these founders to interview them is almost impossible.

I'm not experienced in doing academic research, so my question is: is there a reliable source of data for this that I could use for my research?

This is in the UK, if it makes any difference.

The most reliable source is the college/university itself. You can compile a list of where these founders when to school, and call the school itself and ask the question. The question has to be Yes/No so you will have to phrase it like: "Did you award such-and-such degree to John Smith?"

If that is too labor intensive, a simple Google search of the person "John Smith College" should return results from reputable sources such as Time, Business Insider, etc.


Which logo to use in a seminar title page? This might sound a silly (probably it is!) question to ask. But whenever I go to give a talk at some other institute I face this dilemma of putting the host institute's logo or only my affiliation logo, on the title slide. Most of the time I put both.

Keeping aside my decade-old-hesitations, let me ask you about your opinion on this.

The acceptable use of logos is usually described in an institution's corporate design manual. The corporate design manuals I've seen do usually not allow people not affiliated with the institution to use the logo without explicit permission, so I would never use the host institutions logo. Such thing will also not vary between fields (in my university's cd-manual, only some color schemes differ between faculties). There might even be some legal issues involved, but I'm not competent to discuss legal matters.

Most academics in at least my field, quite reasonably, ignore corporate design manuals which might even specify minutiae of how your slides are supposed to look. Usually, they do this by not showing any logo at all- my preferred choice for aesthetic reasons. But there is absolutely no reason to show a host university's logo.


Does a post doc at a prestigious university make up for doing a PhD at a lesser ranked university for Mathematics? I think I understand that someone should do a Ph.D. under a strong advisor and have a solid publication record, and I know going to a more prestigious university helps. Now, this is where I get confused. Let's say person A goes to Princeton and person B goes to Iowa State, for example. Let's say person A gets a post-doc at Michigan and person B also gets a post-doc at Michigan. Do people A and B both have an equal chance of getting a tenure track position at for example the University of Oklahoma? I guess what I'm asking is that if someone gets a post-doc at a prestigious university, does it make up for the prestige of where they got their Ph.D.?

The university I'm going to do my Ph.D. in has a nontrivial amount of people that get postdocs at prestigious universities but none of them end up as tenure track professors at universities with a graduate program.
A very small number of people ended up at R1 universities past 1990, perhaps several people at my university.

Some famous counterexamples to this are Igor Rodnianski, Aaron Brown, and Ernest S. Croot.

DISCLAIMER: I'm not interested in going on to be a tenure track professor, just curious.

Actually, what is better is what you do in whatever circumstances you end up in. If you are productive and publish good research, the institution at which you do it is of little importance. But any institution at which you can find good collaboration resources, such as weekly seminars in field, are valuable. Larger places which larger faculties tend to have these. But even quite small institutions manage it.

One of the reasons that few people are winding up with tenure track positions at R1 universities is that the number of total positions offered in a given year is small compared to the number of potential candidates. So, the competition is fierce, but it doesn't consist of ranking the candidates in the order of the prestige of their institutions.

Go where you will find people with similar interests and who are willing to work with you. Write a lot of good papers. Build an expanding circle of collaboration. The very best faculties are not, in fact, concentrated at only the very most prestigious universities.

Note also that doing mathematics alone without any feedback or synergy is very difficult. So, a group of like minds is very valuable. It is possible to wind up at a prestigious place where there is actually no one to give you any support. It will be difficult to advance from such a situation.


Do extracurricular research/activities in graduate school negatively affect your future? I'm the kind of graduate student that finds many research topics interesting and wants to participate in lots of student organization activities related to science and academia. But recently, one of my professors warned me against "doing too much" beyond my research focus, both in terms of publications and in terms of extra-curricular activities.  As I see it, your goal as an academic is to develop a "specialty", so it is important to focus on one narrow topic and pass over opportunities to research other interesting, but unrelated topics.  But can research outside of your particular focus in graduate school really negatively affect your ability to get hired in an post-doc or tenure track position in the future?  How can "doing more" reflect negatively on one's self?

Read broadly, publish narrowly deeply.

This is roughly what I've been telling my students. Now all of this depends greatly from area to area, but here's what I believe to be true. Having a broad background in your area might slow you down initially when trying to publish. But over the long term (your entire career), a broad base will help you more - it will let you be flexible about topics of interest, it will allow you to see connections where others might not, and it will help you place your work in a larger context.

But from your question, you appear to be referring not just to "exposure to outside topics" but "activities related to the larger enterprise of science and academia". With those activities also, you should be careful. Maybe choose one or two outside activities and devote your extracurricular efforts there. The advantage is that by focusing, you're more likely to be able to do something meaningful, and it also prevents you from frittering away time in busy work.


