reviewing other articles for a conference I have been appointed to take part in reviewing papers for a conference. At the beginning I received an email in which the program chair told me to mark my fields of expertise, so I did that.

After a few days, it appeared in the reviewing page a list of all the papers submitted. But when they assigned me the papers, they do not assign me those in which I have expertise in the field and that I put in a previous email.

So now I have reviewed my assigned papers. I have seen that I can see all the papers submitted and there is also the possibility to put my review in those that there have not been assigned to me. Should I do that with the papers that are my field of expertise? or should I only review those that I have been assigned.

Thanks

Welcome to conference reviewing.  Your situation is unfortunately extremely common.  If the number of submissions in area X is less than the number of reviewers with interest and expertise in area X, then inevitably some of those reviewers will be assigned papers in area Y.  Symmetrically, if the number of submissions in X is more than the number of experts in X, then some of those papers must be assigned to reviewers who'd prefer Z.  Ideally, most papers are reviewed by experts and each reviewer is assigned mostly papers in their areas of expertise, but sometimes the matching system breaks down.

By default, you must review the papers that you were assigned.  But there are a couple of ways to address mismatches.

If your assignment looks like a complete mismatch, you should quickly contact the PC chair and express your concerns, and in particular to verify that they received your preference email.  If you're early enough in the process, the chair may be able and willing to swap assignments with other reviewers with complementary mismatches.  There might also be a mechanism to swap assignments directly with other committee members, but you should always get the PC chair's permission before actually swapping.
Most computer science conference review forms ask for your confidence in your review; fill in this field honestly.  If you really don't have the expertise to understand the paper or make a recommendation, your review should read "I apparently do not have the expertise to understand this paper or make a recommendation."  That's a damning review of both the paper and the assignment process, but that's okay; your job as a reviewer is to be respectful but brutally honest.

On the other hand, as a matter of simple self-preservation, you should not review papers that you were not assigned.  Reviewing well is extremely hard and time-consuming, and you have many other demands on your time.  (And reviewing badly should just not be done at all.)  Generally speaking, doing extra unsolicited reviewing will not earn you additional credit or brownie points.

There are a few exceptions.  If you see a paper that you plan to read in detail anyway, despite getting no credit for doing so, you might as well write a review.  And if the initial reviews of a paper disagree, the PC chair may seek out additional input or even full reviews; if you're asked about a paper in your area of expertise late in the review cycle, you should help.  (If you're asked about a paper outside your area of expertise in later rounds, you should just say no.)


A paper's citations per year? Google Scholar shows the total number of citations per year for anyone with an account there:

Is it possible to see a similar figure just for one publication?

Yes, click on the article title and scroll down in the dialog. You can hover over the bars to get raw count.


How do I stop feeling unwelcome in my department? I could not find a PhD advisor and the person in charge of my PhD program suggested that I leave with a master's degree.  He said that I was good at carrying out tasks but I did not have the motivation to advance the state of the art in my field.  Some time later I found an advisor in a different department, and he seems to like me.  But I still cannot get over what the graduate coordinator said, and now I hate visiting the building because I feel I do not belong and I don't want to talk to anyone I know.  What should I do?

After I found an advisor the graduate coordinator said something like "I knew you had it in you, I just wanted to see how much you wanted it."  But I don't know if he really means it, and if he did, I think that's kind of a mean thing to do.

You mentioned that your new advisor is in a new department. So, can you cut the losses with the old department?

But, although the comment stings, and your feelings are understandable, being able to handle it is part of completing Ph.D. To complete a Ph.D., you need (within a reason) to go against the grain, latch onto something, not listen when you are told it can't be done, and pursue it against the odds. In the process you grow a thicker skin and not let doubtful comments get and define you.

So, it is possible that your advisor meant to test you, and see how determined you are to continue the process. I am not saying that it is the best approach, but I have seen this happen.


on a CV do you list both a paper and an associated oral presentation? I attended a conference that accepts short papers as well as accepts the papers for oral or poster presentations.  I had four papers, for two of which I gave the oral presentations.  My conundrum is that on my CV do I list both the papers as well as the associated presentations or just the papers as that is in some sense the higher priority?

I generally see people break their CV into peer-reviewed and non-peer reviewed contributions. Then within those categories they indicate whether or not they were the presenting author.
The presentation is really presenting the work in your paper, so they are one and the same. Plus consider the fact that the proceedings of the conference are what people will be able to find your work in, and therefore you want to give them the information for your paper. For example:

Peer Reviewed Contributions
Your Name, Co-Author, Co-Author, "A breakthrough in a big question", The International Journal of Great Answers, vol. 42, no. 0, pp. 3141-5926.
etc...
Non-Peer Reviewed Contributions
'*' Co-Author, Your Name Co-Author, "A very novel and important answer to a very big question", The 9th World Conference of Very Big Questions, Conference paper and presentation.
Your Name, Co-Author, Co-Author, "The smallest possible answer to the biggest possible question", The 42nd World Conference of Very Small Answers, Conference paper and poster presentation.
Note: Contributions with an asterisk '*' indicate that Your Name was the presenting author.


How to start researching for a thesis topic I'm senior undergraduate student who has just received a thesis project from my professor to work on for a year. However, I don't know where and how to start. What would you suggest?

The project topic is related to telecommunications and electronics and inter-disciplinary. Because of this, I will be working with a friend on this project.

Great suggestions above, here is the methodology I follow:

First off, determine the general term for the area of your thesis, for example, "civil engineering" or "genetics".
Create a word document (literature review) where you keep track of citations and books you have read in this topic.
Perform a "Google Scholar" Search for your topic, add list of citations to your literature review as you save each article and print to keep in a notebook. In addition, add a 'review' of each journal article you read including Summary, Main Hypothesis, Strengths/Weaknesses and Date Reviewed.
On Google Scholar, you can see what other articles have cited the article you are reading. This is a great way to gain further resources for your search.
Do this every day for a few weeks and you will be sufficiently immersed to have a background in the previous work to understand your thesis topic and background.

Additional Tips: When performing research, it's important to begin focusing on what new insights, methods or understanding you can bring to this field of study. In many ways, academia is a 'competition' where the winners are rewarded for their efforts with additional funding, facilities, and prestige. By performing background research (aka Literature Review), you are able to learn from the hard work and progress of others, and expand on their insights in order to 'make a better mousetrap'.


What’s the current state of the art in searching for journal articles? I haven’t been a student for many years. When I was in school at first we used portals like

JSTOR
Science Direct
Elsevier
Galileo

Next, Google Scholar came out and seemed to be a superset of all of those, so it was the best when I left off.
I was on a phone call with a university class a couple of years ago and they told me there was some newer “meta portal” (my term) that was along the same lines but even better than Google Scholar. I can’t recall the name and it’s not obvious which one it is when I try to figure it out by searching the web.

Web of Science is a subscription-based citation database that came out shortly after Google Scholar. I can't compare it to other services such as JSTOR and Galileo (which I have never tried) but at least anecdotally I find it to be better in some respects compared to Google Scholar (better UI and more trustworthy citation counts, at least in my field). However it is subscription-based so whether or not you have access will depend on your employer/institution.
Edit -- There is another citation tool that I feel is criminally underutilized so I feel compelled to promote it. The arXiv has a fantastic browser add-on called the arXiv Bibliographic Explorer which provides detailed information about citations for nearly every article on the arXiv. Even though this is not directly related to your question, I have found it to be an extremely useful tool that not many people know about, so it deserves mention.


Starting collaboration through first e-mail. Can it work? I was an undergrad student with Professor X a few years back. Prof. X used to be a co-author in all the publications with Prof. Y. Prof. Y is very popular in the field.

Now, I am working in a university. I have keen interest to work with Prof. Y on a few problems of interest.

I have less idea on how to collaborate in such a situation where I don't have indirect contact apriori. The option that I have is to send a mail to him which looks as follows:

  Subject: Request for collaboration -- Problem A and Problem B

  Dear Prof. Y

  Greetings!

  I have learned about you from Prof. X during my works with him.

  I have gone through your recent papers: [this] and [this]. I am good in Method1 and Method2 which could suitably address your problem.

  My recent works can be found in [this profile link].

  Looking forward to hearing from you.

  Sincerely,

  me

  --
  [my signature]

Is this approach a suitable for my collaboration with Prof. Y?

Update: I had sent an email to Prof. Y after incorporating the suggestions from the fellow academia.SE community members here. I got a response from Prof. Y and looks like he is also interested in working together.

Let's elaborate on my comment in this answer. Here are the issues:

There are just statements in your draft, no actual question.
The tone of the mail is a bit informal for the case you don't know Prof. Y (at least in my opinion). Leaving out the "Greetings" will make it better.

Here's my proposal for the mail:

  Subject: Request for collaboration -- Problem A and Problem B

  Dear Prof. Y,

  I have learned about you from Prof. X during my works with him.

  I have gone through your recent papers: [this] and [this]. Recently, I have worked with Method1 and Method2 which could suitably address your problem. Would you be interested to (Removed: collaborate on [thing] with me?) talk with me about the topic in a phone call or meeting? It would be a pleasure to work with you on this topic.

