If asked to submit both a shorter and longer abstract, is it possible just to send a shorter one that meets both word limits? I saw the following abstract submission guidelines:

  Please submit a 500-word text abstract for technical review purposes that is suitable for publication. Accepted abstracts may be published
  with the printed Technical Program for distribution at the meeting.
  Please also submit a 300-word text abstract suitable for early release. If accepted, this abstract text will be published prior to
  the meeting in the online or printed programs promoting the conference

My question is, how close to the prescribed word count do you have to be? Would it be possible to send one abstract for both requirements?

It is possible, but you would not want to do that.

Apparently, these are the guidelines for some sort of conference. Usually, you send in a preliminary abstract, then you get a message back that they will accept your permission within a certain deadline. Now you can write and hand in your article.

If you haven't finished your article in time for the abstract submission deadline, you basically have to write an abstract first. But after you have written your article there are most likely changes that need to be addressed in the abstract, which is why you get more words for the final abstract to amend your early release abstract that will probably be available on the website of the conference.


Going to a lower-ranked school for better advisor fit Computer Science PhD admit here.

Is it crazy of me to turn down a top school (MIT/Stanford) for a lower-ranked school (think Cornell/UW/Columbia/Michigan) if I think there is better advisor fit?

Obviously all of these are fantastic schools and I am very lucky to be choosing from them. However, I felt like I got along really well with my would-be advisor at the lower-ranked school than I did at MIT/Stanford. People have told me that it's crazy of me to turn down MIT/Stanford since they are, along with Berkeley/CMU, on a different "level" than the other schools.

(My field is somewhat narrow so there is only 1~2 faculty at each of the schools doing research in the area. So regardless of which school I go to, if the advisor doesn't work out, I would be in a dire position.)

EDIT: Both advisors are well known in the field (and both have produced outstanding graduates), but the MIT/Stanford professor is good deal more senior. Also, talking with their current students, the MIT/Stanford professor is known to be pushy and have a "strong" personality (which may work for some people, but not sure whether it will work for me, as I've never worked with such people before).

All of the schools that you are discussing are first-rank computer science schools with global leadership in their areas of specialty.  In this area at least, the only real difference between the "top" and "top of the top" schools that you are considering is the number of different areas in which the school is a global leader.  Thus, if you already have a clear, narrow focus that you know that you want to work in, and there are 1-2 people in that area at all of the schools you are choosing between, the distinction between "top" and "top of the top" is pretty much null.

Furthermore, your graduate career will be primarily determined by your advisor relationship rather than the school within which it will occur.  Beware of being misled by first impressions, but a good match with your Ph.D. advisor is worth much more than the incremental difference between schools.


Applying for tenure track position in mechanical engineering with lack of relevant coursework experience? My undergrad and masters degree was in materials engineering. All my coursework and lab experience is in materials engineering. During my PhD, I had taken just two courses which did not directly help with my PhD research. My undergrad and masters courses were also not aligned with my PhD research.
My PhD thesis was on using finite element analysis and smoothed particle hydrodynamics to study mechanical damage under extreme conditions. As for credentials: I have 5 publications in applied journals (IF~4).
Now, I was applying for tenure track positions in mechanical engineering department where they want my academic transcripts to be submitted.
My question is in two parts:

How do I justify my ability to teach and contribute to the mechanical engineering department if my degree and coursework experience was not in that field? My research is however in that field.
Since my colleagues in the department would be from mechanical engineering background with dedicated coursework experience, would my application be considered seriously for a position in the department? I have been asked to submit my transcripts with my application package. They would know that I lack the coursework.

I understand that noone have been in my peculiar position before. Usually people take necessary courses during their PhD. I got away with not taking them as I could self learn the required basics and was able to apply them successfully to my research work. However that doesn't make me technically thorough and strong in the topics.
Hoping for some insights on how to go about with my faculty position applications in my case.

This is not necessarily a big problem, or an unusual one. Not every professor in a department is expected to be able to teach every course. I trained as a physicist, but I'm now in a nuclear engineering department.
As part of your application, you may be asked to write a teaching statement. In this, you should identify i) a few existing courses within the department which you can teach and ii) some brief ideas for new courses you could teach. These new courses could easily be tailored to your expertise. It is also entirely possible to learn new material and to teach it.


Postdoctoral fellowship -- what is it about? Assume you are just about to finish your PhD and you are facing the decision of whether to go for a postdoc position or for an assistant professorship. Which one should you choose?

Let's ignore the salary for the sake of this question. Then which of the two is better? What about the benefit of short-time employment and getting to work with lots of different people (in case of postdoc) vs. being stuck at one place for several years (assistant professor). Is it beneficial to work with different groups or is it irrelevant?

Does a career involving several postdoc positions look like the individual could not get other (''better'') employment (even if they deliberately chose one over the other)?

Will a postdoc position give you more time for research because you don't have to teach or have to teach less?

Is it generally better to seek professorship rather than postdoctoral fellowship?

The typical perspective for U.S. people in this situation is to try to balance the following three items:

The desire for a permanent, tenure-track job, and its associated stability.
The desire to do as much research as possible in one's life.
The desire to not starve to death.

Generally those just completing their PhD's are not eligible for tenure-track jobs that have a large research component, because their track record is insufficient.  Therefore it is common to take a postdoc (or two, or five) to bolster the research record.  This has the immediate effect of meeting the second and third goals, and has the potential to open up more research-oriented tenure-track jobs.  However too many postdocs and it becomes more difficult to get tenure-track jobs (and further postdocs).  The implication is indeed as you suggest, that these positions have been taken because the individual could not get a suitable tenure-track job.

Very few people consider "assistant professor" negatively because of being "stuck at one place for several years"; the only reason to turn down such a position is because it may be a bad fit, as compared to the sort of place one wants to be.


Is sending fall semester transcripts beneficial even if grades show a downtrend? I received my undergraduate transcript with the fall semester grades a week back; I was wondering whether I should use it over an old transcript for my application to grad school in the US (top 10 in physics).

Reasons for sending old transcript (latest: spring grades from junior year):

Spring semester showed good grades.
Higher CGPA (+0.05 on a scale of 10.0).
Subsequent fall semester shows a downturn in grades (-0.7 on a scale of 10.0).

Reason for sending new transcript (latest: fall grades from senior year):

Shows advanced physics and math courses; I have talked a bit about these courses and a project in my Statement of Purpose.

One reason for the less than ideal performance in the fall semester is taking a lot of theory courses; however, I have not "explained" this in my SOP as there aren't any failing grades (or really poor performance).

Does the choice between the two transcripts really matter or am I overthinking this? If it matters, I am an international applicant from India.

P.S. I have completed the essential courses earlier so that is not a factor to be considered.

Edit: As pointed in a comment below, this question is not a duplicate as my grades are quite good (sorry for not mentioning this in the original post).

You should include the latest transcript.  The reason is simple: that is now your true transcript, and replaces the prior transcript.  If you don't include the most recent grades, then the universities where you are applying may wonder why: did you have terrible grades? Were you not attending classes at all?

Your current transcript is your transcript.  Just include it, and don't play games about it.


Balancing an internet startup and a tenure track professorship What should do or consider to simultaneously succeed at my new professorship and my internet startup?

I am starting a tenure track professorship in the fall. I am also on the team of  an internet startup which has received an initial round of funding. I have expressly limited my availability to the startup to the amount my university allows faculty to consult. That said, this is not consulting,  and no explicit rules regarding my situation are on the books beyond broad conflict of interest rules.

I am not alone in this decision to pursue academic and startup success together, and as I talk to others starting this path I see common questions as to what challenges we will face.

What factors should a dual academic/startup founder consider, especially pre-tenure?  I'm especially interested in advice from professors with a startup.

Nothing is impossible, but how many hours a week do you want to work? Do you have any life beyond these two endeavors. I don't participate in a startup, but at various times have published books and software and built interesting tools for students and professionals.

But the warning here is that beginning a tenure track (especially) is a very time consuming proposition, especially if you want to actually attain tenure in a few years. You need to serve the students well at what ever level you find them. You need to establish an appropriate publication (research) history as well as a recognizable place in the profession through conferences and such. You need to have, or create, contacts with other researchers to help you in your own. This might come at your own University, given a large enough faculty with good synergy, but you may need to expand your contacts outside.

In the US, the typical "slog" to tenure is seven years and you don't get do-overs. Not every paper you submit for publication is necessarily going to be accepted.

You can read other questions on this site to learn some of the other problems that junior faculty have in adapting to the academic life. Not much of it is likely to come easily to you if you are really new at it. Good things happen in Academia, but they don't happen on auto-pilot.

Some institutions have a history of tenuring most candidates. Some, alternatively, have a history of tenuring nearly no one, though some of the "failed" candidates have a good chance of success in moving, due to the reputation of the university.

All that said, many (most) junior faculty do have outside interests of various sorts that take some amount of time and effort. It isn't impossible to succeed at both, but you may need to set parameters for yourself and decide early on what is the most important thing in your life. If you sort of stumble along at both, you aren't likely to be a success at either.