Ethical nature of multiple post-doctoral applications I am a student applying in different places for postdoctoral positions and asking various faculties for position. It happened that, due to limited resources, I am not getting much response. However more than one faculty (from different institutes all in Europe) gave positive responses. The caveat is, I have to jointly write a research proposal with them for grant application/some fellowships. Whatever be the outcome of the proposal(s), I am starting my collaboration with them soon.

My dilemma starts here. The fellowships each one suggested are very competitive. Those faculties themselves informed me that getting those fellowships became more difficult in the present financial situation. Now is it ethical to do apply for multiple funding agencies in this way? Fortunately, each of them suggested applying for different fellowships. I am slightly afraid of the morality of the whole issue (like: what if all of the projects get funding). Please help.

There is nothing wrong or strange to apply for several fellowships and funding as you describe. The opposite would mean you have to gamble on one and hope it comes through. What can be a bit problematic is perhaps if each proposal causes a lot of work for somebody in a department if you later is a no show despite funding. In such a case it would be good to let people know you are sending in other applications as well so they are not completely in the dark about your situation. I am sure everyone will be sympathetic. If they are not you may not want to go there anyway.

The risk of getting money from several of your applications seems like a luxury problem. Yes, you have to decide which one to go for but that should be a pleasant problem. I would tackle the problem IF it becomes reality and not worry about it at this stage. Your first step is to get applications in, not worry about what to do when and if any funding comes through.


Correcting Preregistered Methods After the Fact I'm often asked to help conduct statistical analyses after a paper is rejected for statistical errors. In some cases, the study, including the methods and analyses, is preregistered in some way (e.g. the study that I'm currently dealing with was preregistered on clinicaltrials.gov). The problem that I face is that the preregistered statistical analyses are often incorrect and I would consider it a sort of malpractice on my part to perform the wrong analyses - even if that means deviating from the preregistered methods. Are there any guidelines regarding the academic/publishing ethics of deviating from a preregistered protocol?

As a fellow statistician who assists non-statistician researchers, I sympathise with this predicament.  I actually gave a faculty talk at my university about a month ago, giving advice to researchers on writing methodological applications such as pre-registered descriptions of experiments.  One of the things I stressed in that talk was the importance of describing statistical methods without "locking yourself in" to models or tests that end up being inappropriate for the data.  Generally speaking, the statistical description in the pre-registered methodology should set out the general model form expected to be used, and give a description of the hypotheses that will be tested, but it should always give allowance for the researcher to make changes in the model when this is necessary to accommodate the data (e.g., when diagnostic plots show heteroskedasticity or non-independence of residuals).

Obviously all this is too late in the case you are dealing with, but it is a useful opportunity to raise those issues with the researchers who wrote the pre-registration document, and give some advice for future practice.  It is also worth bearing in mind that the primary purpose of pre-registration of experiments is to prevent researchers from making post hoc comparisons and then passing them off as the hypothesis of initial interest.  Pre-registration does not exist primarily to lock statisticians into model assumptions.  In any case, logically, there are three possible ways you could proceed in this case:

Good analysis trumps pre-registration: Do the correct statistical analysis, making whatever changes you need, even if this is contrary to the method/model set out in the pre-registration document.  Make sure the write-up of the analysis and subsequent academic paper clearly disclose (and explain) any deviation from the pre-registered method.  The reader will then be able to decide whether or not they still trust that the pre-registration has achieved the desired purpose.
Pre-registration trumps good analysis: Do the analysis in accordance with the pre-registration document.  Make sure the write-up of the analysis and subsequent academic paper clearly discloses the flaws in the analysis, but notes that they were fixed by the pre-registration decisions.  Don't try to sweep these problems under the rug.
Refuse to do the work: The last option is to refuse to do the statistical work on this project, on the basis that you cannot comply with the pre-registration method, while still doing good statistical analysis.  This option leaves the other researchers in a bit of a bind, but some might say that that is the proper penalty for having locked in bad methodological decisions in the pre-registration document.  (And even if you choose this option, some other statistician might take up the work, so they will still need to read this answer for advice!)

In my opinion, the first of these options is clearly superior to the second.  You get a good analysis that is done properly, and the reader is able to decide if the pre-registration has achieved its purpose (usually to prevent post hoc comparisons) despite the changes.  If you decide to go ahead with the analysis, I would suggest that you adopt this method, but make sure the other researchers agree that they will clearly disclose the changes you make to the method in the final paper (so that the reader knows that there was a deviation from the pre-registered method).


Is including an own paper in the literature review a bad practice? The title mostly says it all.

I am writing an article on a rarely researched topic in my field - 4-5 articles exist, as far as I know.

I recently published a related article, still making this topic a rarely researched one.

Would it be a bad practice to include my own published article in the literature review?