  My recent works can be found in [this profile link].

  Looking forward to hearing from you.

  Sincerely,

  me

  -- [my signature]


How to collaborate with unmotivated postdocs As a PhD student in a multidisciplinary subject, I am grouped with a postdoc by my supervisor. In our lab, the usual rule is student do the theory and coding, and postdoc do the experiment.

My collaborator postdoc is highly unmotivated: he badly performed the experimental tasks that I told him to do (most of the time, the experiments was unqualified), and delayed our project progress.

I am much younger than him, and he refused to follow my instructions, and instead fed me with unreliable “ideas” and asked me to do his job... My supervisor knows the situation, but does nothing and just watches. Each weekly meeting I am the only guy having progress.

At end I had to do the experimental part myself. It was tough but finally the project was accepted to a top journal. I have done 95%+ works, but have to add the postdoc as a coauthor (he didn’t even take part in writing the paper)

I anticipate similar course of action in future projects. I can’t change the group.

How can I properly motivate my postdoc to get him work for me?

Edits:

The question has been revived and let me summarize some of comments. It helps to clarify some statements:

"get him work for me" simply means "do his duty as a collaborator".
The postdoc received authorship; but I am actually the guy doing all the works.
The whole story is, I gave up pushing on him, did the bio training myself, and finished the data acquisition myself.
In this question I am humbly asking how to avoid similar situations from happening again.
I am not being harsh from the very first beginning. I was polite to the postdoc, even after wasting months.
Technician is not a negative word. If you are familar with bio labs, you will know most postdocs are no more than a "technician", most of them cannot get a decent faculty position (e.g. top 100 US universities). I am a technician too, but just in coding. The only scientist is the professor.

How can I properly motivate my postdoc to get him work for me?

You don't. Changing anyone's behavior is difficult; changing your "superior's" behavior will be even less successful and will lead to conflict.

I would start by trying to figure out how long the post-doc is planning to be around. It may be that he is on his way out; this would explain both his lack of focus and the professor's apathy.

In any case, I agree with the discussion in the comments -- the situation as you describe it is inexcusable. But as a PhD student, your options are very limited. I would suggest asking the professor for a private meeting. In the meeting, I suggest making the following points.

You successfully published a paper in a top journal
The post-doc contributed virtually nothing to this work, and in fact delayed progress
You feel it "may have been inappropriate" to even list the post-doc as an author of the paper
Based on this experience, you think it would be more fruitful to work independently from the post-doc on future efforts.

The professor will likely not be receptive to this, and will make some vague promise about speaking to the post-doc. So, the real question you should be asking (yourself) is:

  Should I finish my PhD with this advisor or find another group?

If you are willing to leave (and you are sure!), you can mention this to your advisor if his initial reaction is not satisfactory. This may change the calculation for him -- or he may be more candid with you (e.g., telling you that he is about to fire the post-doc). Or he may let you go.

If you are close to graduation, then it's probably worth sticking this out. Adding people as authors when they didn't contribute much does not really rise to the level of serious academic misconduct, so I would simply avoid relying on the post-doc as much as possible.


Is it possible to recover after a career setback such as this? I'm sorry, I'm not a mathematician--I'm the wife of a very frustrated and depressed mathematician.

My husband got a math PhD in 2009, and could not get a research post-doc in his chosen field.  We had young children at that point, and he spent two years as a lecturer, applied for hundreds of jobs, and finally took a tenure-track job at a teaching university. Now, he honestly believes that a research position is impossible for him.  He loves to teach, but hates the endless grind of "administrivia", the low pay, and the mental laziness of the students he's required to teach. (I wish I could give more details, but his research area was a fairly small community, and I don't want to give any aspect of his identity away.)

I hate watching this brilliant man say things like, "Well, since I didn't get a post-doc, I'm stuck on this path, and there's nothing I can do to get out of it."  I hate watching him spiral into depression.  I am insisting on him getting counseling, but he refuses to take anyone's encouragement that other jobs are possible, saying things like, "You just don't know the academic world.  If I go to the NSA, no one will hire me in an academic position.  If I become an actuary (because we do need more money) then all of my time will be sucked into studying for exams, and I still won't be able to do research." In his mind, no one in our circle of loved ones has the authority or experience to give him accurate encouragement.  So I'm looking to anonymous strangers at this point. :(  Is a research position possible after spending time at a teaching university?  Would he be able to get back into academia if he had to leave to do actuarial work/industry/something that helps pay the bills?

I wanted to give a brief update.

To begin with, THANK YOU to everyone who replied.  My husband's eyes lit up after seeing that 1) This was a fairly common problem, and not somehow indicative of his skill level;  2) There were solutions, other than being miserable; and 3) The solutions did not a) condemn him to a life of administrivia, or b) require him to leave academia all together.

After getting the hope he needed from you guys, he spoke with a mentor of his from undergrad, and was given incredibly specific guidance on where to go from here.  His teaching load is so heavy, (4/4 or 4/3) and the mentor gave him a few places to apply to in his field where the teaching load is more conducive to some research, but is not at a research-specific university.   (3/3 or even 3/2!!!) He plans on speaking to his advisor, getting some glowing letters of recommendation, and starting a job search soon.

Thanks so much.  It was nice to see his face light up again. <3

The situation you describe is unfortunately common. It is an unfortunate reality that the number of people well qualified for research jobs is greater than the number of jobs.

A few notes:

Hiring committees will be looking for good publications, and for recommendation letters coming from leaders in the field attesting to your husband's impact and further potential. If he continues to do good research, publish it in well-known venues, and speak about it at conferences, then he has a good chance. If not, then unfortunately he is competing with people who are.
Most of the complaints you mention are common at research jobs as well. I teach at a large state university, where we have our share of poorly prepared students, and/or students who are just going through the motions. Indeed a Harvard professor once quipped to me that "we have remedial classes here, too".
I do know people who have successfully moved from one teaching position to a different teaching position, and been much happier afterwards. Some departments have more motivated students, pay better, and/or do a better job of keeping the paperwork down, and your husband could look for one of these.
I know people who have taken a variety of non-academic mathematical jobs, and for the most part they are quite happy with them!

The bottom line is that your husband can probably get a research job if he can sustain a very strong research program during the interim. Otherwise, there are likely to be appealing alternatives as well.

Good luck!


Is it necessary to get a masters degree for industry jobs in Machine Learning or AI? I’m about to enter my ultimate year of a physics BSc at a top university in the UK, and have done a computational physics  internship with a research group at the university and am currently doing an internship at Harvard that requires strong machine learning skills. I was hoping this would be enough qualification to justify being able to get an entry level job in ML or AI and use that to one day lead myself into a job working with DeepMind, OpenAI, IBM Watson - places like these. I also have some fantasies about working in game design randomly, although I think that needs less a graduate degree and more a portfolio of coded games perhaps.

However, with those ML and AI jobs I was citing, does it behoove me to get a graduate degree if I want to one day get hired by them? I personally am quite drained from exam stresses and don’t think academia suits me as much as I used to think it does, but if it’s necessary for my goals in industry it might be worth considering.

It depends, I think, on what sort of job you want. For people in the trenches, even at IBM/Watson, an undergraduate degree is probably enough to get hired. You would likely be a team member building things at the direction of a manager. Creativity would be in the "how to do this" rather than in the "what do we need to build" area.

However, at the level of doing research at IBM, and I assume others, the requirements look a lot like they would for an academic position. Lots of the people there have doctorates, actually. I don't know that a PhD is necessary to get hired, but the more education you have, the better your chances.

I know people at both these sorts of levels at IBM and at Oracle.

It used to be that at IBM the trench types could get a doctorate paid for at the company, but that option has disappeared for a while now. They might be a bit flexible about giving you some time-slack to do it, depending on the manager, but funding is unlikely.

At smaller companies and especially at startups it is probably much more flexible, but also risky. I also know people doing interesting things at such small software shops who have a more basic formal education though they are good at learning on their own and staying at the forefront.


Applying to Computer Science PhD Programs I am a computer science and math double major, and I am applying to computer science PhD programs this fall. I have a 3.9 GPA and have done research with 3 professors during my time in undergrad. I have one publication and three poster presentations, and I will hopefully have at least one more publication before I apply (but due to problems in the research group, that might not happen). I can get two great letters of recommendation, but the third might be lackluster. I go to a regionally known liberal arts school, but it is most certainly not a household name.
With my qualifications out of the way, I want to study machine learning. My prior research was not in machine learning per se, but it did involve aspects of it. I have done work in bioinformatics, computational statistics, and computer vision. My professors are not especially well known in their fields, but they do publish frequently. What tier programs should I apply to? My advisor thinks I should apply roughly on the threshold of top/mid tier programs, but I would like more opinions.
On a tangent: Some schools have both computer science and machine learning PhD programs. Should I apply to both? And do some schools admit generally with no specialty? If so, would I have a better chance with them since machine learning is so competitive?