Finally, what you learn and what you do in the startup may be a plus when it comes to tenure, though you indicate it is a different field, lessening the possibility. But if entrepreneurship is valued in your field it may be a help.


Risks of shifting to post-publication review I've heard some compelling arguments from open science advocates for a system of reviewing scientific research outputs that focuses almost exclusively on post-publication peer review. The idea is that research would initially be published in free and open venues, with little to no lag time resulting from pre-publication review (pre-pub review, if any, is focused on weeding out large and obvious flaws and not on assessing perceived significance or impact). Once published, social tools similar to those in place at Amazon and StackOverflow (reviewing, commenting, reputation systems, etc.) would be used by the community for more in-depth assessment and critique of research outputs. Scientists could get credit for post-publication reviews, which (if openly accessible along with the article) are  valuable scientific contributions themselves. On the other hand, junior scientists afraid of unjust retribution for being critical of a senior scientist's research could post reviews anonymously/pseudonymously, protecting their professional reputation but still making an important contribution to the scientific discourse.

I've seen two primary arguments against this kind of system: 1) that pre-publication review is an important quality control mechanism, and 2) that it ensures that the published scientific literature actually gets read. Regarding this second point, many raise the point that many research articles go uncited (and potentially unread by anyone other than the authors and reviewers). It could be tragic if a major scientific breakthrough existed in the literature, but was never widely acknowledged because the paper never got any attention and post-publication review.

Do these risks give real cause for concern? Is there some level of quality control that can only be done pre-publication? Do we risk missing out on important research by not requiring rigorous review of all published material? And are there other risks not mentioned here that would make a shift from primarily pre-pub review to primarily post-pub review problematic?

In my mind, there are three semi-related problems with post-publication peer review:

It's difficult for the lay press to distinguish between pre- and post-publication reviewed papers, and for many "breaking" articles, I'd be concerned about reports of spurious results becoming more common, not less. For example, if I publish a paper on a risk factor for X disease, how long does the press have to wait to report it? Do they have to let peer reviews build up? Pre-pub at least ensures that someone has looked it over.
Article readership is nowhere near uniform, and there's no reason to believe reviews would be different. At the moment, every single paper published by a journal is subjected to some form of review, whether anyone else cares about that paper or not. Relying on post-publication, it's possible some papers will get few/no reviews. What's a non-expert to make of those papers? Similarly, what's a non-expert to make of a post-pub vaccine study that's been flooded with anti-vaxx rhetoric dressed up in technical jargon?
Post-pub peer review is inherently non-anonymous. I'm pretty sure Big Deal Figure in the Field is not going to be judged as harshly as New Grad Student even for the same work - and this will also likely effect those with clearly female or minority "sounding" names. Prominent scientists may be more likely to get a pass under the assumption that they're  right. In my mind, breaking review anonymity is a step in the wrong direction.


What are possible outcomes when a PhD cannot be completed during the funding period? Suppose a university provides a five-year PhD studentship (i.e., tuition waiver and monthly stipend). What are possible outcomes if the student doesn't complete their PhD in five years?

Will the university continue waiving tuition and paying a stipend?
Can the student complete their PhD?

When a school makes a funding commitment, it is generally true that the commitment is contingent upon a student making satisfactory progress to the degree, as judged by the department.

What happens when a student can't finish in the stated period depends upon a combination of factors:

Where the funding to continue supporting the student will come from
If the student is, in fact, making adequate progress and will finish in a reasonable period of time
What the regulations of the department or university are with respect to enrollment (that is, is there a limit to how long a student can be enrolled)

So long as a student is making satisfactory progress, and a source (such as PI funding or teaching assistantships) can be found to pay the student, departments are usually not inclined to dismiss a student based on failure to meet an arbitrary timeline. Usually, the student, supervisor, thesis committee, and department will agree on some sort of timeline to finish the degree program as quickly as possible.


What are the signs that it is time to switch from thesis to capstone track? The Master's program (Software Engineering) I'm enrolled in offers both a thesis track and capstone track. Currently I'm enrolled in the thesis track and I've completed all of the required coursework for the thesis track, but I've been stuck in the thesis proposal process for over a year now1 and I'd like to just graduate and be done. I suspect that I'm being "encouraged" to switch over to the capstone track without the Research Advisor outright saying it. What should I take as the signs that it's time to make the switch?

By stuck I don't mean that I don't have a proposal, I mean that I've been submitting revisions about once a month for the past year with conflicting feedback being received and no real progress towards having a Thesis Director.

This answer might not be applicable to everyone; however, today I met with the Associate Director of Professional Programs at [tier-one university]. I was informed that barring extenuating circumstances, if a student doesn't have an accepted proposal and a Thesis Director assigned after a year then they should switch over to the capstone track to ensure they are able to successfully finish their degree.


What do mathematics graduate schools look for in undergraduate students? I'm just curious. I have a strong GPA, but I heard that's not enough. I was told that among a GRE score, schools actually place stronger emphasis on performance in 4 classes: a proofs/logic course, analysis, discrete math, and a linear algebra course (this was apparently has less emphasis than the first 3). I was told that these classes are the bread and butter of most graduate math classes and are indicative of how well you can learn the more rigorous content. Is this true?

I have some research experience under the NSF in mathematical epidemiology with a few poster presentations and abstracts at conferences.

Do these schools care about extracurricular such as volunteering experience? I know these aren't going to get you into Harvard per se, but do they slightly augment your profile? I know academia is primarily concerned with research so this may not be too relevan.

I am an (associate) professor of mathematics at the University of Georgia and was involved in graduate admissions for several years.  My answer is based on a perspective which is somewhat skewed towards pure mathematics: we have applied mathematics in our department as well, but it is one of seven research groups, so when looking at applications, to a first approximation we select for the same things among pure and applied applicants (and in fact not all applicants clearly identify themselves as one or the other, which is fine).  There are other departments that are more than half applied mathematics, and yet other departments (e.g. at Harvard) where applied math is a separate department entirely.

The main things we look at are competitive  GRE scores (including the math subject exam), strong grades attained in strong courses, and very strong recommendation letters which convince us that the student would have a good chance of succeeding in our program.  These letters generally come from faculty who have taught the student multiple courses, including an advanced course and/or a reading course.  Getting one letter of recommendation from someone who directed undergraduate research is a popular choice and is fine, but it does not really make a big contribution to the application because most such letters sound exactly the same (no one is going to say "So and so did an REU with me, and let me tell you: we got nothing done over the whole summer.")

  [S]chools actually place stronger emphasis on performance in 4 classes: a proofs/logic course, analysis, discrete math, and a linear algebra course (this was apparently has less emphasis than the first 3).

I don't find this to be especially good advice.  For me, the key courses are
(i) real analysis, (ii) abstract algebra, (iii) topology, especially the first two. These are in fact three of the four topics in which most of our PhD students take qualifying exams [some applied students take numerical analysis and/or probability].  Moreover, every graduate program in math I've ever heard of requires students to take exams in real analysis, abstract algebra or both.  Because these courses exist at both the advanced undergraduate and beginning graduate level, we really want students to have taken the undergraduate versions and have done well in them.  If they haven't, then they need to begin a graduate program taking these undergraduate courses, then make the transition to the graduate versions and then take and pass the quals, all within a couple of years.  That's hard.

Concerning your list:

(i) proofs/logic

Many students do not take a separate course on this.  In my undergraduate program we have a course on this but the strongest track of student avoid it by taking a kind of analysis class in which this material is taught on the fly.  Whether a student knows proofs and logic should be clear from the rest of their coursework and their recommendation letters.

(ii) analysis

Yes, this one is dead-on.  Let me say that a lot of courses are called "analysis".  We look carefully to see what the text is and what the topics were.  Something at the level of Rudin's Principles of Mathematical Analysis should be taken in order to be competitive.

(iii) discrete math

No, this is really not a critical course.  I can't think of many graduate courses that have such a course as a prerequisite.  Also the name "discrete math" is often used for a lower level course not even taught to majors.  But if you mean something like combinatorics, probability or graph theory: these are courses which most students enjoy, but they are not the courses we are looking to see if our applicants have taken.  This is not to say that the material from these courses is not important or useful in mathematics: it most certainly is, increasingly so across all parts of mathematics.  But it's not hard enough to learn to separate applicants like certain other courses.  I have never taken a course in graph theory, but some of my papers contain results about graphs: it's just not that hard to learn graph theory on the fly.

(iv) linear algebra

Yes, you need to have taken such a course, just like you need to have taken a course in multivariable calculus.  But this is (at the latest) a sophomore-level course for most students who go on to graduate school.  A course (or more) in abstract algebra, which will in places build on the linear algebra, is much more critical.

  I was told that these classes are the bread and butter of most graduate math classes and are indicative of how well you can learn the more rigorous content. Is this true?

As above, I don't think the list is well-chosen to be among the most important courses.  Also "indicative of how well you can learn the more rigorous content" is a red flag to me: a student's graduate application should be replete with evidence of how well she has learned the more rigorous content, by successfully completing coursework containing this content!