No, not at all. You should cover all publications which fall within the scope of the review, and if one of them happens to be a paper of yourself, then of course you still have to cover that in your review. Just make sure that you try to be objective in the way you discuss it. Best practice would be to review your paper as you would review a paper by any other author.

Maybe you have a coauthor in the review who was not coauthor on the research paper? Ask him/her to do the review section about that research paper.

Also note the positive aspect of this situation: having published a research paper in the area you are reviewing gives you more credibility as an author of a review in that area.


Will delaying entering grad school for a year to pursue study abroad put one at a strong disadvantage? I'm a year away from getting my undergrad degree in (computer) engineering, with a minor in Japanese. I never had the opportunity to do a study abroad due to the rigors of the major. As some probably know, the JET program is a program by which selected individuals move to Japan to teach English at public schools for a year (or two or three, but not more, I believe). I've always been very interested in doing something like this, but I have always assumed that doing so would ruin my chances of getting into a graduate program or landing a good job upon my return.

It wouldn't be like attending grad school before entering the industry or vice versa, in that I would be teaching English for a living, not studying or working in my field. I could still self study, and my field gives me the advantage of still being able to apply my skills working on personal projects and open-source software, but I would certainly be removed from the industry and academia, I would expect.

I feel like leave from the field would look bad to any prospective schools or employers. How accurate is my assumption? Would a leave of absence to do something like this reflect poorly on me in the eyes of potential schools or employers?

This will not hurt your future plans. International experience and second language skills like this will likely help, even if they are not related to your undergraduate or graduate career.


Is a university that grants me a PhD for $1000 and a copy of my unpublished book fake? I have paid $1000 for PhD in mathematics. And I have sent them my book to be considered as a PhD thesis.

Now I suspect that I have lost the money.

But as far as I know they are not accredited by the U.S. Department of Education.

So, is it possible that I will find a job requiring a degree, using this (fake?) PhD?

Now they have told me that the U.S. Department of Education will send my diploma to US foreign affairs department and then they will make some "stumps" on my diploma. Do these stamps mean anything? Are these stamps just a formal thing which mean nothing and don't make my degree "official" ("real")? Moreover, to send my diploma to the departments costs additional $1000-$1750 (dependent on whether I pay right now or later).

You have lost the money whether or not the "university" gives you the degree.

You have given your money to what is known as a diploma mill. A long time ago (nearly two decades!), I received an email offering degrees from "prestigious, non-accredited universities" based on life experience. This is a complete and total scam. Even if you have a diploma, it will be useless for professional purposes. Anybody responsible for hiring a PhD will see that there is no work resulting from your "graduate career," which will be a tipoff that the degree is worthless, and you will be unlikely to receive a job offer. Worse still, even if you were to get an offer, it could be rescinded when the truth is uncovered.

Disengage now, before you lose any further money on this situation.

Addendum: I should also mention that I am unaware of the US Department of Education doing any certification of diplomas and certificates on an individual basis.


How do you come to terms with the fact that you might never be among the best in your research community? I am currently a PhD student advised by a new (and awesome, in my opinion) theoretical computer scientist in the field of optimization. This was my dream ever since I took a class on convex optimization a few years ago during my MS.

However, I don’t have a math or CS background. My master’s and industry experience have both been in applied signal processing. When I recently looked at the kind of grad students who work in my current choice of research area, I realized the level of competition I am up against.

These are all from amazing institutes around the world and had been the brightest kids in their colleges, the ones with medals in olympiads, top Putnam scores, etc. I am from a mid-tier college in my country and never won an award for excelling in math/algorithms.

How do you come to terms with the fact that you might be doing research in what you love with an amazing mentor, but you’ll just never be the best in even your research community? How's that not discouraging?

If every swimmer were to compete with the latest 20 year old Olympic gold medalist, they would soon give up. That's why we have different leagues. They provide more relevant frames of reference to compare different athletes. Thus you need to:

Shift the frame.

Adjusting a bad frame:

You are a PhD student who completed some regular college and an outsider to your field. But you are comparing yourself with your supervisor and with "the brightest kids" in the world and, what is more, with scientist who specialized in your field from the get-go. How can that not be disappointing?

What about: You are an up-and-coming young researcher with real-world experience and a background that is not the usual run-of-the-mill in the field you are working in. You have an amazing supervisor who trusts your work and you are at least as successful as the other PhD students in your cohort. Perhaps you are the only one from your college who made it to graduate school in the last couple of years. You still have plenty of time as a researcher to develop your own profile according to your interests. Don't be fooled by the impostor syndrome.

Dropping a bad frame:

Never mind what I said in the beginning. Science is not a competition -- at least it shouldn't be.