At least in the top-4 (I'm an ML PhD in one of them and helped pre-screening candidates) Machine Learning has become incredibly competitive. We almost always asked for 1 publication (if possible in ML, although not always). Third recommendation letter is probably irrelevant, the two most relevant things were the most informative letter (the professor that knows you best) and indication that you can become an independent creative researcher (1st author papers, out-of-ordinary projects or accomplishments). GPA almost didn't matter. Note that I've heard some of these criteria are different outside top-tier.
Applying to CS will likely increase your chances of getting in. I know many students doing ML in non-ML labs, but this also has downsides and you have to find an advisor that accepts you. Not applying to Reinforcement Learning within Machine Learning will also increase your chances (at least last year).
It's hard to know if you have good chances of getting into top schools, but if you have money and time I would apply widely, it doesn't seem impossible. I applied to 10 schools and have friends that applied to 15. It's pretty stochastic, I got into 3 of the top 4 but got rejected by multiple others.
Focus on doing good research in ML, if possible a workshop at a top conference, and impressing your current advisor.
Best of luck!


Using endnotes in a teaching statement I've been working on my teaching statement recently (for the mathematical sciences, but it shouldn't matter).  I'd really like to keep the main body to one page, because I personally wouldn't want to read anything longer than that, but there are several instances where I feel like I could include a little more information "for those inclined to read it".  Do you think it is appropriate to include these comments as endnotes, or is this somehow more irritating than having a slightly longer document with such comments incorporated inline? For instance, if I do something like this, I end up with one page of text followed by a half page of notes.

  I've had broad success1 using a modified Moore method to teach a
  graduate qualifying exam review course.

  ...

  Notes

  1 In the three years I have taught it, 22 students have taken the course, and 19/22 have passed at the PhD level first try; in contrast, the first-try PhD pass rate for the five years prior was only 50%.

If I incorporate such statements, I'm over my (entirely self-imposed) one page limit.

Endnotes of the sort you are suggesting would give the impression that you don't know how to write a teaching statement. In any document like this, you're trying to make a convincing case, which means knowing what to put in and what to leave out.


Should I sleep less to achieve my thesis targets? I am doing my Masters (thesis-based) in Computer Engineering in Canada. I started my research in September 2015 and it is now the end of April in 2017 but I haven't done ANY significant research. It is very distressing and I definitely will need extra time to finish my research and graduate.

I meet with my professor and we both decide on what I need to do and a deadline is set for specific tasks. The initial stages of these tasks mainly involve installing software on my lab system which has the hardware I need for my research. I always run into problems during these installation processes and I end up spending more time than necessary JUST to have the necessary tools needed to do my project. By the time I get started with my work and do anything meaningful, the deadline arrives and the tasks remain incomplete.

My professor is frustrated by my lack of concrete results but despite that, he is encouraging and believes in my abilities. I also think I can publish at least one conference paper before I graduate. However, I am wasting my potential and my expertise by not meeting set deadlines. I know I can get things done but apparently, I am too slow in getting to where I want to be.

I feel that setting aside a set amount of time each day (6 hours or so) is not always effective in meeting goals. Should I just give up sleep (and definitely my leisure time) to meet my goals? I am afraid that it will impact my health and my concentration and negatively impact the quality of my work.

Should I simply come to terms with the fact that given my capabilities, I will need to sleep less to meet my goals?

EDIT:

I also work as a TA and a good amount of time also goes towards preparing for labs and marking students' papers.

Reducing sleep may work for a day or two. However, after that, sleep debt accumulates, and sleep deprivation will lead to a reduction in productivity.

Sleep is essential for your physical health, and in particular, it is essential for mental functioning. You may find it better to view sleep as a form of "work time". The cognitive structures you have about your thesis will be refined and pruned while you sleep. You'll make novel connections while you sleep. Sleep will also enable you to have the mental energy to engage in focused activity on the thesis.

In particular, the kind of deep creative thinking required to analyse data and write a thesis is helped greatly by being well-rested. Sleep also helps ensure that the work you do is directed towards your goals.

Thus, allocating enough time to sleep so that you are well-rested is essential to overall academic productivity.

So in general, if you are looking to maximise productivity in the medium-term (i.e., from a week or two to perhaps a month or two), then look at things other than sleep and thesis-time that can be trimmed. If possible, remove all other work commitments (i.e., no tutoring, RA work, consulting, etc.). Other work consumes largely the same set of limited mental and time resources that you have available each week. If possible, reduce non-work commitments.

Also, in the medium term, many people do pull back from social and leisure activities a little bit. But in the longer term, you want to think about a balance to your life that truly works for you. I also think that incorporating at least a moderate amount of physical exercise is also important.


Developing a work ethic, or learning/doing things you aren't interested in (prelim topics) Short version: Graduate prelims include lots of topics which are only distantly related to your particular research area. How does one motivate oneself to learn and do this stuff?

Long version with personal background: I'm a 3rd year undergrad who's planning on applying to graduate schools in the US next year (in mathematics). I'm taking a graduate course (Galois theory) which, in the graduate programs I'm looking at, typically amounts to less than 1/3 of the material on the algebra prelim, which is one of the usually 3 topical prelims. For me, the concrete consequences for failing this class are academic probation with possible loss of funding/scholarships; if I were in the graduate school here, this would be possibly ejection from the program.

Unfortunately, I find this topic to be horribly uninteresting. I did very well in the first half of the class because it was essentially a very fast-paced redux of group and field theory, but I can't find a single drop of inspiration or interest in my mind for these classic Galois theory results that we're developing. I've done some undergraduate research in algebra (factorization theory) and, if I were to go into that as a professional, I feel confident that I will never touch Galois theory ever again. So for me, Galois theory being mandated to be learned by me for only this one purpose, a prelim exam. Therefore, I'm having trouble finding motivation to learn it.

The lectures are in the usual "lemma: proof, theorem: proof, corollary: proof" style (occasionally throwing in a sentence or two of motivation, why we study this topic), with weekly homeworks which heavily supplement the lectures (only a small percentage of grade), and 2 tests (midterm and fnial). These homeworks are pretty in-depth and are expected to take upwards of 5 hours to properly complete. (Usually 1-2 pages of proofs for each problem, and 3-5 problems per week.) Nobody is holding my hand any more and walking me through the class like in undergrad classes. (E.g., the homework problems aren't even close to self-explanatory and often cover topics not even mentioned in lecture.) Even though I'm showing up to lecture and taking detailed notes, I haven't even started the last 3 homeworks. The final is still 3 weeks away so it's not impossible for me to catch up, but it's going to take a lot of hours to get this material learned so that I don't fail the class.

As far as I can tell, this class structure is more or less standard in graduate mathematics, so if I'm serious about wanting to continue in academia I'm going to need to find out how to manage this problem (lack of interest). How do others handle this? Where does the motivation come from? (other than Adderall.)

In this case, the best way to motivate yourself to study this uninteresting material is to try to become interested in it. It's important not to specialize too early, and as a third-year undergrad, you should only now be in the process of deciding a broad subfield of mathematics to specialize in (usually Algebra, Analysis, Geometry/Topology, Applied Math, or some combination of the above). Given that you're interested in becoming an algebraist, it's simply too early in the game to be crossing specific sub-fields of algebra off your list. Especially not Galois Theory, the basics of which you will very likely be expected to know if you take graduate courses in algebraic geometry, number theory, or the like. And even if you don't directly use this material in the future, it's a chance to develop mathematical maturity and intuition. (I'm glad to have been exposed to Galois Theory as an undergraduate, and I'm an analyst!)

As for this particular class, it sounds like it's simply going too fast for you. Which there's no shame in; I certainly had the same experience when taking graduate classes as an undergrad. If you revisit this material in a few years, you may be surprised to find yourself enjoying it. In which case you'll be thankful for anything you learned the first time around, even if it didn't fully sink in.

Basically, you should motivate yourself by keeping in mind that the effort you put into this class will benefit you in ways that aren't apparent right now.


How good are entrepreneurial opportunities for faculty members? How easy is it for faculty members working at a reputable university to become entrepreneurs?
If the faculty member sees an opportunity for a great product and wants to set up a small office with a few engineers working with one or two students, will the university sponsor such a venture?
How enthusiastic or forthcoming will the industry and VCs in general be towards this?
Lastly, how common are such professor-run companies for, say engineering faculty in top US schools?

This is quite common in American universities, and there are probably thousands of start-ups that have arisen out of university-based research. The question of financing such a venture is of course a challenging one to answer, but with the right contacts, is usually available.

I can think of at least four or five such start-ups in the department I attended for graduate school, and I imagine there are several more in the planning stages.

As for how enthusiastic industry and VC's are, well, I think it depends entirely on the strength of the idea, and how "market-ready" the concept is. The sooner it's ready to go, the more enthusiastically people will flock to it.


Is it safe to assume that all faculty know what a DOI is? Can I refer to DOIs without explaining what they are?  I am writing for an audience of experienced academics.

My suspicion is that the vast majority of academics (in STEM fields, say) will

have seen DOIs being used many times in papers and online,
be able to discern your intent if you use the term DOI in a context other than in print with a URL next to it,
have absolutely no idea what the letters stand for, and
never have done any research (e.g., read the DOI wikipedia article) about what DOI's are, why they're used, etc.