Who is giving you this advice?  Faculty in your department?

  Do these schools care about extracurricular such as volunteering experience?

Not really.

  I know these aren't going to get you into Harvard per se, but do they slightly augment your profile? I know academia is primarily concerned with research so this may not be too relevant.

Very slightly at best.  Just putting it on your CV is probably worth precisely nothing.  If you can describe your volunteering experiences in your personal statement in a way which makes them sound compelling and relevant to your graduate career then....well, then you have written a good personal statement, which could help you a bit.  If you did something really substantial which shows
off organizational and administrative skills that most students lack, that would also help a bit...but not as much as the time you put into it.  Obviously there are other good reasons to do volunteer / community work that have nothing to do with an academic application, so you should certainly feel free to do so.  Just don't think of it in terms of improving your application.

Added: The OP asked for followup information from an applied perspective.  I can only give the perspective of a math department that admits some students who study applied mathematics.  In our department, the requirements for applied students are only slightly different from all other students.  In particular, see here for qualifying exam information, which shows that all students are required to take both real and complex analysis and (algebra or topology); students who do not want to take both algebra and topology can take probability (which by the way is very close to real analysis and quite challenging) or numerical analysis.  I believe that the vast majority of students in my PhD program specializing in applied mathematics have taken the abstract algebra qual.

My department has recently added on applied area of emphasis for its undergraduate math major.  In this track, abstract algebra is not requrired (though it is required for all other majors): see here for some sample programs.  On the other hand, as a student interested in graduate study you need to know that these major requirements are very intentionally designed to be as minimal as we can get away with.  We want to have more math majors, not less.  Students who want to take more classes are always free to do so.  Moreover we tell our students that for certain career paths they should take more classes.  Especially here we recommend further classes, including two semesters of algebra.  This advice is not specifically targeted at students who are interested in pure mathematics.  And by the way, there are many kinds of applied mathematics which you would be absolutely locked out of without an undergraduate background in algebra.

  I do not think I will need abstract algebra directly, but I'm slightly ignorant.

It is very unlikely that any undergraduate math major can say with any assurance what kind of mathematics they will not need in their PhD studies or later career.  Making this kind of decision is a kind of negative investment in the future.

  Some schools of interest do not have that content in the curricula.

Please let me know what specific programs you are looking at.  That would be useful information to me and I could give you more targeted advice.  In particular, all of this advice is predicated under the assumption that you are applying for graduate study in a mathematics department in the United States.  If you are interested in an interdisciplinary program, or e.g. want to do mathematical biology from a biology department, then things will be very different.  If you are applying to a university which has separate programs in pure and applied math -- or has separate posted admissions requirements -- then things will be different again.  But for general admission to a math department in the US: not having abstract algebra will be a huge point against you, I believe.


Interview for postdoc position in mathematics I have an interview for a postdoc position in Mathematics at a very good university in the UK. The interview committee comprises a maths professor (not in my field, which is analysis of PDEs) and three other professors from other scientific disciplines.

I do not expect any technical questions since they are not in my field. But I am worried they will ask me: "why is your work important/useful/relevant?" in the context of applications to real-life. What can I say in such a situation? Also does anyone have any general advice to what such a panel might ask me?

Why should you be worried? This is a pretty standard postdoc position interview question and you should be prepared to answer it.

I echo P.Windridge's comment:- your specific answer may be less important than a clear indication that you've considered how your research fits in, extends, challenges, tests the current state of the art in your field.

You've set the problem of answering this question in the context of "real life", whatever that is. For your specific case, I would have thought the "real life" applications of PDEs is easily referenced.


Tips to organize LaTeX presentations for a semester I am giving my first course this fall and, as a LaTeX enthusiast, plan to prepare my slides in LaTeX for all the usual reasons.

For those of you who also do this, I wonder what resources you use to manage your slides for a semester. For ex., do you have one "master presentation" with different "chapters" for different classes or some other strategy?

What's your best practice?

I use a different file for each topic. Each file covers 1-2 hours of teaching, more or less.

All files are in the same per-course folder, and their names start with numbers which define the order of the topics, for instance 1-introduction.tex, 2-polynomials.tex, 2.5-rationalfunctions.tex, 3-analytic.tex... If I have to insert an extra topic at the last minute (or in the next year), I can do it by adding decimals like in the example with 2.5. :)

Dates are a bad idea because if you want to re-use the same material the next year you have to change all file names. :) Lecture numbers can also be quite fragile, so I prefer to use topics like this.

I just copy the same preamble over to each file, because I don't change the preamble too frequently. If I had to make more frequent changes to the preamble, probably I'd consider a custom Latex class, but for now it works for me like this so I keep it simple.

I suspect that this works well for me only because I have a good set of tools though: for instance, a file manager that uses natural sort order and an editor that can compile Latex without clobbering the directory with lots of .aux and .log files.

Another tip is: sometimes you notice weak points and mistakes only after giving a lecture. If there is a chance that you will be giving the same course next year, keep a file called notes where you note down all the things you'd like to change.


Is IJCA a valid open access journal? Can someone let me know whether IJCA (http://www.ijcaonline.org/) is a valid open access journal to publish our research work?

BR,
Tharindu from Sri Lanka

This journal is in Beall's list of predatory journals, which is a strong indicator that you should not publish your work in this journal.  (This question and its answers explain what a "predatory" journal is.)

You might also be interested in the answers to this question, which describe how to evaluate the quality of a journal.


What is minimum GPA for getting PhD in Germany? I'm in the last year of my MSc in computer engineering and I want to apply for a PhD in Germany. I have a reasonable resume and have a published paper and my master GPA is 16.5/20, but my bachelor GPA in not so good, it is 13.5/20.

Can you tell me how much is this important? Do I have any chance?

As flo said, it totally depends on the university.

In principle, you can become PhD student at any German university if you

Have someone eligible (normally a professor in the department) who declares that she/he will supervise you, and
You meet the requirements from the examination regulations for the PhD.

In the majority of cases, the examination regulations can be found on the web. Many departments do not list a formal "grade" requirements, but some do. Typically, the grades are only given in German style, so there is room for interpretation when translating foreign grades. GPAs are pretty much unknown in Germany. Admission officers will look at the grades (e.g., A-F, where F means fail) and if the institution where the grade has been awarded is "OK". Summary grades are expressed in the same system as the individual grades. To make this part of the answer complete, as you are probably aware, it is normally a requirement to have a Masters degree before you can start with a PhD.

Structured programs, such as graduate schools, typically have their own rules on top of these. Again, standard vary, and you should be able to find some information on the home page of the respective graduate school.


Nominating a professor for a fellowship I know a professor who is really brilliant, but also very modest. This professor has helped me to progress in life. Now, I want to express my gratitude by nominating him as ACM Fellow. However, I have no experience in situations of this kind and I would like to ask you a couple of questions:

When you are nominating a professor for a fellow title, do you need to ask permission to him? or should I keep the process in secrecy?
In case the fellow title may not be granted to him, could this fact hurt his reputation?
Is it ethical to try convince other professors to support my nomination application?

First make sure that you have read all the regulations for the award (in the case of ACM fellows: http://awards.acm.org/fellow_nom_guide.cfm). You see that the nomination in this case is quite some work. Especially question 3 is already answered there: You need five endorsers. Hence, it is expected that you "convince five people to support the nomination".

For question 2 it seems pretty clear that the ACM fellowship is really very competitive, so not getting the fellowship will not really hurt (not getting the Nobel price is also not a big deal for most people).

For question 1: In my opinion you do not need to ask for permission. The awardees do not have any obligations so they will not have any burden from this award. I also think (but I am not sure about this) that is usual to not inform people that you want to nominate them. However, you need to provide a lot of information to the award giving institution and it is also not unusual to ask the person that you want to nominate "I (better: We) plan to nominate you for this award and would appreciate if you could provide us this and that information to prepare the nomination."


How detailed should proofs be in a mathematical PhD thesis? I heard this suggestion from a mathematics professor:

In writing a mathematical Ph.D. thesis, it is far more tolerable to be tediously-lengthy than having a gap in the proofs.

I think what he means is that whenever in doubt, adding more details to make the argument clearer is always better, even if sometimes doing this may make the proof too wordy.

Now if I really follow his advice literally, it seems there are too many details for me to write. For example, I don't even feel safe to write "the case n=1 is trivial" when proving by induction, or "by a direct calculation we have the following result". Another example is, whenever writing a commutative diagram (some of my diagrams are 3-D), I doubt if I need to prove that every small triangle or rectangle is commutative. (Actually I have asked this question but have received no answer so far.)

Thus my question is: How detailed should be the proofs be in a mathematical Ph.D. thesis?

I usual give the advice

  If something is clear, just write it down clearly.

Of course there is a caveat: What is "clear" clearly depends on the reader, and also what is considered a "clear explanation" certainly depends.

But the message is: If you are tempted to write "The case $n=0$ is obvious." think a minute about the explanation and how to write it down. If you then think that writing down the explanation does not add anything, leave it out.

But in general, I would say, being more verbose is the better option.