If you're doing research mainly to outcompete your colleagues, to improve your social status, to feel pleased with yourself: you're doing it wrong. Then you are extrinsically motivated, and this is neither sustainable nor does it make you happy. Have you ever delved into a problem and forgotten to drink or eat until the sun went down? Have you ever felt deeply frustrated because you just couldn't wrap your head around some strange finding, only to realize later that it completely makes sense when you look at it from a different angle? Experienced the enthusiasm that came with that discovery? Do you deeply feel that you have to understand this? Then you know the feeling of flow that really only comes from intrinsic motivation. Forget the competition; enjoy the game.


What masters degrees can I apply for with an undergraduate in Computer Science? I'm a Computer Science student in the UK who is about to go into my last year and I'm looking into applying for a masters programme and I'm not sure what subject areas I can apply for. I've heard that doing a Masters in Computer Science after doing your undergraduate degree in Computer Science is essentially useless. I'm on track to hopefully graduate with a first if that effects what I can do after I graduate. I was particularly interested in pursuing something maths related.

There are many kinds of masters program you can apply for with a degree in CS, ranging from more "technical", specialized programs to non-technical ones like an MBA. Restricting the possibilities to more technical master's programs "that involves some maths" and/or advanced programming still cover a large number of potential programs, especially if you're willing to go abroad. Examples include master's in machine learning, bioinformatics, financial engineering, embedded systems, information security, data science, and scientific computing.

It'll be best if you first consider clearly which specific area you want to specialize in. If you are still uncertain about this part, it'll be good to work for a few years first. Working also serve as a kind of reality check -- you may think that you will enjoy a specialization based on your experience with a related module during your undergraduate years, but later discover that you don't really like the job scope of a typical professional in that field, or any of the potential employers in your location, or the overall long-term prospect of that particular field. In that case you can still adjust your plans before investing more time, money and effort to get a Master's in that particular specialization.


Research results obsolete while publishing Consider the following situation. Scientist A obtained a novel cool result and submitted it to a respected journal after putting the preprint to arXiv. The journal started the peer review process which will take 2 years. During this time scientist B drastically enhanced A's achievements thus making them obsolete. B also put his preprint to arXiv, so the reviewers can easily access it too.

What will happen then? Will the journal publish A's work? If not, why?
And what should A do to have any credit for his (pioneer) work?

There is no way to predict what will happen to your paper or whether
you will get credit you find satisfactory. If B is a decent person
he/she will choose to to make some acknowledgement of your prior or concurrent work.

This cannot be the first instance of such competing claims for priority.
Your journal may have a policy
on handing such situations, and it would not hurt to ask, as long
as your request doesn't appear to put blame on the journal for delaying
your paper.

You don't say what field of science is involved. Does your paper use
different methods than B's? Methods which are not made obsolete by
B's paper and might lead to other developments? Does anything remain
of your paper that is not superseded by B;s? If so maybe you'll be
asked to revise your paper to highlight what has not been 'scooped'.

In some fields I know of cases in which journal editors worked out
an arrangement for one or two joint paper(s), pretty much to the satisfaction of all. Obviously,
that would not always be possible.


When you cite a paper, is it a good idea to email the cited author(s)? Inspired from this question, I think the reverse can be an interesting discussion so I will set up an artificial example.

Suppose I cite XYZ in a published or under review paper. I am not affiliated or have had past contact with the author(s), so we are personally unknown to each other. This can also include a passing chat in a conference/ seminar, but certainly not something regular or memorable. For ease, let us assume that the citation is of some importance, i.e. it is a key paper and my work relies on it, or the results/ methodology are related. This, therefore, excludes "lit review" or "professional/ courtesy/ standard" citations. My intentions are honest: I genuinely intend to say "thank you, your work is good and it helped me a lot, feel free to contact me in the future" and do not intend to trade citations, disguise a suggestion (Trojan horse) or have a hidden agenda. I would be happy to discuss further, or end up working with XYZ in the future, but the purpose of the email is not that.

Given the above, is it good practice to politely email, Tweet or PM the author(s) with something along the the following lines?

  I found your paper XYZ to be interesting and relevant to my work, and I cited it in my recent paper ABC. My paper is related to yours in Way 1, Way 2 and Way 3. I believe you would be happy to know that a colleague found your work to be useful and I took the liberty of contacting you. Please consider me open for future contact and feel free to email me with any thoughts you may have.

If yes, when is that true? Conversely, under which circumstances can such an email be seen as unprofessional, impolite or suspicious? Are such emails considered sound academic/ professional practice, or is there a danger to be misunderstood, appear offensive or seen as having other intentions? Basically, is it a good idea or will it backfire spectacularly?

I think emailing authors when you find their work particularly interesting or useful is nice, and I'm sure everyone loves to recieve such emails. However, I don't think citation has anything to do with it. That said, I don't think I would ever find it "unprofessional" or suspcicious to recieve such an email.