Added: In response to Strongbad's comment, let me summarize the above briefly. I believe that a large majority of academics will have seen DOIs being used and know that if they go to the URL they'll wind up at the paper they're looking for. I also believe that, if pressed, many academics would say that the point of having a DOI is to be able to provide people with a stable URL where the paper may be found. But I think that in most cases the latter response would be a guess because I think that very few academics have spent any time looking into DOIs in any serious way.


Is it better to apply to a less prestigeous PhD Program, or do research for a year and reapply? Should I consider applying to mid-tier schools? Or will I have better long-term success by working or doing research for a year and re-applying to top-tier schools? I don't want to be a professor, I just want to be an expert in my field and then do research in industry. How much does the institution you attend actually matter?

Details about my situation:
I am a senior at Worcester Polytechnic Institute currently applying to PhD programs in machine learning and robots. 3.98 GPA, two grad classes, a few research projects with professors, one publication as first author at a tiny workshop, and some solid internship experiences. I am planning to apply to MIT, Stanford, Berkeley, Georgia Tech, and CMU. I think I am a competitive applicant, but I also know that those schools are insanely hard to get in to in my field. I'm planning for the event I don't get into one of these top schools.

Clarification:
If I end up taking a year before grad school, I would be doing research at a company (Uber) or getting a research internship at a university lab somewhere (not sure how or where).

Doing research for a year and reapplying would definitely be the better option IMO. Even though it's true that when it comes to performing research, it matters less where you do it, there are certainly undeniable positive effects from getting a degree in a prestigious university - from the peer group you'd be surrounded with to the visibility your work could get later on. After all, the research that you will do during the one year is not going to get wasted. Even if it doesn't get published, it only sharpens your ability to perform research.


Is checking the format of a paper an expected part of the reviewing process? I have some papers to review and I am wondering whether I should do an in-depth inspection over the whole paper format? I see nothing major but there might be some tiny format errors here and there..

  Does the organizing committee expect reviewers to check submissions
  against the conference format?

I would say the responsibility of the reviewer is to judge the content of the paper. So, checking if the format of the journal/conference has been followed is not part of this job. Very large and obvious deviations can be pointed out, but for example spotting that the font of the caption is in size 11 and not 10 is not part of a reviewers task.


Listing GPA on undergrad CV when reaching out to professors I intend to apply to PhD programs in computer science, and I have been advised to reach out to professors I'm interested in working with by sending them my CV. My GPA is 3.6, which is not bad, but it's not great either. I think the rest of my CV/profile is quite positive, but I am not inclined to list my GPA for this 'reaching out CV', since it may create a bad first impression, even before I apply. So the question is whether I should leave my GPA on.

Conspicuously missing a CV makes a worse impression.  The most important thing, in my view, is to take some time to properly understand what the professor is doing, and how you could help his/her research efforts.  A thoughtful contact of this type is much more valuable than crafting the correct CV/profile.


Erratum on my bachelor Thesis I have written a thesis for my bachelor degree and next week I have to defend it. The problem is that I found some small mistakes (not spelling mistakes, but small mistakes in equations, a wrong number in the abstract and so on) and one or two more significant problems.
Now I want to write an erratum on my thesis that handles six different of these mistakes. Is this too much? I don't want the jury to think that I was sloppy with writing the thesis or that I didn't check it before I handed it in (I did check it numerous of times).

So, is it normal that an erratum contains so much mistakes?

A thesis is generally a pretty big document, and it would not be surprising to have a number of mistakes even after several passes of editing.  If I were on your committee, I would be happy to see you submit such an erratum, because it would indicate that you are continuing to engage with the material and actually concerned about its quality, not just trying to graduate and leave.


Best eBook website for PhD students What's the best "bookmine" academic targeted website for PhD students to find references for their studies ?
Thanks in advance

If you don't have qualms about downloading from a site that has been convicted for mass copyright infringement, then Library Genesis is probably the largest one. It is basically Scihub's sister site for books.
Their Wikipedia page contains up-to-date links to access it (which may be blocked by some internet providers).
Check the legality of what you download. For instance, where I live you risk a 154€ fine for illicit downloads for personal use, without other aggravating factors. (I think at least -- IANAL.)


Data Set Definition , Where to Place (Introduction, Material and Methods)? Machine Learning , Data Mining studies uses various data sets. If used data sets are not well known data sets, following points of these data sets should be explained. More can be added but these points comes to my mind immediately.

features/attributes (number, data type, domain definition)
How many instances exists in this data set?
Test / Training data (Random Sampling, All data used..)
Feature Reduction techniques
Any preprocessing/post processing

Thus my question is: Where should I put this data set explanation in article sections?

Introduction
Methods (Experiments)
Or entirely new section under Data Set heading?

There is no universally-agreed way to do it. I usually place the information about the datasets under the experiments section, before reporting the results. Also, I prefer to present parameters about the datasets (e.g., number of features, number of samples) in a table. If many datasets are used, and there are some points that needs to be clarified, I would create a subsection for the datasets under the experiments section.


How to respond to papers that put forward unreasonable criticisms of my research area? My research area (not me specifically) sometimes gets attacked by a handful of people who don't know what they're talking about. I don't have a problem with fair criticism, but these people are just being unprofessional.
To be more specific, the abstract of a critical paper might be something like:

We use technique X. After extensive testing we find that X is completely impractical. Moreover, X fails to do Y or Z. We conclude that X is a research dead end and the researchers working on X don't understand what they are doing.

A more accurate summary of the paper would be:

We implement A - one of many techniques from area X. A is widely known to be inferior to other techniques in the literature of X, but we are unaware of more sophisticated techniques. Some basic tests confirm A's inferiority.
 Due to failing to properly use A, it doesn't do Y. Moreover, A doesn't do impossible task Z. (No one claimed that A does Z.) We thereby demonstrate that we don't know what we are doing.

How does such a paper get through peer review? Simple: They publish it in a different community, where no one understands X. Unfortunately, this terrible paper then becomes one of the most visible papers on X in that community.
Most people in my area completely ignore the criticism, although some do try to rebut it. As easy as it would be to ignore the critical papers and hope that others do too, the reality is that the misinformation they spread is harmful to my area.
I was wondering whether others have similar experience and can share what worked and what didn't. Can you win by arguing with an idiot/troll?

You can't change what is already published, so there is no point in trying to.

What you (and the people in your research area) can do is ask yourself why they used A instead of X. Maybe there is an easy-to-use free implementation of A, while it takes a PhD to really understand and implement X properly? In that case, you and your peers should fix the problem by releasing a tool to do X. Possibly an automated one, with a simple interface and no magic parameters to tune. Then you can recommend it to people in the other field.

Another thing you can do is collaborating with someone in that area, and publishing a benchmark paper where you test several algorithms and you show that X really works. A paper of this kind may be easier to publish in their area than in yours, where this fact is common knowledge.

If you simply call them idiots, you will never fix the problem. This is the wrong attitude; the blame can't be all on their side. You should borrow this principle from user interface research: if your users make mistakes frequently when interacting with your program/website, it is not their fault because they are idiots, but it is your fault because your interface is bad.


Should I do a second PhD in Canada or the US? I am three years into a PhD in Germany in an interdisciplinary social sciences field (Global Integration/Global Studies), but I am quite disillusioned with the faculty and the quality of guidance here. Moreover, the academic job prospects are not very good after the PhD, and any other job, given EU regulations, is hard to get (I am non EU). Going back to my country, given the corruption in academics, is also not an option. I am thinking of dropping this, and applying for PhDs in Canada or the US.

Is this a good option? I would apply for single discipline such as political science. I am thinking of international business too, because my work is a policy relevant field.

As a general rule, if your current degree program is not serving your needs/goals, then yes, you absolutely should look for other options.  Hopefully the research experience you've gained in your current program will prove helpful in the future.

That said, you need to be careful in applying to a new program.  A PhD application from a student already in a PhD program raises a red flag, especially if they are already fairly far into the program.  Obviously the current program isn't working out for the student, but does that indicate a problem with the student (uh-oh), a problem with their advisor (but then why not change advisors?), a problem with the program as a whole (but then do we really want a student that was admitted to a dysfunctional program?), or something else?  And even if there isn't a problem, why should we give a slot to someone who already has one elsewhere, instead of giving a new student a chance?

The best way to ameliorate these concerns, in my experience, is to get strong and supportive recommendation letters from the faculty in your current department.  You also need to tell a convincing and positive story about why you want to move (for example: a shift in research interests that does not match the strengths of your current program).  One thing you absolutely cannot write is "I want to move because my current program just isn't good enough."


How do I continue my PhD research project as a Postdoc? I was wondering if I could get some advice about how to go about continuing my PhD project as a Postdoc. I'm actually from the UK not the US but I think that your answers and advice will still be applicable and really helpful.

So here's a bit of background about myself: I really enjoyed my Plant Science PhD, and even though I came out of it with more questions than when I went in, I managed to get two papers published in two very respectable journals (both of which are still cited today). At the time I wanted to get experience working in other fields, so after my PhD I found a Postdoc in a different research area of Plant Sciences; however, I didn't really enjoy this research area and due to unforeseen circumstances that were out of my control, I came out of it with only one paper, which I am still trying to finish. At the moment I'm employed in Science Services so for the first time in years, I am in a position where I can be choosy about my next job.