Another test you could apply is: Write down "obviously…" but note down a longer explanation somewhere else. After a week or two reread that part and try to recover the result again. If you don't have any problem than you are probably fine without a longer explanation.

Some resource that may be helpful for your proof-writing skills is the talk given by Leslie Lamport on proof-writing last year at the Heidelberg Laureate Forum: Here is a blog post about it and the whole talk is here.


Specialise now or broaden knowledge? I am currently an undergraduate student in mathematics coming to the end of a 4-year Bachelor degree. I have strong credentials (good marks, plus research and teaching experience) and have been doing research with one of the leading Professors in my area since the second year of my undergraduate degree. I have a couple of publications with this Professor as well and most would say I have a very strong foundation to do good research in this particular area of study during my Masters, PhD and beyond.
I have been keen on learning/studying another area of mathematics for a while now that has connections with my current area of study, though, would require me to change to a different area of research. I'm considering changing to this other topic of research for my Master's degree, both because I'm interested in doing research in this particular area, and also it would be good to broaden my knowledge at this stage of my career. Though, my current supervisor and mentors seem to have high expectations for me to continue here, and they have relatively large research group set up at my current institution that provides me a lot of undivided support.
Would it be silly for me to change universities and research areas when I already have a good setup now, or is this stage of my career a good time to move, learn and try different things before a PhD? I feel it would be better to stay in my current area as I have a good foundation here and am quite knowledgable of current research, though, I don't know many people who specialised in their research area from 2 years into their Bachelors degree. Is it a risk making this change seeing as I would have to get up to speed in the other area of research, or am I overthinking things?
N.B. Master's degree are mostly research based in my home country, minimal coursework is completed.

If you are on a trajectory that will let you quickly complete a doctorate, then I'd suggest that you don't redirect at this time. This depends on your country, of course, and the requirements for a doctorate. In the US, having a broad enough knowledge base that you can pass qualifying exams is a necessity and is also an advantage in that you would be able to teach nearly any undergraduate course after completion. But standards differ.
But you can always broaden your view later if a narrow view is indicated at present. And you can then do so without compromising career goals.
I'll note also, that having insight into one area of math doesn't necessarily translate easily into insight into others, even if they seem quite similar in some ways. I (retired now) had great insight into Real Analysis, but very little into Abstract Algebra. I could fight my way through algebra but it wasn't fun. So, broadening may mean a longer path than you need to travel at this instant. But math can also be synergistic, so ignoring other sub-fields, long term, probably isn't optimal.
If you are well supported in what you are doing now and the end point is reasonably in sight, then it is probably best to keep on keep'n on.  But note that this is mostly just opinion, and others will differ.


Impact factors of preprint repositories I'm wondering if the growing catalogue of preprint repositories have known 'impact factors' similar to those of popular print journals. If so, can anyone highlight them?

Even if there are services computing them, the impact factor for a preprint repository would not be useful.

Impact factors represent how many citations an article gets on average within a certain period of time. As such, they are supposed to be a rough metric for the selectiveness of a journal. If a journal is highly selective, then only highly impactful articles should (in theory) make it in, driving the impact factor of the journal up.

Now a preprint repository is explicitly designed to not be selective - Every paper gets in (possibly under some conditions that are hardly comparable to peer-review). As such, the impact factor of such a repository would not measure anything of interest.


Asking a community college professor for a letter of recommendation I am applying for a master’s program and required to obtain two letters of recommendation. Originally, I asked two teachers from the private college where I got my BA, even though I did not know them very well while I was in school. I was one of those students who studied on my own and got good grades but never reached out to professors after class as I didn’t feel like I had to.
I received a Letter of Recommendation from one of those professors, and unfortunately it seems very generic, as if it was from a template, and doesn’t mention how I am particularly prepared for my master’s thesis.
On the other hand, I have gotten to know one of my community college professors much better. I voluntarily took his research methods class after I graduated to prepare me for the research I would be doing in the master’s program. I have also seen him during office hours and with his help I am planning on presenting at a conference in the spring. He has also taught at a more prestigious school (UCLA). He has agreed that he would be able to write me a letter of recommendation.

Would this be preferred over a more generic letter from my private college?

This is hard to weigh without knowing more information about you, but it can be addressed in a general way.

One of the biggest pieces of advice I give to undergrads is to develop a relationship with professors they hope to earn letters of recommendation from, including going out of their way to take extra classes/do extra work with them.  Now that that ship has sailed for you, I would lean toward the community college professor.

You don't mention the other letter you got from your BA institution, but I presume it's a solid one.  That allows you a little more leeway on your second letter.  You can already show strong results at the BA level, so getting a very good letter from a community college professor (or, e.g., an employer from the private sector in your field) that knows you well will look better than the generic letter.  People who read these letters know what a generic letter looks like, and are certainly able to "read between the lines" and assume this letter doesn't say much good about you.

I would be concerned if none of your letters came from your BA institution, so if my assumption isn't correct about the other letter, then I would say you probably have to use the generic one.


How conceivable is it to research independently while working in a non-research role in industry, to improve my profile for graduate admissions? I'm toying with the idea of finishing my undergraduate degree and then entering industry for a short while. If I spent three years and earned enough, my thought is that I'd soften the burden on my parents of financing the sinewy road -- filled with costs and time -- I'm willing to take in earning a PhD. If I earned enough after three years, then I'd feel uninhibited, for example, in getting two masters, waiting another year to apply for a PhD if I were rejected the previous year from one, taking a year off to research and so forth.

Spending a few years to earn money seems good, except that during these years, it's dubious whether I can work towards making myself a stronger graduate school applicant (most importantly, by doing more research). Also, any research done as an undergraduate would, I fear, go to waste. If I returned for a masters at my undergraduate institution directly after finishing my undergraduate, by contrast, I could continue whatever I was working on as an undergraduate.

A possible remedy is to research on my own (or under a willing professor's supervision) while I work in industry? Have others tried out such plans? Are they generally advisable?

Please Note: My question is different from the suggested duplicate, because I ask about the possibility for a student (and not a PhD) to perform research on the side (after working hours) while working in a non-research role. The duplicate question resolves whether someone employed in some company's research division can also research themselves independently.

It is hard to do both research and industry work especially something that is not related to your main research topic. I work as a database administrator and software developer. After I finished my undergraduate degree, I started working in industry in 2003. Fast forward to 2016. I used 3 years to finish a master and used about 9 years for a PhD. I am about to finish my PHD, but it was hard to do so.

I offer following advices. Note that these points are mostly useful for PhD. You can and most people do finish your master degree while working.

Try to find a company which do R&D, and try to align your thesis subject in your company's vision. This way even when you work for your company related work at least you learn something about your research.
Try to find a company which allows about academy work leave in its employee guide. Even you talk about your academy leave when you interview about your job, another manager may not allow it. But if company has a clearly defined policy about this, they have to allow it.
Be prepared to spend more time than others. Think about it. A normal PhD student in my country spend 4-6 years for PHD. In some countries, PHD does not require course work and qualification exam; thus it may took only 3 years. But this is their only job. If they spend 20 hours (reasonable for 45 hours) every week for their PHD. This means that they spend 3120( 3 years), 4160(4 years) , 5200 (5 years), 6240 (6 Years) to finish their PHD. You will not able to put 45 work hours + 20 PHD hours. You may be able to put 10 hours at best. This means that if you do not put extra effort in holidays and your leaves, you will need two times more time to finish PHD.
If your institution require Qualification Examination, be prepared to take leave from your job. It will be near impossible to be successful in this exam with full time work. I changed my job to part time (2 days) for 6 months for this examination.
Be prepared to fail. If you need industry work for your livelihood, sometimes you have to put your work ahead of your PhD. This is especially hard for normal academia people to understand.
Similar to above point, try to find an advisor who understands your situation that sometimes you need to put your job ahead of your PhD. My advisor is similar to me that he changed his career from industry to academy. But I saw very different attitude from others in my university. And this is from a university where I pay tuition with my own money. I had an argument with department head about this subject. He told me that I need to put my PhD first, I told him that if I could afford that I would already have done that.  I know that I would have host of other difficulties with other universities. Some universities in my country does not accept working PhD student.
Be prepared to give up a lot of your social time for your PhD.


GNU Free Documentation License I want to use this picture for one of my presentations. Do I have to mention the author there, and if yes, how do I mention him? It will be my first talk in English, so I don't really know how to correctly use/cite a picture from someone else.

As it says on the page you linked it, attribution is required. So, all you need to do is add the author's name under the image in your presentation.

The important thing here is that if you do not include the author's name, you are implying that you create the graphic and if you did not, then you should attribute it to the true author.


How much contribution justifies being a co-author of paper I am part of a Computer Graphics lab where I got to help a small team already working on a paper, by assimilating/cleaning up some data sets which they required. I was also part of some discussions and shared my views whenever possible trying to help them in analysis phase. I have hardly any other contribution other wise.

Going forward, I am now being offered to be one of the co-authors of the paper. I kind of feel that I haven't really done enough and its almost reaching it's ending stage anyways, so not much chance in future as well.