What I would like to do is apply for funding to continue my PhD project because I would like to get back into this area of research; I think with the new technologies that are available I could make a lot of interesting discoveries. My PhD supervisor has since retired and has given me his blessing to approach other researchers, and I assume I have to do this before I apply for funding.  Is this correct?

I have no idea how to go about this and if it is even feasible, so any advice you can give me would be great.

Many thanks,
Kate

In the UK there might be one or two early career fellowship schemes that you could apply to. Some have restrictions on when you finished your PhD and require the hosting university to provide some percentage of the funding. They are competitive of course but it sounds like a good fit for your situation - you have a good idea and relevant experience and all you need is someone sensible enough to fund you.


How many weeks of break (per year) should a graduate student reasonably expect to have? Here are the details for one of my schools so far:

At UChicago, my prospective adviser said that I should expect to have around a month off per year (probably 2 weeks in winter and 2 weeks in summer).

It's probably fairly reasonabl, though it came as a bit of a shock at first but that was because I was used to being an undergrad where I had at least 2 months off EVEN if I included courses during summer quarter.

I'm on a fellowship for my first two years, but I'll still be pushed to produce results (I'm basically being trusted to do a highly ambitious project).

The official answer depends on where you are located, and the applicable laws in your jurisdiction. For instance, in Germany, graduate students are almost always employees of the government, and are therefore accorded vacation benefits commensurate to that (between 23 and 29 days per year, depending upon age). In contrast, the United States technically does not have any requirements on annual paid leave, so the answer in principle could be as little as zero, but normally is two weeks per year.

Unofficially, that's a matter to be worked out between you and your advisor. Some advisors will be willing to let you take days off here and there as needed, so long as they don't interfere with either your long-term progress or meeting your day-to-day responsibilities. Most advisors will be rightfully displeased if you ask to take two months of leave all at once, but most will not mind a three-day weekend here and there as needed.


Professor told me to organize a lecture course I am a PhD candidate. My advisor told me to make and organize a lecture course, for which he is formally listed as the instructor, but he has little knowledge about what the lecture course will deal with. I have more knowledge than him.

Students attend class two times per week.

One day, they give presentation about paper reviews related with this course.
The other day, I conduct the class and give them knowledge in order to understand papers. In both days in a week, he does nothing.

I don't think it's normal.

Even though he gives me many thanks for conducting the class, my feeling isn't going well. Even worse, I don't get paid.

However, because of a (de-facto) vertical relationship between him and me, I don't know what should I do.

I am not sure an ethics committee can protect my privacy.

Main thing here is that you provide work that is not paid.

(Assumption: studying and working in academia is not volunteering or philanthropy. Not quite clear what culture would have to do here. If you feel wrong about the situation, seems that you agree with this assumption, and you're not confusing exploitative situations for real opportunities.)

If that's an opportunity that's offered to you, the local unit/department/centre/faculty ought to offer remuneration for the work you provide, either for preparation work only, or for both preparation and delivery. In other words, the staff member should (have) arrange(d) the practical and financial details for the opportunity.

A 'research ethic committee' has little to nothing to do with the situation you describe, as the situation does not relate to your doctoral research activity. The situation is not about research ethics, it's about professional ethics.

Have you talked to your local administrators/support staff to enquire informally about the affluence of the local unit? Simply, is there money somewhere to cover for the work you contribute? Can they afford to provide you a remuneration that is a fair reflection of the work you provide?

Have you talked to your head of department about the situation? Colleagues might not be aware of the situation, and might disapprove, and help you out, of it.

Last but not least, are there union reps on your campus that you could approach for informed advice?


Methodology of defining a research topic My adviser asked me to come up with a research topic for a PhD student. As I'm expected to graduate in early 2016, my mentor considered this a good "exercise" for a tenure track career. Of course, this is not intended to be final, I am supposed to propose to my adviser this topic and then it will be decided whether it is good enough to suggest a direction of a student's research.

Based on the field of interest, I intend to propose a problem which I find interesting (and would gladly research myself, if the time permitted). To that purpose, I defined a number of milestones, covering some likely scenarios in the research progress. I also prepared around 20 papers, some of which serve as an introduction to the problems of the field of interest, while others are state-of-the-art approaches closely related to the topic.

This is basically more than I had when I begun my research. So, in that regard, I'm confident that I did a reasonable job so far. Of course, if you have any remarks, don't hesitate to add them.

My problem is that it would currently be very hard for me to come up with more than 2-3 topics prepared in that way.

Also, I can't help but wonder whether the topic I would suggest is "good enough" to lead the student to conduct quality research and eventually to a PhD. In this particular case, my mentor will shape the topic and guide the student so there is no worry. Besides that, I am confident that the suggested topic is a problem in the field, as I thought and investigated it a long before the request came from my adviser.

I find it a bit hard to believe that I'll always have such problems ready in my head, so I assume that I'll have to start from somewhere in forming one.

So, what methodology should I follow when defining research topics?

I think this is a great exercise.  One of the hardest things to cope with in the transition from graduate student to PI is broadening your focus as you move from a "worker" role toward a "manager" role in research.  This doesn't mean you're not going to be continuing to research, but you'll likely have a lot less time to do it than you think, and you need to prepare for how you will supervise where previously you would execute.

That said, I think you're currently approaching this too much like you are going to be the one doing the research, rather than their supervisor.  I would suggest limiting yourself to finding a topic, milestones, and rough criteria for success: the rest is what you want to coach a student as they look into the background, compare in depth with alternate approaches, etc.

The other thing I would advise is that you need to separate your research goals from the goals you want the student to work on.  Every student is a gamble: some work out well, while others drop out, burn out, should never have been in the program to begin with, or just plain aren't a good match for you or your research area.  For this reason, I believe you should never have a student be critical path on an aspect of your research that deeply matters to you: that will put you in a position where you are likely to be trying to push them and micromanage them, because you are worried about the success of the work, rather than the success of the student.

Instead, think about the "paths not taken" on your research, the things that you think would be interesting and scientifically valuable, but that you aren't going to do, the sort of stuff that pads out many papers' "discussion" and "future work" sections.  These sorts of "sibling projects" to your critical path are likely to be a rich vein of seeds for student projects.


How to choose a generalist repository and what risks should I be aware of? I am trying to choose between these different generalist repositories:

Zenodo
Open Science Framework
Figshare (or Dyrad??)
Harvard dataverse
General cloud services
...

Figshare has a nice comparison of them (
https://doi.org/10.6084/m9.figshare.751546.v1), but I was looking for some guidelines to help me to choose the best one that I might have ignored. For instance, many European Projects require to use Zenodo so maybe is better to get acquainted with it, however, Open Science Framework seems to offer a better way to organize the projects but it seems there is no doi to the files uploaded. Is there any guideline or anything I should be aware of before choosing to put my dataset in a generalist repository?
Content I would like to share
I would like to use a generalist repository because I would like to share all my outputs. This might consist of code, dataset but also figures, drawings and some times I share also some piece of hardware design (e.g. step files for 3D printing the adapters, sensor net, some PCB design).

I haven't used any of these resources myself but hopefully the following points can help you in your decision:

This kind of repository and the open science trend in general are pretty recent. This is why it's a bit difficult to evaluate and compare the different options, there's not enough hindsight yet. This is also why, in my opinion, the main risk is that the platform you choose would become obsolete or disappear in the future. So to be safe you might want to choose a platform which allows you to export your stuff easily.

Another important point you should consider is the policy of your institution: the outcomes produced as part of your academic job can be subject to IP restrictions. So it might be a good idea to check with your local IP or legal office what kind of license they allow/recommend and whether there is any IP disclosure process in place.

It's also worth mentioning that there are a few more generic options for sharing outputs: for instance Github, Google Drive, and of course the good old personal webpage (most universities let you create one under their website).


Do Professors Get An Education "Allowance"? One of the most common things I think any students has seen is walking into the office of a professor to a miniature library of textbooks and books geared towards disseminating research to researchers and practitioners. I am wondering how often these books might be paid for out of pocket or if it is common for universities to pay for these books as if they were something like an educational allowance.

How do universities (if at all) try to financially support professors in their continuing education?

I understand there are travel grants for conferences, but I am wondering if professors can take MOOC's or purchase books to help them explore new research areas and receive financial support from their academic institutions?

This is probably as variable as the educational system generally. But I'd doubt that more than a few professors get special allowances for such things.

Some of the books you see are text books given to professors by publishers in hope that the professor will adopt them for a class. Some of them are "ancient" texts that the professor used as a student back in the ice ages.

Some quite useful advanced books might be given to a professor by some publisher when the professor adopts some elementary text. It is a form of bribery, I suppose.

When professors retire they sometimes open their own bookshelves to their colleagues (or students) who are free to carry away things that interest them. Some books actually wind up in boxes outside a professor's door and others are free to expand their own libraries with them. Sometimes such books actually have some educational value.

Some of the books are funded by grants also, but normally grants from funding agencies outside the university.