Other team members are making a point that it won't be just on their part if this work takes up my time even when I don't get to be an author. I am in kind of a moral dilemma as I don't feel my contribution is enough.

Q1. Is just helping out a good enough reason to be a  co-author ?

Q2. How do I justify to myself if I have really contributed enough ? Or should I let the team decide if my work is sufficient ?

Q3. In general, are their any tangible points/guideline I can verify my contribution with ?

The standards for co-authorship vary greatly from field to field.  In some fields, you can be a co-author merely by supplying a useful reagent, where in others you need to be much more heavily involved with the actual work.  I don't know what the culture for computer graphics in particular is, but no matter how you draw the line, the general principle is the same everywhere:

The authors of a paper should be precisely the people who meaningfully contributed to the success of the work.

Some advocate for the tighter definition laid out in the Vancouver Protocol, which requires every author to be a significant writer of the paper as well.  That, however, has some serious problems, particularly in tending to unfairly exclude students from authorship.

Applying this to the case of your authorship, the answer is not immediately obvious from your question whether you should be an author or be named in an acknowledgements section, because it depends on the value of the work that you did and that's something that only you and your co-authors are in a position to just.  For example, if your work with the data set was just reformatting it from one format to another, then it's clearly not worth authorship.  If you did some real curation of the data set, e.g., evaluating the information to remove artifacts, and this made a big difference in obtaining the results, then authorship is certainly reasonable.  Note that the amount of work that you did is not actually a good measure: if you whipped up a curation script in a few hours and then let it run, it's no less valuable than spending months inefficiently curating by hand.

Finally, it's fine to err on the side of inclusiveness.  If your contributions are a borderline case, and the primary authors found your work valuable enough to merit a co-authorship, nobody will be hurt by including you in a minor author position in the author list.


How do I tell my current research advisor I want to work in a related field with another professor? I am currently an undergraduate student looking to work on a senior thesis. Over the course of the past summer and sporadically throughout the Fall semester, I worked with a professor in extremal graph theory. There has been some (from my point of view) subtext between us that I would continue this work into my senior year, though this was never explicitly said.

However, I want to pursue something more algebraic, and have been in contact throughout the Fall semester with a professor working in algebraic graph theory.

How do I tell my current research advisor I want to work in a related field with another professor?

Just tell him. Be polite. You're over-thinking this.


How to deal with past unintentional and unpunished plagiarism? I am currently a master’s student and I cautiously and properly cite in my essays and works as per Harvard’s guidelines. However, I only learned how to properly cite just this year which made me go back and look at my BBAs graduation projects (I have two licenses) and, frankly, they are horrible when it comes to referencing!

To make a long story short, these projects are made up of ‘copy-and-paste’ chunks from online websites, Wikipedia pages and some books, all without putting quotation marks, however still referenced at the end with (some of them) a poor style. Back then, I never thought about it and was like, yeah I am just referencing the ideas. I was not aware of direct quoting, quotation marks (save for small definitions), proper paraphrasing and a proper style of citation. It is important to note that it was totally unintentional to plagiarize, just out of ignorance.

What to do now? Frankly, I feel so guilty about it since I am an ethical person. Although both projects were positively accepted (one of them is a technical one; a website, so the report was only to define some concepts), I, first and foremost, do blame myself for my ignorance and carelessness, however I also blame my instructors for not throwing the projects at my face and telling me to go home and correct everything! What can I do now? No instructor told me anything about it and this was four to five years ago. However and ethically, I am suffering because of this, I feel like I don’t deserve to be a graduate student (unlike what my current instructors think as I am seen as an excellent student at this part of my life and my current master’s grades are excellent and I even cite during exams!) and should just drop out and not use my bachelor degrees in life, yes I feel that way. Why to bother pursuing an MBA and even a PhD if my BBAs projects were built on academic dishonesty (even if unintentional)?

I am so glad that I learned how to properly cite this year just before my master’s thesis so that I can produce a well-written one, but again, I am not motivated due to the aforementioned reasons.

First, it is unreasonable to blame your instructors.  For what reason?  If they had done something years ago, you wouldn't feel bad now?  Probably it was not obvious to them that you had plagiarized.  (Plagiarism can be more obvious or less obvious, depending on many factors.)

Second, people make mistakes in life, and not all mistakes are fixable.  You just have to do your best to be honest and correct now and in the future.  You might consider contacting your old professors to let them know what you did, and that you now realize it's plagiarism and that you are sorry.  If you need to do this to feel you are "deserving" of your situation, you could also redo your projects and send them to your old professors, but this is not ethically necessary.  Who among us deserves the fortunes granted us?  Not I.  I can only appreciate them.


How do tuition and credit accounting work in an independent study course? I've been talking to one of my professors at a Master's program about enrolling in an independent study course under his supervision.

(An independent study course is a course in which a student engages in guided study on some topic under the direction of a faculty member. Students formally enroll in such a course as part of a degree program, just as they would for a traditional course, and it appears in the students' transcripts, academic records, etc.)

However, it's not clear to me whether independent study courses work the same way as regular courses with respect to tuition and credit accounting:

Tuition: Am I expected to still pay tuition for independent studies?

Credits: With traditional courses, there's typically some quantitative relationship between the number of credits a course is "worth" and the contact hours it involves. For example, a 4-credit course involves a certain amount of class time.

With independent study courses, where there are no fixed contact hours, is it common for institutions to have some expectation of how much time a student is supposed to spend on the course, per credit hour? For instance, that a 1-credit course expects about N hours a week from the student.

Since you ask about 1 or 2-credits, I'm assuming you're talking about doing an independent study course with the professor and not creating your own independent study track.

Independent studies (also called independent readings, directed research, tutorials, etc.) are essentially micro-classes of one or two students. You come up with your own reading lists, discussion topics, or projects -- subject to the approval of the professor. Whether to list it as 1 or 2 credit hours (or in my university 3 or 4 credit hours) is up to you. In general, you should plan on spending as much (or more) time in your independent study as you would with any other class.

From the registrar's perspective, it's just another class that you are taking. If you pay a flat fee for up to 5 classes a semester, then it can be one of those 5 classes. If you pay a fee for each credit-hour, then it would count as one of those paid credit hours.

I do independent readings with the undergraduate seniors, master's students, and PhD students when they come to me with topics that are of interest to me, but aren't in the regular course catalog. Since faculty do not get paid to teach independent study courses (we don't get any more money for doing this, nor do we get course releases for it), we're essentially do them out of the good of our hearts or because the topic is particularly of interest to us and/or we'd like the interaction with advanced students.


Which Masters is right for me? I am an undergraduate student in Canada doing a double degree concurrently, a B.Sc (Bachelors of Science) and a B.Eng (Bacehlors of Engineering) over 5 years. (8 years down to three at the price of my sanity? Sure haha!).

My Major in Science is Physics, and my Discipline in Engineering is Electrical/Computer.

When it comes to picking my masters, I have three options:

M.Sc (Science, thesis based)
M.A.Sc (Applied Science, thesis based)*
M.Eng ( Engineering, project based)

From knowing nearly nothing about these, I think the M.A.Sc sounds right for me, sort of a "middle ground".

I want to go on study quantum computers, specifically to apply the principles of quantum field theory to microprocessors and develop quantum computing hardware and software.
(I work as a computer programmer alongside my studies, and I've been a professional polyglot programmer since I was 16, and a hobbyist since I was 11)

My question is, which masters would help me more on a path to a Ph.D, and eventually to a job in academia?

A fellow undergrad suggested I do a double-masters to compliment the double-degree, is this possible? Would it be useful to me at all?

When it comes to picking my masters, I have three options:

  M.Sc (Science, thesis based)
  M.A.Sc (Applied Science, thesis based)*
  M.Eng ( Engineering, project based)

The letters in your masters degree do not matter. In other words, you'll never see an M.Sc. or an M.Eng. specifically asked for in an application call ... you'll only ever see "Masters". As such, your degree could be called an M.Xk.Cd. and nobody would really care. It's the topic and quality of your masters matters most!

If you want to work on quantum computing, then you should look for a good masters programme in either Computer Science, Electrical Engineering or a relevant field of Mathematics. These are typically M.Sc. or M.Eng. courses (again, not that the letters matter!).

A research masters is usually preferable, in that you may even get a publication or two which will help with PhD applications ... or you may continue in the masters programme and graduate into a PhD programme if you are happy with your supervisor.

On a side note, I would encourage you to be flexible in your interests. You quote "quantum computing" as an interest but it can often be unfeasible to get a PhD you like in a really specific area. I think at this stage it's important for you to decide what discipline you want to pursue (Comp. Sci., Maths, Physics, etc.). Having a sub-field in mind is great, but don't plan your future too rigidly around that.

  A fellow undergrad suggested I do a double-masters to compliment the double-degree, is this possible? Would it be useful to me at all?

Of course it would be useful. :)

But as to whether it would be worth your time, I would say absolutely not. See (1).

(1) Masters + 0.5 × PhD ≫ 2 × Masters


How to cite (Chicago author-date) papers your paper is about I'm writing a philosophy essay. The essay is required to answer a particular question by analyzing, in turn, four particular philosophy essays; the essay needs to follow the outline below.

Restate the question.
Introduction.
Analyze essayW by Mills
Analyze essayX by Shue
Analyze essayY by Locke
Analyze essayZ by Hospers
Answer the question with information from essay analyses.

Where do I need to write (Author, Date) in my analyses? Each analysis will be about an essay, and will reference that essay in most of its sentences. Do I need to include the same citation in every sentence that references that essay? That seems like it would aggravate the reader.

I often see this issue when reading student lab reports in psychology. So for example, a student is paraphrasing a number of claims made by Smith (2000), so they write:

  X is related to Y (Smith, 2000). The cause of some stuff is blah blah (Smith, 2000). Then the system does that (Smith, 2000). But several reasons for this include A, B, and C (Smith, 2000).

One problem with this form of writing is that it does not make explicit the link between statement and citation. There are many possible links between citation and statement (e.g., Smith asserted a claim; Smith conducted research and obtained a finding; Smith is one reference among many where a generally accepted fact in the field is asserted; etc.).

In general, if you are writing critical commentary about a particular article, then your writing style will need to be explicit about claims made in the target paper and what is your analysis. One way of restructuring the text is to make the author explicit in the text. E.g.,

  Smith (2000) proposed that X is related to Y. He found evidence that the cause of some stuff is blah blah. He went on to show that the system does that. He proposed  several reasons for this including A, B, and C.

Note the full in-text reference is provided in the first sentence. The remaining sentences make it clear that the propositions are related to the citation in the first sentence. Furthermore, the connecting words (e.g., "proposed", "found evidence", etc.) provide further information on where the propositions came from (e.g., theory, mere assertion, empirical evidence, etc.).


What to do when there are no courses available to help with my research? How will it affect me? I am a first-year mechanical engineering PhD at a Canadian university. I had by undergrad and a master's degree in materials engineering. My previous master's research was mostly experimental with some implementation of a mathematical model in Matlab and Fortran. All graduate courses were on programming or simple mathematical modeling or experimental analysis.
Now for the PhD degree, my research topic involves continuum mechanics, variational mechanics, and finite element analysis. There are no courses available in my university for the next two semesters. I had taken an "advanced" course last semester which had some continuum mechanics in it, but I found it fairly introductory.
My advisor says that in graduate school one must learn topics by oneself. And no one will look for these courses in the CV if one can publish papers using the methods.
I am starting to learn these from online courses and books. But I feel inadequate because of my poor undergraduate background in mathematics and these topics.
My PhD funding is for three years (can be extended to one more year). I need to start my research by the second year. I don't know what to do.
My advisor just points me towards relevant literature. I wonder if she has my best interests in mind.

Part, or most, of a PhD is about self-learning, so you have to step up and work on those subjects you need.
A PhD is usually to push the boundaries of knowledge in topics / areas etc so learning methods or techniques relevant to moving your research forward is what you have to do - simply said your supervisor is correct.


Remote PhD Using My MSc University's Lab I am currently pursuing my MSc in Applied Engineering, concentrating in Mechatronics and conducting research in cloud-based heterogeneous robotics. My current university does not have a PhD program for engineering.

Are there universities that would allow me to remotely enroll in their PhD program and conduct my research using my current university's equipment?

It depends on the country and the PhD program.

In the UK, you could look for a relevant supervisor in nearby universities (e.g. a couple of hours drive away) who might be interested in your proposed project and might be able to fund it (even if you don't need lab space, you'd pay fees etc). You would probably need to meet with them (and other academic supervisors / trainers) every quarter, with more frequent email / phone / video contact - depending on the particular universities rules & regulations. I've seen lots of people do these sort of multi-site projects.


Is it normal to keep changing research objectives in PhD? During my first year, my supervisor advised me to have four objectives that lead to four contributions to the research.

Throughout the journey, until I'm now on my final year (in computer science), I realize myself to keep changing my objectives as the needs of the research keep evolving. And, as the research has evolved, some objectives do not make any sense due to some reasons such as it's not so significant, too simple, and redundant.

My supervisor is always asking how many of objectives (out of four) that I have achieved so far? I can't really answer as it has changed from my first to second, to third a year.

So my question is, is it normal if I keep changing my objectives without sticking the those I outlined during my first year? And, it is still okay to change objectives when I'm now in my final year?

So my question is, is it normal if I keep changing my objectives without sticking the those I outlined during my first year?

Yes.  It would be unusual if you did not improve your objectives.  Improved objectives is a symptom of improved research.

  And, it is still okay to change objectives when I'm now in my final year?

It's not okay to start your research over from scratch when you do not have enough time to complete new research.  It is okay to discover that your existing efforts achieved goals you didn't think of when you started (but scientists should avoid data dredging).  In other words, it depends on the details.


Variation in length of MSc studies I have acquired a 4 year BA degree in one of the social sciences. At the moment, I'm considering applying for MSc outside of my country (I'm Non-EU citizen and I will apply for MSc studies in EU country).

The University where I want to apply has 3-year BA programmes and 2-year MA/MSc programmes. However, in my country I finished a 4 year BA programme with a total of 240 credits and MA studies are usually with a duration of 1 year. I really don't want to study 2 full years for something that I believe I could finish in a considerably shorter time (one year). Also, I already have the necessery credits for the first year of the MSc programme.

I would like to know how is this handled? Does the number of the acquired credits I have matters, or is the official length of the MSc programme that counts?

This is not a universal truth, but my experience in researching Master's Programs is that the main difference between a 1year and 2 year Master's program is the research component.

1 year programs tend to be primarily course based, with a shorter project, if any. Very seldom will there be a 2 year program consisting entirely of classes. Instead, there is usually a thesis, project, essay, etc. that can last around a year.

No matter how skilled you are, research takes time. So a 1 year Master's program will necessary mean a more shallow project, whereas a two year program alloes for more depth, and is more likely to result in publishable research.

So when choosing a program, ask yourself what you're trying to get out of it. If your main interest is classes, 1 year is fine. If you want to be a researcher or tackle an ambitious project, 2 year will probably be better.


How to mention a professor that his CV link in the university website do not work? I want to e-mail to a professor in a US university to get a PhD position. The links of CV download and personal homepage for all the professors in the specific faculty do not work.
How can I mention this fact in my email?
Actually, I want to mention this to make the professor aware of the fact that I have checked his page and not chosen him by chance!

First, check you are on the correct (current) website. It may be that the university/department changed their websites and you landed on an old version, which is not updated or already partly removed.

If you are sure you are on the correct page, and it is the case for all professors (and faculty) that links are not working [as you write], contact the webmaster rather than the professor. There will be a more general problem that is not to be solved by the professors themselves.


Regarding applying to another university for PhD during the first year PhD program at a top research US university I've received my Masters from one of the best universities (may be the best actually) for my area. Moved to another top university as my professor moved.

However, during this process I realized that my advisor can do a better job at handling the lab and careers of the graduate students. The current graduate student is in depression because of the work pressure and never spoke about it until recently. PI had instances of graduate students leaving the group because of the same issue.

The project I'm working is just fine and doesn't seem to be worth all the mental turmoil. Feeling a bit uncertain about the future of PhD with the PI.

Thought of transferring to another lab, but certain collaborations of the PI with other profs wouldn't facilitate that. I'm left with options of a change in the area of interest or move to another major or university.

So, for me to apply to another university or another professor, the major concern is the reason behind the move. I'm not quite liking the toxic environment in the lab and the way the PI advises and want to move out of it. However, the concern is that I do not want to mention about this directly in my SOP and in my meetings with other professors. As this might reflect badly on me in return. So I would like to know what is the best way to deal with this situation. Thanks.

Although more experienced heads may give alternative advice, my recommendation is to focus on what you want to research rather than the personal relationship reasons you have.

Remember what the SOP stands for: Statement of Purpose, why are you pursuing a PhD?

Professionalism aside, ad hominem attacks are not the subject of interest when you meet with potential advisers: you are the subject, what you are interested in, where you’d like to go, how you would approach a problem or issue.


Using a statistical method in an applied context for (probably) the first time. How do I convey this? I am a graduate student in statistics, writing the methods and data analysis section of an epidemiology paper. I used an obscure but highly relevant statistical method to analyze our data. I genuinely believe this is the first novel application of this method outside of toy problems in highly theoretical paper.

What I want to say is: Previous research on METHOD XX has been limited to statistics and econometrics literature

This seems too sweeping a claim for me to make though. It's entirely possible that someone, somewhere has used this method before. It is also a nightmare to cite. How do you cite the absence of evidence?

So, what is the best way to convey this? Is it as simple as tempering my initial statement a bit: Previous research on METHOD XX has largely been limited to statistics and econometrics literature. Should I get rid of this statement all together?

In lots of papers I've seen a phrase:

  According to (or to the best of) the author's knowledge, this is the first time that method XX has been applied to YY.

which seems fair and safe enough.


It is worth to get a bachelor degree in education? What can I do with a bachelor degree in education and what are the pros and cons of getting a degree in education?