A few new professors will get some "start up funds" from a university department and while intended for bootstrapping research, books and papers are part of that.

I accumulated hundreds of books over the many years. Some were donated to educational systems in Kenya eventually. But I still have far too many. No one other than publishers ever funded them, however.

Generally, however, the salary of a professor should be high enough to support quite a lot of such things out of pocket. I paid for professional memberships myself, for example, which generated a lot of journals on my shelves.


How do universities deal with the length of assignment submissions (e.g. word count) in pdf? My university requires all written work (essays, reports and dissertations) to be submitted electronically in Microsoft Word format. At my previous university, PDF was also acceptable (in fact, recommended).

In the UK, where I study, assignment length is determined by the number of words (not pages, as is usual in some countries).

As a LibreOffice user, submitting in Word format regularly results in formatting issues for which I can lose marks. The university has sympathised with this, as well as my ultimate preference of being able to use LaTeX, but insist it is not possible to accept PDF files because they can't easily do a word count.

Looking at other UK universities, it seems that a majority accept PDF submissions either exclusively or in addition to other formats. How do they deal with the issue of assignment length?

My only direct experience with this kind of academic word limit has been with my Master's and PhD dissertations. In both cases the official submission was in hard copy. Under those circumstances, I find it vanishingly unlikely that anyone did a word count -- I suspect that at my university, the word-limit rule would only be invoked if someone submits something that's blatantly too long (e.g. a 500-page MSc thesis).

I would guess that other universities deal with the issue of PDF word counts either by not caring much (as in the case of my dissertations), or simply by counting the number of words in the PDF: despite your university's insistence that this is impossible, there are dozens of free tools, both web-based and downloadable, which can accomplish this task. Even without those, Adobe Reader has a "save as text" function which produces an easily word-countable plain text file.

Another possibility is that those universities set the limits in terms of pages, not words.


Will my American GPA be 'transferred' to an Australian university? I'm a first-year medical student within the United States considering a move to Australia. I am not looking at a "study abroad" or "foreign exchange student" type program. A direct move and goal to be a citizen, living there indefinitely.

As of now, my academic marks (GPA) aren't the best they can be and I am concerned that they will follow me towards Australia if I decide to move there.

If I transfer between the two countries is my United States GPA considered or used by an Australian university? If so, how?

While every university is different, it might play a part of the admissions process, but after that, probably not, no. It’s likely that you won’t even receive credit for the units that you’ve done directly; instead, you’d ask for Recognition of Prior Learning (RPL) and they’ll look at the units you’ve done and compare them to the units you’d need to do for your new degree, then give you non-graded passes for the units in your degree that they felt were roughly equivalent in content and teaching level.

Additionally, most Australian universities mark on a seven-point grade scale, ranging from 1 (Low Fail) to 4 (Pass) to 7 (High Distinction), which wouldn’t be directly comparable to the American 4-point system.

Source: I’m an Australian who transferred between two different universities and degrees during his undergraduate, and is currently doing postgraduate study. This is just my personal experience; I’m open to being corrected by someone with experience working in a university’s admissions office.


Add a Collaborative Report in my CV I'm applying to a PhD program in Biostatistics. Two years ago I was member of a team crew hired by the United Nations to write a report on security. This report was published last year and has my name on it in the Statistics section. A summary of the report is publicly available.

I am considering including this report as a publication but I am concerned that an admissions officer may think that I am inflating my CV.

Should I include this report as a publication on my CV?

These kinds of grey literature are often included in CV's but it's important to be clear about the nature of the publication.  I would put this after any peer reviewed journal articles and conference proceedings papers in a section titled something like "technical reports and other manuscripts."   If you don't have any other publications, then it may make sense to simply describe the project (and what you did on the project in particular) and mention in passing that you were a coauthor on the project report.

For someone just applying to a PhD program, this will look good on your application and certainly shouldn't hurt.


Is first authorship a big deal (in terms of highlighting it on CV, etc.)? From August 2015 through August 2016 I was on a Nuclear/Radiation Physics based work placement in a scientific research institute, between my second and third years of my university Maths degree. I am now back at university, half way through my third year.

About half way through my work placement (which I thoroughly enjoyed), my supervisor suggested that the work I was doing could be considered publishable. Being an undergraduate this was (and is) obviously a very exciting prospect. It turned out that we did decide to write a paper, and my supervisor said to be that I would get to be the first author. I don't understand much, but I'm under the impression that's something to be excited about too.

I finished with all the analysis and wrote a draft of the paper. It was then time for me to leave my placement and my (now ex-)supervisor are still in correspondence, whilst he finalizes the paper. There have been various (unrelated) issues which have held him back from spending time on it - but he suspects (as it stands) that he will possibly finish it and submit it to a journal by the end of February. He's basically completely reformatting a lot of the paper, and probably rewriting a whole bunch of it, because being an undergraduate I have no idea how to write a paper. Of course this means that if I do turn out to be first author, my supervisor has probably been very generous.

Long story short - if things go well and the paper is accepted in whichever journal, is this a big deal or nothing to be so bothered about? I ask basically to figure out where this ranks in terms of putting it on a C.V. (or something). Is this something to simply add on as an achievement, or something to really highlight?

I understand my question is really rather ambiguous. Essentially I'm really not sure what to expect under the circumstances that the paper is published - if anything.

As mentioned here this is field dependent. Given your former advisor offered you the first authorship and assuming that if ordered alphabetically he would be the one to be the first author, then yes, it is something to be excited about.

In my opinion better than highlighting in a CV that you were the first author it would be better to describe what you did in that paper yourself and what was done by the other author(s). And maybe even better that putting this to CV would be to put in to a motivation letter (or any other text accompanying your CV in an application somewhere).


Editor says "the paper will not be acceptable within a reasonable number of revisions": is it worth appealing the rejection? Given the editor's comments reported below, is it worth appealing this rejection or one should submit to another journal?

  At the rate of improvement that has occurred over the last revision,
  the paper will not be acceptable within a reasonable number of
  revisions. Consequently, your paper is being declined. The reviewer
  comments are very helpful and should assist you to prepare the paper
  for consideration in another journal. Reviewers' comments on your work
  have now been received. You will see that they are advising against
  publication of your work. Therefore I must reject it. For your
  guidance, I append the reviewers' comments below. Thank you for giving
  us the opportunity to consider your work.

Appeals are usually intended to be pursued when you think there was a serious procedural problem with the way your paper was handled, resulting in a decision that was not properly based on your paper's content.  Some examples I might think of:

Reviewers were not qualified to judge the paper, or their reports were of extremely low quality (suggesting they may not have read the paper or given it serious consideration)
Editor or reviewers have a conflict of interest
Editor or reviewers show evidence of bias or prejudice against the author
Other unprofessional behavior on the part of editors or reviewers

None of that seems to apply here (unless there is something you haven't mentioned).  It sounds like the reviewers read your initial submission and said it wasn't acceptable for publication as it was; it needed significant revision.  You made some revisions but they are not satisfied.  So you still don't have a version which they consider suitable for publication.  If the editor thought it was worth the time to keep revising it, he could let you do that, but he doesn't.  So your paper is rejected.

It sounds to me like this decision was properly made based on the reviewer's opinion of the paper's content, with which the editor concurs.  You may disagree with that opinion, but simple disagreement isn't grounds for appeal - you'd have to show the editor and/or reviewers did something objectively wrong.

So submit to another journal.  But first, go through the reviewers' comments carefully, and make the changes you feel are appropriate.  They might need to be extensive.  Reading between the lines, it sounds like the reviewers didn't think that your revision did a good enough job of addressing their concerns, so maybe you need to think more carefully about what they said.  The reviewers for the new journal may well have the same concerns.


How to cite an article from a magazine (no date, published quarterly) in MLA7? I’m writing a comparative research analysis for my freshman writing requirement class on the school-to-prison pipeline, and I’m trying to cite this article by John DiIulio. The site doesn’t give a date of publication, and I can’t find any dates online for the print publication date; all I know is that it was the spring edition of 1996.

How do I cite this in the MLA7 style?

The relevant citation is provided in the site itself.
 My Black Crime Problem, and Ours by John J. DiIulio, Jr.
 City Journal, Spring 1996, pp. 14-28

To cite in MLA7:

DiIulio, John J., Jr. “My Black Crime Problem, and Ours.” City Journal, Spring 1996: 14-28. Print.

Hope this answers your quesion.


How much do figures need to differ to avoid copyright claims? It sometimes arise that I need to use, for an article, a book chapter or any other written work, figures that I have already published (not figures published by others). These are usually schematic figures explaining what a chemical or physical system look like, how an algorithm works, etc. Thus, instead of reusing the exact same figure, I can easily create another one, conveying the same message with (more or less subtle) differences in presentation.

However, I have no idea how to answer the following question: how different need two figures be to avoid the second one infringing on the copyright of the first? What is a good rule of thumb to be used? Is it enough to change one of the following:

color scheme
viewpoint of a 3D visualization
moving around blocks in a 2D diagram (or mind map)
changing axis properties (labels, tick mark positions, etc.) in a graph

In general, I would argue that the new plot needs to do one of two things:

present materially different content relative to the old image
present the same material in a different context.

Graphs are generally visual representations of numerical data. The numerical data itself cannot be copyrighted (because the data are "facts"), only the presentations thereof. However, simply changing axis labels or colors, and other similar "gloss" changes, don't really make the graph any different. Rotating a 3D graph, or changing significantly the relationship of blocks in a mind map or diagram to show off different features would represent a change in the message and presentation, and therefore would be OK.

However, chemical structures and mathematical equations are not normally considered subject to copyright, as they represent "facts," and cannot be arbitrarily drawn or represented; there's only so many "legal" ways to write them. That said, cutting and pasting somebody's figure from another article would be a copyright violation; recreating it yourself would not. (Otherwise, we would never be able to write E = mc^2 without it being a copyright violation!)

If there are doubts, however, you can always try to contact the journal in question. If needed, you can ask for permission to reuse a figure, especially if it's one you've already created. Most journals already permit self reuse, so long as you include an appropriate credit and citation of the original.


Techniques for teaching reflection and critical analysis to unprepared students I have a group of undergraduate students who are best described as 'unprepared' meaning that they were not well prepared for life in university. They are, as a group, under-performers, although there are certainly stars contained within the group. One more point of complexity is that the students are studying in English, which is not their native language.

Reflection is something that has been identified as useful not just for performance while at university but also for encouraging life-long learning for the students. While strong students might take to reflection quite readily, critically analyzing the countless decisions that they have made on any given academic project, unprepared students seem to have a much more difficult time with this.

My question is, are there particularly effective techniques for teaching reflection to unprepared students (or academically weaker students)?

Almost certainly this is going to be a multi-stage, complicated process, with no simple answer. However, here's something relatively simple to start with, maybe.

I'd suggest starting with collaborative peer-evaluation. Create an assignment which has a peer-evaluation stage (with no reflection on the final grade). The peer-evaluation stage consists of sitting them down and working through each person's output as a group. Ideally, you'll act mostly as guard-rails for the discussion, keeping it on-topic and professional, while providing some initial thoughts.

The goal of the peer-discussion phase is to start getting them to think critically about the output, from both the perspective of a creator and a consumer.

After the discussion stage, then allow them to take the feedback and re-edit their work to improve it, grading only the final result.


Do I need to have teaching experience before entering grad school? I'm considering going back to graduate school, but I've heard from a number of friends that graduate students are all required to teach. Is that the case? I have no teaching experience at all. Will that negatively affect my chances of getting in?

In general, no, it won't. Having teaching experience might weigh in your favor in exceptional circumstances (a graduate department that needs a lot of teaching assistants, and you're "on the bubble"; you're going into an education program or something similar; or the application specifically asks for teaching experience).

However, most graduate schools don't expect that students have prior teaching experience, and provide training to smooth the transition.

Teaching load also varies widely from program to program: some science and engineering students TA for one semester over a five-year program, while humanities graduate students may have to TA every semester to pay for their studies.


Why are meta-analyses the most quoted type of research paper despite being often flawed? Meta-analysis represents the statistical pooling of several individual studies focusing on a specific research question, ideally conducted within the context of a systematic review of the scholarly literature.

Several examples of meta-analysis are available, with the first ones already appearing in the mid '50s, despite this term being proposed first by Gene Glass.

Indeed, it appears that meta-analyses continue to have substantial success in the scholarly literature, and often appear among the most quoted types of research design. Yet, a plethora of meta-analyses of suboptimal quality is being currently published, and this unfortunate trend does not appear to cease.

Which are the main reasons for this success? And, most appropriately, is this scientifically sound and reasonable, given the epidemic of meta-analyses often of suboptimal quality (Ioannidis 2016) or overlapping in content (Biondi-Zoccai et al, BMJ 2006)?

Disclosure: I am the first author of Biondi-Zoccai et al, BMJ 2006, and I have coauthored dozens of meta-analyses.

You have it backwards.  Meta-analyses are not heavily cited despite frequently being flawed; rather, they are frequently flawed because meta-analyses are heavily cited.

Because meta-analyses often were high-impact papers, many people with poor training and little experience tried to publish their own meta-analyses, in the hope of boosting their C.Vs.  It's (mainly) this flood of incompetent authors who are publishing flawed studies, and dragging the whole field down.

  The increase is a consequence of the higher prestige that systematic reviews and meta-analyses have acquired over the years, since they are (justifiably) considered to represent the highest level of evidence. Many scientists now want to do them, leading journals want to publish them, and sponsors and other conflicted stakeholders want to exploit them to promote their products, beliefs, and agendas. Systematic reviews and meta-analyses that are carefully done and that are done by players who do not have conflicts and pre-determined agendas are not a problem, quite the opposite. The problem is that most of them are not carefully done and/or are done with pre-determined agendas on what to find and report.

--We have an epidemic of deeply flawed meta-analyses, says John Ioannidis

Eventually, hopefully, journals and authors will become more aware of this and the poor-quality reviews will be ignored, correcting the problem. As evidence for this, we see a number of guidelines and resources for improving meta-analyses becoming more widely used over the past few years:

IOM
PRISMA
MOOSE


How to obtain a fair recommendation letter from a professor who knows me via course, not research? The normal case is that students should obtain a recommendation letter for graduate school from the professor under whom the student has performed research.

Currently, I am taking a course conducted by a field-famous professor, from whom I wish to obtain a recommendation letter for my grad school application. However, due to some reasons, I am not able to do research under him, which implies that our only connection is that course that I am currently taking.

If so, maybe one year later, he may refuse to write me a letter, because he does not know me well, or even has forgotten me. Even if he is willing to write me a letter, being not familiar with me, he may not be able to write a decent letter for me.

(By "decent", I mean a letter that actually can help. I know that as long as he is willing to write me one, he can simply say "the student obtained a good grade from my course". I don't think this kind of letter will actually help, IMHO.)

So besides obtaining a good grade for this course and frequently asking valuable questions, what can I do to impress him so that I can obtain a decent recommendation letter for my future grad school application? How to make him understand me better?

Visit the professor and explain your plans and your wish to have him provide a letter in a brief but structured way. Slip in some of your (positive) thoughts concerning his course and, if you were inspired by it, the importance of the course for your current interest. I do not think you can do more. If the person is not interested, I doubt you can do anything to change the view that would not be annoying in the end. It is possible the person has forgotten you but if you stood out even a little in the class, my bet would be the opposite. As I see it you only risk getting a no, and not much could be done to change that.


How can I improve my chances of receiving PhD funding (UK, Anthropology)? I have been accepted to UCL and Oxford for a PhD in anthropology, however I have not been offered funding for either position. I am considering reapplying next year and I would like to know how I can improve my chances of securing funding. I already have experience as a research assistant for my MSc supervisor, and she has acknowledged me in a recent paper. I have also presented at a conference, though I have not published the paper. Would publications improve my chances, even if not in top tier journals? What other things could I do to make my application stand out to funding committees?

I should add that this is my second attempt - I was in the same situation last year when I applied only to Oxford for a PhD, gaining acceptance without funding. I received my MSc from Oxford, with an overall grade of 67 and a distinction in my thesis.

Funding is extremely scarce, especially in Britain. Since you have been accepted, I would write to the person who you suspect would be your adviser if you matriculated and ask them for advice. The program clearly has an interest in bringing you in. They may be able to find fellowships or paying jobs within the university that can help you financially.


Creating dataset by scraping YouTube? I'm trying to build a large dataset of images for training a machine learning model. My idea is to generate these images by grabbing frames off YouTube videos. My question: would this violate copyright laws if the frame comes from, say, a movie? Would I be safe to openly distribute this dataset for other researchers?

According to this: http://tubularinsights.com/youtube-copyright-ownership/

People / Entities / Conglomerates still retain at least some rights to their own videos most of the time.

So yes, if you come across any licensed material, for eg. grabbing frames from videos of movies etc without seeking permission first and the original owners find out, then you could get into trouble.

You could handpick videos / create playlists that you want to scrape making sure that their content is not commercially licensed or is used with permission of the original creators (I think you typically do this with the publication that follows / describes your dataset, if you choose to do that)


Scholarships and the PhD thesis in the Scandinavian system? I'm totally confused about how you have to write your desired thesis in the Scandinavian higher education system when you've got their scholarship. By reading the articles about how it works I feel that I have become more disoriented.

When you read promotions about hiring new Ph.D. students in the universities' websites or places such as Scholarshipdb.net it's often said that you have to do research on a particular field. Is this research counts as your dissertation or you have to do your own thesis aside from that?

From what I have seen (a whole bunch of PhD students, though I have done my PhD elsewhere) is that the research PhD students do is going to be the content of the thesis. The thesis contains two parts, the manuscripts/articles published, and a coherent story based on the work.

So the thesis is a product of the research the students are doing during their PhD.

Now, this might be different for some fields, or funding situations, and quite likely, for industrial PhD positions.


How to write a math abstract for a conference in an experimentalist dominated field without "specific numerical results" Note that in experimental fields it is not uncommon that an abstract is required to have "specific" unpublished results 9 months or so before the conference. The problem is if you are a theoretical/mathematical researcher in these lab based fields often your mathematical model and derivations are the crux of your research and a numerical exploration comes later. How do you write an abstract for these fields highlighting that you derived the model, proved a bunch of existence and uniqueness properties (that they likely don't care about) and have just started your exploration of numerical examples (likely the only thing they care about) without having anything definitive to say yet about your numerical examples.

The most definitive thing I could say about the numerical examples is, "We show that for a given set of parameter space we observe X and for another set of parameter space we observe Y. This is the consequence of X being true in contrast to Y being true in our field of application". To be clear I don't know anything about the structure of the parameter space that yield the two distinct X and Y scenarios yet, but I do know that both X and Y are possible given some preliminary simulations, and that the difference between X and Y is interesting.

One thing to note is this is not a conference that includes a proceedings. You have an abstract and a talk, but no paper comes out of it. Papers are strictly for peer reviewed journals in this field. The answers to this question How to write abstract for conference when you have no results yet? seem to be more geared towards fields where papers come out of the conference.

Writing as a mathematical modeler in Epidemiology, and a regular submitter to conferences with these types of requirements, which are dominated by empirical research findings, this is something that's hard, if you approach it from the direction you have - with the numerical results coming at the "end" of your research.

It would be good to have a numerical result, because as has been mentioned, while you might not view these as the crux of your research, it may very well be the crux of why someone is interested in your research. Even as someone who does appreciate the theory side of things, I'm often rather more interested in the numerical results.

That being said, these conferences are mostly looking to avoid "Will be discussed" results, where there's no means to evaluate if you've done anything, or if it will be interesting. The latter is especially hard for deciding whether a presentation becomes an oral or poster presentation, because giving one of the precious oral slots to someone whose going to largely be discussing a slew of null results is (often) irksome.

You do however have results, and that should be enough to make it past the bar. If X and Y are both possible within the parameter space, and that means something for the field, then that is a specific result, and you should expand on why that's interesting.


Grad school without GRE? I am thinking about going to graduate school soon after getting my B.A but I don't know if my background will let me in/what I can do to get in.

I have an A.S and almost a B.A in marketing. Since High School I have worked in a corporate office in the marketing department. I have had to pay for college myself because my family and I don't have a lot of spare money so the entire time I'm in college I'm working a full and part time job, otherwise I wouldn't be able to stay. My grades aren't the best B-C average because of everything I have to take on just to go to school.

I also never took the official ACT or SAT. I have severe ADHD so the longer a test is the worst my grade gets. I took the practice SAT exams in High School and did beyond horrible but once I got it back and it showed all my wrong answers I was surprised by how simple the questions were and that I got it wrong when I knew the answer.

Anyway, my main questions is that I've seen people get in to grad programs without a GRE before but they were 4.0 students with 2 B.A's. I know I can take the GRE but I'm sure the test results won't show my true academic knowledge. Does anyone else suffer from ADHD in this way that can give advice or even the likeliness of getting into a grad program without the GRE?

EDIT: I was confused by the SAT and GRE. SAT was changed to GRE

You seem a bit confused.  The SAT/ACT is a test that most American students take to get into an undergraduate program.  Once you are in an undergraduate program these scores become irrelevant (except possibly if you want to transfer to a different one), and they definitively become irrelevant once you have an undergraduate degree.

The exam that most students take for American graduate programs is the GRE.  Having said that it is indeed quite similar to the SAT: in fact, the last time I looked the quantitative section was almost identical.  If you do not do well on timed tests in general then realistically I don't think the GRE will be much different.  (But it is probably worth a try...)

Whether you can get into a graduate program without taking the GREs depends mostly on whether the GREs are a required part of the application.  For many types of graduate programs (still in the US, of course; the GRE doesn't exist elsewhere) the GRE will be widely required, e.g. if you are in the arts or sciences.  For other types of graduate programs, maybe less so, but they may also have their own exams.  Anyway, you should just browse the webpages of programs of interest to you: they'll tell you whether the GRE (or some other test) is required.


Sending a full Transcript, or only a part? I have a quick question. I have to send in official transcripts to some graduate schools. I am trying to apply for Mathematics. However, since i am also doing a B.A in Philosophy and Economics, the last semester has no mathematics classes as I have some classes I have to take. I have the option to not disclose that in my official transcript and "cut off" the future semester. Would that be seen as disingenuous? I don't want the admissions to think I am "avoiding" mathematics, there is sim ply no math courses my school offers that I would like to take and I need some courses for my other majors.

I have just one advise: Be honest. Changing an official transcript to make you look better is not honest, and could get you into trouble.

Moreover, a semester without math does not necessarily look bad.


Is it ethical for students to be required to consent to their final course projects being publicly shared? In a course, students were required to sign a consent form to share their final course project. There were two options that they could choose from: either anonymous sharing or sharing with attribution/credit. There was no option to opt-out. But the scope of the sharing was not limited in any way:

I permit the instructor(s) to publicly post this work electronically or physically, and to digitally or physically handle the delivery, cross-posting, deposit, or other distribution of this work...

Is this ethical? Or would this violate any University policy in the US? I know that different universities have different policies but here, it seems, that students are being softly coerced to give consent since they need the final-project grade and it seems reasonable to assume most students would be somewhat fearful of asking to opt-out.

The red flag here is that the instructor is requiring students to sign away a legal right they have. What gives them the right? A university may reasonably make such a requirement as a matter of university policy in a few situations where that makes sense (e.g., as someone mentioned, it is standard that PhD theses are made public). But the instructor’s mistake and clear point where they are overstepping their authority here is their assumption that they can set arbitrary rules that have nothing to do with the educational goals of the course, and that students must follow as a condition of getting their grade.
We have
seen
this
before unfortunately.
US universities simply don’t endow their instructors with such absolute-ruler powers. In fact, as someone who was a department chair and experienced the administrative side of running a university, I can confidently say it would be very undesirable from the university’s point of view to give individual instructors the authority to make students sign legal statements whenever the instructor thought it was a good idea. To put it mildly, some instructors are less sensible than others and probably should not be trusted with these sorts of powers. Nor is this a recipe for consistent policy-making.
To be clear, an instructor can set rules on where a student sits during an exam, or impose deadlines for homework submission etc, since such rules are necessary to accomplish the goal of teaching and testing the students. But at the end of the day the instructor is required by the university to assess the students’ performance and assign grades, and may not hold the students’ grades hostage to arbitrary conditions that make the instructor’s life easier or help them teach future classes, showcase their teaching achievements, or otherwise achieve other goals tied to the instructor’s self-interest.
To summarize: yes it’s unethical, and violates the “don’t be a jerk” policy, and probably other ones.
Edit: I was asked to spell out the specific ways in which the instructor’s behavior is unethical. They are:

Coercion: the instructor is coercing students to agree to give up their legal and moral rights to control what happens to their project work, where this does not provide them any legitimate educational benefit tied to the course.

Abuse of power: the instructor is using their power over grades, a technical power they are given by the university but that’s supposed to be used only for the specific purpose or assessing the students’ work, to coerce them to behave in such a way. This seems pretty clearly done for the instructor’s personal benefit.

Violation of employer’s trust: the instructor is violating the trust their university puts in them to use the authority the institution is giving them only for specific purposes and in specific ways.

Note that versions of these sorts of behaviors are illegal in many countries. For example using the power of your office to benefit yourself has been the reason for many holders of political office to be sent to prison in the US, and for a president to be impeached. In this particular case the behavior is probably not serious enough for these laws to apply, but the principle is the same.


Should I start writing a paper early or after all research is finished? I am working on research that will lead to a paper. The research isn't finished but I've finished enough that I have a good idea of what the basic idea of what the paper will say and look like. Is it better to start writing the paper now and make revisions as my research progresses or is it better to finish the research, have firm conclusions already in place, and then start writing?

The concept of "finished" is problematic when it comes to research.  I think that the same quote applies as for art: research is never finished, it is only abandoned.

Less poetically and more pragmatically, it is often only in the process of writing that certain critical aspects of the work become apparent.  When a person is in the midst of working on a project, they tend to get very close to the material and begin to take as clear and obvious things that are very much not so for others who are not so deeply involved.  Writing one's work up in a scientific paper forces one to step back and build those gone-implicit arguments from the ground up (or at least it does if you are writing well).

This often leads to discovering unexpected problems, which lead to new literature searches, new theorems, new experiments, and even whole new perspectives.  I have had nearly the entirety of a paper change out from under me as we wrote it and revised it, and the work became much better as a result.

So, to return to your question, of when to begin writing up a paper.  My advice and experience is this: begin writing when you think you have achieved the key results that you want to build the paper around.  As you begin to do so, you will likely discover gaps that need to be filled in, which will shift how you write the paper, etc.  When the process converges, you know you've got a good paper on your hands, and it is ready to submit into the tender mercies of your dreaded peers.

Don't let yourself move forward with the research, though, to try to achieve the next key result.  It's fun and exciting to do new things, but you must also have the discipline to cross the Is, dot the Ts, and observe the little things that need to be corrected and might otherwise escape your notice.