If you want to teach at any level, even in industry, a degree in education is valuable, and, in many cases, especially at the lower levels, is a requirement. It can also be a gateway to graduate degrees for a person who wants to do educational research, especially in academia. My former spouse, for example, was professor of educational psychology, a common specialty.
In most places in the US, perhaps all, a bachelors is required for a teacher. For elementary education that mostly means a bachelors in education, but there can be exceptions. For higher levels it may be somewhat less of a requirement that your degree be in education specifically, though you probably will need to take courses in education to advance in either elementary or secondary level teaching. Usually, the credits you are required to learn can also be applied to a masters in education.
But note that a degree in education has many possibilities. There are differences in programs that focus on elementary education and secondary education, for example. And some programs, geared toward teaching adults, can be valuable for a person wanting to be a "trainer" in industry.
For university teaching, such qualifications are seldom needed unless you want to teach in an education department. But if you want to teach math, for example, in a university, math degrees are normally needed, not education credits. But a math degree, alone, will probably not qualify you for teaching at the elementary level and may or may not at the secondary level. And, again, someone teaching secondary level math will probably be required to earn several education credits to keep their job, though, perhaps, not to get hired initially.
Whether it is "worth it" or not depends on what you contemplate for your career.


Am I eligible for a fellowship doing interdisciplinary work? I'm pondering a Masters (thesis) in Computer Engineering after I graduate undergrad. I also have a subject matter I want to research that will probably require a fellowship in order to conduct my Masters.

I want to explore a section of Computer Engineering that I can apply to Sociological and Ethnic studies ( the particulars of what that is isn't important here ). I have a sociological research institute  in mind that is perfect to help my research into what I want to do for my Masters. I want a fellowship in this institute because its the preeminent leader in its field and it intersects perfectly with what my research would be about.

The thing is, I don't know if they would even take me in the first place. Yes, I have a degree in Sociology but my Masters work is in engineering. Would it be in the norm for a research institute ( especially one in the Social Sciences ) to offer a fellowship to someone who isn't in their field? I'm going to be a Engineering Master's student who wants to conduct research in a Social Science field.

You sound like a perfect candidate, given your major and your further plans. Many social scientists like to understand problems more than fight about academic boundaries--at least if they are at an institute that describes itself as concerning the "Social Sciences" rather than a particular discipline.

Do look carefully at the guidelines to see if they specify which programs they will support. If they are vague, you may want to ask the program officer for the fellowship about whether it is designed to fund such cross-disciplinary study, and/or if there are "computational social science", etc. programs to apply to that would be purely in scope. (You can look at lists of past awards to see the variation so far.)

If you have a strong start in computer engineering and you can convincingly convey your dedication to use it for the social science purpose you mention, as well as show that the degree program will let you, then you could be a strong candidate. (Unless the fellowship is specifically toward master's degrees, you may face tough competition from doctoral students, though not because you are on the wrong track.) Good luck!


How to deal with impatience when starting off in research? I am half way through the first year of my PhD (physics) and I find myself faced with the following problem related to research discipline and learning new techniques while doing a PhD. The problem is probably specific to my personality, but I am hoping that some people can relate and provide their experiences/advice.

Essentially I find it hard to actually learn anything new, especially when it comes to techniques. Let me clarify by describing how I read a paper

When reading a paper I usually read just enough to 'understand' it on a functional level. I.e. afterwards I know: a) What has been done b) How it fits with some other things I know c) If it is useful for the research my group is doing and the projects I am working on. When c) applies I read 'in more detail'. That usually just involves following the derivations on a functional level. I.e. afterwards I would know a), b), c) for every part of the derivation.

The problem is that I don't actually learn any techniques this way. I could not sit down and do what has been done in the paper, even though I could tell you exactly what has been done in the paper and (for the ones I read in detail) how it has been done.

That isn't too bad if you want to come up with new research ideas, I even found that you can solve some problems this way, but you can't actually write the solution down. The latter unfortunately is very necessary if you want to write a paper.

I have a similar problem with textbooks that I was going to describe here, but for the sake of brevity1 I will spare you the details.

To me the situation is a bit worrisome, especially because that did not happen to me during my undergraduate. When doing supervision work and exercises I always felt like at the end I understood things on a level where I could do them again. When people asked me questions about it I could not only tell them how to do the question in principle, but also point out technically details that you encounter along the way. I am worried that I will never reach such a level of understanding in any new areas the way I am approaching it at the moment.

I suspect that one of my problems is that I have become really impatient somewhere in between feeling the pressure of trying to produce valuable research and trying to learn things as quickly as possible. This creates the feeling that I am unable to 'sit down' and 'actually do something' 2 .

So, reading my question above again I don't feel like I have pinned the point down very well at all, but this is my 3rd try, so I'll go with it and see if people have some advice. The title question is going to be: How to deal with impatience when starting off in research?

 1 Really not an appropriate description of this question anymore...

 2 Don't get me wrong, I am not procrastinating. I am doing a lot of work and I also enjoy the work very much. It is just not very effective and when I think after each day what I have achieved, there is a lingering fear that I just wasted a lot of time.

From what you describe, i.e. preferring learning by doing rather than first getting strong theoretical foundations, you seem to be more a hacker than a academician.

From Hackers and Painters by Paul Graham (whole essay is about this difference):

  The fact that hackers learn to hack by doing it is another sign of how different hacking is from the sciences. Scientists don't learn science by doing it, but by doing labs and problem sets. Scientists start out doing work that's perfect, in the sense that they're just trying to reproduce work someone else has already done for them. Eventually, they get to the point where they can do original work. Whereas hackers, from the start, are doing original work; it's just very bad. So hackers start original, and get good, and scientists start good, and get original.

In my personal case, impatience brought me from academic science to startup world and data science What I do or: science to data science. If I had know about my psychological traits, I wouldn't have dove into the academic world (it's not only about intellectual skills, but also patience... and ability to deal with hierarchy).


Is it customary for a student to reply to professor's email within 24 hours? I got an email from professor M asking me if I will have time for a tea with her on Friday, and then I came up with this question:

Even if it is an important email from your professor (e.g. select your thesis or advisor), when you need some time to think before you make the final decision, how fast should a student reply to the a professor's email before the student is considered a lazy student, or a student who tries to slack off in studies?

If I write the reply to my professor's email after 3 days, will she get angry or even unfriend me?

There isn't really anything special about academia in this regard.  If someone sends you an email that needs a response, it is always courteous to respond as quickly as you are able.  It doesn't matter if it's to a professor or a student or a friend.

Anyone might get annoyed with you if you take a long time to respond to an email to which they need a quick response - not just professors!  But there's no magic number - you can't say that 71 hours is fine but 73 hours is excessive.  Some messages are urgent and need a quick response, others are not.  If someone is expecting a quick response but you need more time to make a decision, you can certainly contact them to let them know you are considering it, and ask when they need your answer.

As a general note: several of your recent questions seem to be written from the assumption that academia has its own special unwritten laws for everything, and if you can only find out what they are and obey them, everything will be fine.  For better or for worse, that's not generally the case - there are no such objective standards.  The key to successful interactions, in academia or any other job, is "act like a decent and professional human being".


Does age matter to get a job/postdoc? I stayed at home after I got married, but at 25 years old I decided to study History. Now I've finished my BA, MA, PhD and postdoc. I've got several publications and I can say I have a very accomplished career, but I'm wondering if my age (now 40 years old) will affect me eventually. I'm Mexican and my husband is American-Belgian, and he asked me to decide where we should live, right now I'm looking for a job/postdoc and I do not know what is the best option. What do you think?

In principle, age discrimination is illegal in the US and various other countries in the world.

In practice, there are a lot of apparently legal ways to get around age discrimination (e.g. discriminating based on experience, work history) and I have heard of first-hand accounts of supposedly illegal discrimination at various institutions throughout the world.  There are a number of employment lawyers who go around arguing these kinds of cases.

However, at least in the US, being good and well-known is an inoculation against much of this discrimination.  Ultimately, if you are successful and active, at any age, you will be hirable.


Putting an affiliate professor in statement of purpose I was just wondering if, when discussing professors who would be interesting to work with as PhD advisers in the statement of purpose, one can also mention a professor who is an affiliate of the department but primarily a professor in another department?

It may be difficult to have an affiliate professor as your sole adviser if he or she is not a professor housed in your main department. Administratively, it can be a challenge to have graduate students matriculated in one department but being advised by another.

However, if the professor is an affiliate of the department, he/she likely has someone who is full-time in your target department that they work with. You could say something such as

  I am interested in working with Professors Carl McCauley [in main department] and Demelza Fordham [affiliate]. Their research on the decomposition of rubber aligns closely with the work I did on rubber composites while at the University of ZYX.

If you tie them into a professor in your target department, being associated with an affiliated professor can actually be a good thing. It will give you more diversity and networking opportunities.  It may also fulfill requirements for outside committee members on your dissertation committee.


How to cite a site from the dark web? For my masters degree in computer science, I'm currently working on a paper on ransomware. Goal of this paper is to focus on academic writing and citing sources correctly.

Trustworthiness/Quality of sources

As I wanted to show what kind of business ransomware is and what amounts of money are dealt with, I had a look at the TOR onion network - a deep web only accessible by TOR browser.

I found some interesting results. Despite the fact that the pages are completely anonymous and it's not sure if the authors can be trusted, would it be ok to cite those pages on ransomware-related questions, stating their poor trustworthiness immediately after the citation?

BibTeX

Other questions came up on how to cite these pages. My bibtex file now looks like this (I replaced some parts by * for obvious reasons):

@misc{Darknet:****,
    title={**** - The Better & Cheapest FUD Ransomware + C&C on Darknet},
    howpublished={\url{http://****.onion}},
    note={Abgerufen am 12.03.2017}
}

My question here is how to state that the *.onion url only works in TOR browser? Or should I better include a screenshot in case the page gets shut down?

Is it OK to cite? Yes.

But... While I recognize that some valuable information can only be obtained from the dark side, it is unfair to air a source’s opinion when the source’s identity and motives are shielded from scrutiny.

So, describe the anonymous sources as clearly as you can. I totally agree with you: "stating their poor trustworthiness immediately after the citation". And note that not everybody knows that *.onion URLs only work in the Tor browser.

About the URL format, cite as any URL, as Anonymous Physicist recommends. I would also suggest you to create permanent records of the web page. Services like perma.cc might help you, it cannot resolve .onion domains, but you can upload your own archive. Another way can be find here.


What to do when the professor does not stand up to cheating? I was the teaching assistant (TA) for a very introductory physics course at a large state university. In the course of grading for this class, I came to learn that my university used the same course material as many other universities had for the equivalent course for more than twenty years. The answers to questions, in particular, were readily available online, through various forums. The syllabus explicitly forbade providing disingenuous answers, as well as any plagiarized responses. To be clear, this instructor was a fully tenured professor; not someone in any risk of losing their position.

After noticing patterns in homework assignments, I began to look for them in midterm and final exams as well. What I initially thought was a couple of bad students turned out to be more than 50% of the class regularly citing online sources word-for-word. Once I realized what was happening, I informed the professor, and I started assigning zeros to the offending students, in accordance with University policy, and the professor did not object to my assignment of zeros. However, all of this was still subject to the lead professor's review.

The professor asked for documentation of the offenses, and was in fact the undergraduate director of the department. I spent the better part of a week accumulating evidence, scouring Yahoo answers and other common homework repositories for the sources of the dirty students' answers. I found a veritable source for every single one. I printed copies of the students' responses, alongside their internet sources, and deposited the six-inch-tall stack of documents at the professor's door.

As far as I know, nothing happened to a single student, and word was never made public of the massive cheating scandal that was blatantly obvious in this course. Multiple athletes were in this (1A) course.

Is this just academia?

Beer and Circus calls this the "student-faculty non-aggression pact":

Faculty provide an easy class and don't look too hard into cheating
Students happily take the easy grade and leave the professor free to do research

I wouldn't say this is "the rule"; plenty of faculty do an awesome job teaching. But, I'm not surprised to hear your report -- some faculty don't care about teaching generally, while others care about teaching but don't care about grades or catching cheaters. Many feel (for better or worse) that cheaters get what they deserve eventually, and don't want to be personally involved in punishing them.

  What to do...

I would carefully check the department and university policies -- often, cheating cases are explicitly prosecuted "at the professor's discretion." I would also speak directly with the professor. Speaking of....

  I started assigning zeros to the offending students...[collected evidence]...and deposited the six-inch-tall stack of documents at the professor's door.

I suspect this was not the best way to go about it. I would recommend first speaking with the professor, making them aware of the problem, and asking how to proceed. At a minimum, this could have saved you a week's worth of wasted effort. As it is, you assigned a bunch of zeros, and it sounds like your professor was okay with this -- that is some punishment, at least.

  Is this just [the way of] academia?

Well, it's certainly a bit dysfunctional. And it's inevitable as long as prosecuting cheaters is a lot of work for the faculty while providing absolutely no "reward" when done successfully.


How to automatize the making and sending of event's attendance certificates? Our department make a lot of attendance certificates, for events we run, and we waste a lot of work typing attendance lists and sending them by email. Most of the public are students are from my institution, and we can get a list of names and email address. We make about 1.500 certificates by year.

We are thinking about using a event system, but I'm having trouble to find one that makes certificates and don't cost thousand of dollars.

Anyone have a suggestion? A better solution?

I suggested in my comment that you could search on Stack Overflow for a mailmerge or vba solution.

This is one example of printing sheets that you could adapt to your situation:
https://stackoverflow.com/q/46332953/4961700


What should I include in my first email to a potential PhD advisor? I am applying for Ph.D program, and I need to find an advisor to accept me in his group. I want to send to him a perfect email and get his attention to me.
I would like some opinion on this matter.

Do I include my CV and recondition letter in the first email?
Do I mention my GPA?
Do I straight-up ask them if they are accepting students? Or, do I first attempt to establish a relationship?

The field is renewable energy.

First of all, do not write a generic email to 50 faculty members. You need to focus on a few that you think are a good fit. For example, many faculty members won’t take you because they don’t have funding.

Next, try to make a personal connection: read their papers before, see how you could contribute, and tell them.

If you have a connection to them (you took a class/worked with a colleague of theirs, mentioning them will be a massive bonus (in terms of likelihood of receiving a reply).

Good luck!


Assistant professor vs Associate professor What's the difference between an associate professor and an assistant professor?

What can one of them do that the other can't? and which is a higher level? can any of them supervise a PhD student?

In a typical university in the United States:

An assistant professor is an entry-level faculty member.  They are generally on the tenure track (although the term "assistant professor" does not guarantee this) but do not have tenure yet.  Typically, within about seven years an assistant professor will either be promoted to associate professor or will leave the university, although the timing can vary a little and it's theoretically possible to remain an assistant professor forever.

An associate professor is one step up from an assistant professor.  This promotion is usually the same as getting tenure, but not always.  (Some universities, like MIT, frequently have non-tenured associate professors.)  The final step for most faculty is a full professorship.

As for what an associate professor can do that an assistant professor can't, that varies even more than the terminology.  In many US universities, the only additional power an associate professor has is voting on who gets tenure, but I wouldn't claim this is universally true.


Is there anywhere to complain about the behaviors of editors of journals except themselves? Two months ago, I submitted a paper to a journal. Within two weeks, editor in chief gave me: "Invitation to Revise". He himself read the manuscript and provides some comments.

I worked on his comments during the past two months. Today I finished the revision and submitted the revised version of the manuscript in the journal submission system. Eight minutes later, editor-in-chief emailed me that the paper did not accept, please see the comments to the editors and reviewers at the end of email.

There were two lines of comments, telling me could you please submit the manuscript to our new special issue, with a link.

When I look at the web page of their special issue, I found out that their special issue submission, will start some month later and its deadlines are much later. I don't have so much time, to wait for this.

What can I do? Is it useful to email to EIC?

When I don't have the right to submit the manuscript to two journals at the same time, what prevents EIC and editors from acting unethically?
Especially, when they have all the powers?
EDIT: In response to comments, the question is:

Is there anywhere to complain about the behaviors of editors of journals except themselves?

It's probably just supply and demand.  Your paper isn't good enough to make it into the regular editions, but he is going to lower the bar a bit to fill out the special issue.

I have seen this.  It's not nefarious.  In a way the regular/special difference is like the difference of journals with different importance, exclusivity.

In terms of what you should do:  I would lean to moving on to another journal.  And upgrade the paper based on the reviews.  Now, if the editor could tell you the paper was good to go (for the special), that is different.  But it sounds like this is not the case or else he would have just told you that at the time.  Being invited to enter another uncertain outcome of his would not interest me.  Yeah, you will have new competition at new journal, but at least you are moving on.  How I would prefer it.


Is there a template for academic paper changes report? After updating the academic paper as per reviewers comments, one needs to submit the updated paper in parallel to a report of what did he change or why didn't he change. Is there any template for such report? if not, what sections should it contain?

At jakebeal's suggestion, I'm converting my comment from Jan. 12 to an answer:

Some people just use the referee's report and insert the information about what they did with each comment. So a minor comment (about fixing a typo for example) might be followed by just "Done." A comment about adding some more information might be followed by "Done; see page x, lines y to z." A comment that one didn't comply with might be followed by a careful explanation of the reasons for not complying. On the other hand, I've sometimes just written "I've complied with all the referee's comments except x. The reason for the exception is that ...."


Citing statistical information presented in a table using data from a variety of sources? How do I cite information that I am presenting in a table (i.e. that I have created), when the statistics I have compiled are from different sources?

When it comes to citations with reference to a table, I often see it implemented in the APA-style, that is:

table heading above the table

in the table text, there are small letters in superscript (a, b, c...)

the references are named below the table, again with the small letters in superscript, but all in one line

I found this example in the APA Style Blog:

In addition, that blog post offers a different example in which the respective references are placed in their own column: