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How to convert GPA to German Grade?
My GPA of bachelor is about 3.0, and I just want to know how much it would approximately be in German Grade? Would it be lower than 2.7 in German Grade?
I have read other questions on this website, but none of them could help me, can you simply tell me how to convert GPA to German grading system?

Have you looked at Grade Conversion Charts section of the Academic grading in Germany Wiki page?

Yes I read it completely but couldn't calculate my german grade

No. Don't even try.

A GPA of 3.0 is (usually) exactly a B, which is coincidentally 3.0 in German Grade. Note that this is an estimate. Also, the correct way to calculate it would be not to convert the GPA directly, but to go through the transcript and re-compute the average using the German Grade.
This is a tool I found after a second of googling:
http://www.foreigncredits.com/Resources/GPA-Calculator/
It has grade tables and even a calculator that can do the math for you.

thanks for your information. I have also found that tool, but couldn't work with it, i guess i have to spend some more time with it

This is actually wrong. the correspondance is more:
A -> 1.0 (best possible grade),
B -> 2.0,
C -> 3.0,
D -> 4.0 (barely passing grade),
F -> 5.0 (failed),
The linked tool converts a german 2 to a GPA of 4.0 which would correspond to straight As, which is clearly wrong

Without knowing the specifics of your system, no, it's not possible to tell you how to convert your grades (or anyone else's) from one system to another.
However, what you do need to know about the German system is that it works "backwards": a 1 is the best grade, and 5 is a failing grade. The "1,0" corresponds to an A or A+ in an American style 4.0-system, and then moves in increments of 0.3 or 0.4. 4.0 corresponds to a D, and anything below that would be regarded as an F.

yes i knew about the point which you mentioned. thanks anyway


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Applying for industry jobs: how early do you submit job applications?
I've heard conflicting advice on this, from 6 months prior to graduation all the way to "wait until after you've graduated so you can start immediately". On the one hand you don't want to give yourself too little time to interview, but on the other I understand that employers may want you to start immediately to fill a need.  Is there anything rude/impolite/weird about applying for a job knowing that you won't be able to accept an offer for several months?  Do companies routinely wait on Ph.D.'s to finish?

This may well vary by geography. Employers may be conditioned by usual notice periods, even if these don't apply to new grads. In the US, two weeks' notice is common, so employers may not be used to waiting for months. In contrast, the typical notice period in Germany is three months or even more, so employers will routinely hire someone today who hands in his resignation tomorrow but can only start at the new place three months later. This may also have an impact on expectations for recent graduates. Anyway, you may get (even) better answers at Workplace.

@StephanKolassa Good point about this being region-specific, and excellent suggestion for checking out workplace.stackexchange.  Quick search there and I came up with this post.

Another way this may vary on Geography: a PhD in France is a regular job. After finishing a fixed-period job, you are entitled to a fairly generous unemployment benefit for several months. The advice there is quite often: "wait for the stress of graduation to pass, then start applying" as most to all PhD students can afford to stay unemployed for a few months (as "unemployed after a PhD" does not mean "with no income of any kind"). So the social support system of the country probably does play a major role (as does your immigration situation - are you allowed to stay and claim the benefits?)

Most articles found by a search for "how long does it take to find a new job" state anywhere between 3-6 months. Anecdotally, both for myself and for my friends, this is quite accurate. This, combined with the fairly frightening statistic that unemployed people have a MUCH harder time finding employment, would lead me to strongly recommend that you start well before you graduate.
Most positions that hire PhDs are familiar with the nuances of hiring someone who hasn't yet graduated. I currently work in industry, and we've had a number of people who've had to take a few days vacation to defend their thesis. You should mention during the interview process where you currently stand in your PhD work so the employer knows what to expect, but from my experience it shouldn't be too much of a problem.
Do note that some positions require the PhD of their employees, so you would not be eligible for those types of positions until you graduate. I would still recommend interviewing anyways so you're not starting from scratch... you can just contact them and continue when you actually receive the degree.

What about applying for a position that requires a Ph.D. with the understanding that you wouldn't be able to start until after you graduate.  Is your company generally fine with waiting a few (3-6) months for students to finish before starting?

@SumedhJoshi Again, from my experience - you'll have a mixed bag there. In my current position, 3-6 months would not work. For some companies, that's fine. It depends on the nature of the business and the urgency they have in bringing in new hires. No straightforward answer there.

Some jobs requiring PhDs will happily give you a conditional job offer, conditional on being awarded the degree (in the same way they'll happily make offers "subject to references", or background checks, or whatever). Others will be looking for someone who already has the degree at the time of interview. Your recommendation of course holds in both cases, since applying is a good way to find out which is which ;-)

I have been involved in hiring several Ph.D.'s (math, computer science, operations research) in the finance industry in the US. (before returning to academia to get my own math Ph.D.).  In the US, the answer to your question is that the correct time to apply will depend on the type of industry job you are looking for.  My experience is that for jobs at larger companies which routinely hire Ph.D.'s you should start applying in the late fall before you anticipate graduating.  These companies generally have a well-developed recruitment process and are recruiting with the anticipation of bringing someone on several months down the road.  They may even plan to have you start with other recent Ph.D.'s and have some more or less formal training period.  (My experience is in finance where this is the norm, other industries may differ.)
For jobs at smaller companies or start-ups, I would recommend waiting.  Typically these companies are looking to hire someone who can start as soon as possible (six months is an eternity for a small company or start-up).
So I would recommend starting applications and attending recruitment events for larger companies in your field right now.  As the process evolves and the time until you could reasonably starts decreases, you should then expand the range of places you are talking to.

To clarify, by "late fall" you mean e.g. November-December if you plan to graduate in May of the following year, right?

@SumedhJoshi Yes, basically right now if you anticipate graduating in May.

"Right now" = not the answer I wanted to hear because it probably means I'm behind :).

@SumedhJoshi Ha, no you're ok (at least in my experience).  If it were February you would be behind.  For job applications in industry there are not generally formal deadlines though.  They want to hire good people whenever they are available.  But, just as a rule of thumb 6 months out is a good amount of time for the recruitment process to play out.

This may also vary along the size of the company and the plans that company has.

One scenario:

If a company wants someone just to complete a task, them maybe if you say on the interview that you will be available after three - six months then the answer will be something like that: We will contact you after this period, and believe me they never call you back. So, a good policy is to make an proposal for part time job untill you finish you Ph.D. (I know this is not easy in all times).

One other scenario:

If you apply to a big company with a long business plan then you can discuss with them when you are able to get started.
My suggestion is to start looking for a job two - three months before you finish your Ph.D.

From the company's point of view there are two different recruitment scenarios.
One is simply "maintaining the workforce" to replace the inevitable losses that occur over time. These are usually entry-level positions, and the main objective is to hire the right number of people who are "good enough". The skills and qualifications required are not specific to particular jobs; the successful pool of applicants will be fitted into the overall company structure in a (hopefully fairly optimal) way. This is more common in large companies than small ones, of course.
This type of recruitment is usually done on an annual cycle, and the timing of the process matches the normal academic timetable. It would do no harm to contact the company informally to ask them when they would prefer to receive applications. There is no sense in submitting an application that will not be processed for a few months, and may "get lost during that time.
The other scenario is a vacancy targeted at filling a specific position in the company. The requirements will be focussed on that particular role (even if the statement in the job advertisement seems rather vague and generic - a company doesn't necessarily want to tell its competitors exactly who it wants to hire!) and the objective is to fill the post as quickly as is practical depending on the local norms for notice periods, etc. If you apply for that type of job, being unable to start for a long time may be sufficient to reject you however well qualified you may be.
Such jobs are often not targeted at "first-job" college applicants either, since they may be looking for specific practical experience in industry.

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Tips for purchasing food and drink for a talk
Can people who hosted talks at your university provide some tips on purchasing food and drink for the event?
We have a visitor from another American university and I am tasked with buying "food and drink" for about an audience of 30 - 50 people. We are located relatively close to Starbucks but far away from the nearest supermarket such as Walmart. The talk will last two hours.
From what I have seen, people usually purchase donuts and coffee for these events. I have seen these coffee "crates", "barrels", (I'm not sure what to call them).
Can anyone provide some suggestions as to where you can purchase cheap, and standard meal for these talks? I have asked people around me but they seen to have no idea, our group don't usually host visitors and the graduate students used to purchase for these talks have all graduated.
(Again, in a North America setting)

Surely you can still send an e-mail to one of these former graduate students, even if they aren't around the lab anymore.

Do you have a car?  If not: find one of your locals who does have a car, and enlist their assistance for bringing the food/drink to the venue.  I’ve never owned a car and generally prefer to manage without one even in places where that’s considered ridiculous… but for group catering, I’ve learned from experience that it’s really not worth trying to be a hero and lug things around by hand.

@PLL - If the car thing is a problem, one could look into delivery options.  Where I live, one can get deliveries from the grocery store nowadays.  Funny how things come around eventually.  When I was a child this used to be possible and now it has been reestablished, in combination with online ordering.

Background: as an undergrad, worked with/ran my campus programming board (lots of food purchasing for events). As a graduate student, worked with grad student association to run the odd event. And have organized multiple lab events.
What should you buy:

Coffee and donuts are a classic -- you can't go wrong, especially if the talk is in the morning.
For a lunchtime talk, pizza is a cheap/popular option. Alternatively, subs are occasionally a good option (but more expensive and usually a bit messier).
For evening talks, aim for light hors d'oeuvres (cookies, mini-meatballs, cheese & fruit platter, etc.).
Alternatively, just stick with donuts and coffee for everything -- again, you really can't go wrong there :)
Don't forget napkins, plates, cups, plasticware, etc.!

Where you should buy it:

Starbucks offers what they call coffee travelers. Each has 96 fl. oz. (~2.8 L) of coffee and will keep warm for ~3 hours (in my experience). Be warned: you'll need to call ahead and order these (they prepare them fresh as needed).
For donuts: pickup 4-5 dozen donuts from a local donut shop (Dunkin' Donuts or Krispy Kreme in the U.S.). Alternatively, try contacting the bakery at your local supermarket -- given a couple of day's notice, they can probably prepare several dozen donuts for you to pick up.
The local supermarket (Kroger, Wegmans, Walmart, etc.) is actually a great place for placing catering orders like this. They can do pretty much anything - subs, baked goods, cheese & fruit platters, you name it. Many will already carry pre-made platters, so you don't even have to order ahead of time.

One last idea: contact your school's dining services. They're usually (a lot) more expensive, but they have some nice services such as:

All-in-one packages
Drop-off/cleanup services
Nicer linens/plates/etc.
Continous coffee carafes, water carafes, etc.

Last but not least -- get itemized receipts for everything. Businesses should have no problem providing these if you ask. Makes reimbursement much easier.

Most donut shops do coffee like that as well, so that can save a separate trip.  Also, do consider independent coffee/donut/bagel shops if you have some in your area, not just the national chains!

While cookies, donuts and chocolate are always a safe bet, I have seen that fruits and vegetables are highly appreciated as well. They are really cheap, but require some work, as apples, stem cabbages, peppers ... have to be cut into pieces of finger food size. Cutting and preparing plates for 50 people takes something between 30 and 60 minutes, depending on whether you just want to serve food or have a nice presentation as well.

+1.  I would just add that (at least where I live), one could, alternatively (if short on time), pick up the fruit and veggies from the grocery store, already washed and cut up.

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Scientific writing: When conducting a simulation on a personal computer, what specifications should you report?
(Note: Personal Computer  = Laptop)
When reading papers that involves some sort of numerical simulation of a software or custom code, many authors would remark on the specifications of the laptop for which the simulation is conducted. For instance.

Can someone enlighten me as to
What are some of the common specifications should you report? There seems to be no comprehensive list of specs that one must report. For example, the # of cores of your laptop, the brand/series, and RAM as shown above and ... what else, clock speed, frequency of your processor...
Can someone provide additional insights on how these specifications come into play when you are trying to reproduce or compare results? For example, if I simulated some algorithm on a dual core AMDdual opteron processor 275 with 32 GB RAM and try to compare it with the same algorithm quadcore Intel Core i7-2600 with 16 GB RAM, how do I go about commenting on how the simulation platforms affect the simulation results? i.e. does Bigger RAM necessarily means shorter simulation time? Does quadcore laptop necessary implies that the algorithm performs better compared to dual core laptops?

It depends largely on what you're simulating, to be honest. Machine learning and AI, obviously better specs lead to better performance, but if you were running a simulation entirely in Java, it boxes its own machine so running it on a gaming rig versus a notebook would likely lead to almost identical performance with default VM settings.

The details are not there to enable a completely scientific comparison or benchmarking across different machines, it's just to give other researchers a rough sense of the computational resources that were used/available in case they are considering trying to replicate or modify your simulation or compare it with their own code. You should report anything that seems relevant, e.g., if your code is GPU-based then include the specs of your GPU, if not then don't. If the color of the box the machine comes in matters, report it, otherwise don't. Etc.

A bit old this question, but let's answer. I split it in three different cases:
1. You want to say that the simulation can run in a reasonable time
In this case, I usually write "The simulation run for X hours on a standard workstation.". No details needed, you just want to show that it is feasible to run the simulation and give a very approximate idea, no one cares how much RAM/which CPU you have. The goal is only to show that it is feasible on a normal computer and if it takes 2 hours or 5 hours, it is not very important.
2. You want to provide the exact time
First of all, please don't run it on your laptop. Use a dedicated machine, with the minimal amount of software running to minimize the interference. Depending on the specific domain "minimize the interference" may require simple or very complex strategies. For instance, if you need to obtain the performance of your MATLAB code, you can just close all the other applications and it will be ok. But if you need the performance of a hard real-time program, probably you need to remove the operating system and write bare metal code.
In any case, it is essential to get many samples of the execution time and provide in the article average, variance/standard deviation and number of samples.
Regarding the specification itself, write the most important information: CPU, RAM, Operating System, Compiler/Interpreter version, any other information you think is essential to replicate the experiment.
3. You want to compare your algorithm with another one
This is the most complex case. All the consideration of point 2 applies. However, it is very unlikely that the specification provided by the other article are sufficient for you to correctly replicate the experimental setup, especially in General Purpose computers (for instance, how can you get the same exact software installed? How can you run the CPU at the same exact temperature that may impact performance?).
So, usually, what you should do, it is to replicate the original article experiment in your machine (by impementing their algorithm), where you will run then your algorithm. This is the only way to get a fair comparison.
Direct answers to your questions

does Bigger RAM necessarily means shorter simulation time?

No. Not even increasing the CPU frequency necessarily means reducing the simulation time.

Does quadcore laptop necessary implies that the algorithm performs better compared to dual core laptops?

No, it depends if the algorithm (effectively) exploits parallelism.

People might be interested in the RAM amount if it's close to a hard limit, e.g. the calculation completes with 16 GB but fails (or at least runs considerably slower) with 12 GB.

The specific CPU can be important in some circumstances, such as when a hardware bug is discovered after publication that may have affected the results.

"A bit old this question"  Time is relative ;)

If you know the details it is better to give them as you do not know how other people might be able to use the data in the future, especially bearing in mind that (a) you are answering a very old question (b) there is no such thing as a standard workstation (c) the very word 'workstation' can imply extra capabilities above and beyond a personal computer and (d) there is probably no good reason not to give it.

@Jool You can add sure but you are providing no useful information. The execution time on workstation/laptop/mobile phones are likely in the same order of magnitude, so for the sake of the feasibility it doesn't really matter. The point is: if you cannot provide an execution time measured in an accurate way, then it is no interest on the specific machine (clearly, if you used a HPC cluster is a different story...)


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Why is it that sometimes in bibliography, DOI information is added?
When I'm casually browsing through bibliography section of preprints, sometimes I find that an author will also include the DOI information in the citation.
For example, I just picked a random Arxiv paper from today: https://arxiv.org/pdf/2207.06887.pdf
Observe that in the citation section, some references have a DOI attached to it, but others do not.
I've observed this in many preprints and publications.

Is there a good reason to add the DOI information?
Why is it that sometimes certain references have DOI information, but others do not? Is this a citation consistency issue?

Thanks!

Yes, because it makes it easier to find the referenced document, but not all documents have an associated DOI.
In an arXiv submission, there's no guarantee of consistency, because this is up to the authors. For instance, the authors may have compiled the list of references from references downloaded from publishers' websites, which typically contain the DOIs, and manually inserted references from different authors, which might not be consistent. Instead, when publishing in a journal, the copy editor typically tries to ensure consistency according to the publisher's guidelines (well, the world is not ideal and not all do, but some certainly work reasonably well), either by adding the missing DOIs or other information themselves or asking the authors to make the additions.
A lot of software packages used to help researchers manage their resources (take genei.io) can use the DOIs to look up related papers and build relationship graphs that help when performing a literature search. This is beyond the obviously useful property of simply being able to generate a clickable link for you.

I'd like to add that a lot of research management tools can also parse DOIs for you and build relationship graphs of your papers

@ScottishTapWater Agreed, thanks for the edit!

it's good practice to include DOI links if the author/publisher can find them. Lots of stuff doesn't have a DOI but where one is available it's important that it persistently links to the content that the authors intended.
Disclosure: I work for Crossref (a nonprofit registration agency of the DOI Foundation) and we have about 130 million DOI records.
Publishers and others (about 17k of them as of today) join Crossref and commit to keeping the metadata up to date and ensure those links keep resolving in perpetuity.
Hope this helps!

Frankly, it's probably just a matter of some output formatting of reference manager software.  If the  doi is in the database, it gets included, otherwise it gets left blank.  On journal publication, page editors might demand better.

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Double-blind review: submit a follow-up paper in a very short time
My colleagues and I are planning to submit to a conference which adopts double-blind review. The deadline of the conference is in 3 weeks. The work we plan to submit is built on our previous work that has just been accepted 2 weeks ago.
The first paper was actually submitted 6 months ago, but it was rejected at the first time. That's why there is only a very small gap of time between the two papers.
We need to cite the first paper, and its title together with the list of authors already appeared in the list of accepted papers on the conference website.
We can try to cite it as somebody else' work. However, any reviewers can conclude that this is the work of the same group. In this case, do we violate the double-blind review policy?
How should we proceed? We desperately want to submit to this conference, waiting should be the very last option.

This is a situation that pre-prints can help with, in communities that are ok with it. It helps if the pre-print was up a while ago: you can cite the pre-print and say you build on that work, and then replace the pre-print cite with the conference paper cite in camera-ready. Unfortunately, this requires making the preprint available substantially earlier.

I've been in a similar situation before. After consulting with the conference chair, we decided to place an anonymized version of the accepted paper in a dropbox folder and cite it anonymously as our own with a link to that dropbox file in the reference. I also added a footnote in the paper to explain that this previous work is accepted but not yet published, and how this previous work contributed something totally different from the work presented in the paper.

In any case, do not cite your accepted paper as somebody else's work.
I've seen research presented in two parts in Conferences. Ask the organisers about that.
On the other hand, I just found out these guidelines:

Use the third person to refer to work the Authors have previously undertaken.

e.g. "...has been shown before [Anonymous, 2007]" instead of "we have shown..."

Cite papers published by the Author in the text as follows:  ‘[Anonymous, 2007]’.
For blinding in the reference list:  ‘[Anonymous 2007] Details omitted for double-blind reviewing.’

Other advice is given in this Q&A.

I have never been able to figure out how it can work out to review papers with these guidelines. Either there will be parts that cannot be properly reviewed because they rely on information hidden from the reviewer, or the reviewer does know those things and thus also knows who the authors are.

I think this is the way to go. You can also make a note and say that you can provide the still unpublished paper to the referees if needed. If the paper is really yours you should be able to remove the name from it easily!

@TobiasKildetoft I think that the approach described in @dsfgsho's answer is helpful in this particular case, especially, since the cited paper is not yet published.

The approach described is the general set of guidelines for certain journals, regardless of whether the cited paper has been published. What I don't understand is how it can work in practice to have such guidelines.

Putting too much honest effort in hiding identity can backfire spectacularly. We had a case where we most meticulously avoided indicating that a paper might be our own group's work (although we cited all relevant previous work). The paper was rejected because the reviewer said the "anonymous" we did not make sufficiently clear that we build on our "official" group's work. We did, but the reviewer clearly thought he did the "official" us a favour.

conference which adopts double-blind review.

Just remember that it's always "reasonable effort at being double-blind" rather than actual double-blind and your question becomes moot. You're doing nothing wrong by citing a recent previous paper of yours if it's justifiable on the merits ignoring the question of review.
H-o-w-e-v-e-r - check whether the conference has specific rules about these cases and follow them to the letter.


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How to write horizontally across the blackboard while keeping handwriting as horizontal as possible?
Does anyone have tips on good ways of writing horizontally across the blackboard?
I notice whenever I write across the blackboard, the line will have a slightly downward slope of 15 degrees and it is quite visible from afar. It sort of looks like the bottom left half blackboard of this picture.

Does anyone have any tips of writing across the board as horizontally as possible? My board is about 10 meters wide divided in two halves.

Just practice... Seriously, it is something that most people need to practice a lot to do it decently

Laser line level? (Not really a serious suggestion.)

@tonysdg commercialize it. Laser guided blackboard

@MachineLearningisnotGod: I unfortunately have the business acumen of a particularly-dim hamster ;-) Feel free to make your fortune if you wish!

Just don't let some self-proclaimed handwriting experts tell you that you are lacking self-confidence because of the downward slope.

Writing works different on different heights, so train writing at different heights. For me it is easiest to write horizontally if the baseline is about the height of my  mouth. Writing at the height of my stomach or my chest is almost impossible and I need much more care and it takes much longer. If you have to write at that heights, you could also squat down, but be aware that the things you write down there may be too low for some people in the audience.
If you can move the blackboard up and down, move the blackboard such that the line you write is on your favorite height.
Do not stand still and stretch your arm more and more, but move your whole body along as you write.
Related to the previous point: Use short lines. Two halves at a ten meter blackboard still make five meter long lines. Depending on the size of your writing, this may still be too long.
Try to get good chalk. I prefer chalk that slides over the board more easily. (The people over at mathoverflow have something to say about this, see here and here).
Try to adjust your font such that it helps you to stay on the line. Writing cursive for text (not equations) may work, but I think cursive needs more care on the blackboard.
If you practice, try to find a blackboard that has lines, a grid or crosses that help you stay in line.

+1 for writing at mouth height! Higher works as well, but anything lower is just terrible. And keep the lines short, 2.5m is absolutely enough! (Easier for you to write and much easier for the students to read.) An addition maybe, I'd like to keep one eye on the upper limit of the board, to check if I'm still parallel.


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Why isn't it common for papers in pure and applied math (and other related fields) to be modified/corrected after it has been published?
As research grows even more intricate in fields such as pure and applied math (and other technical areas), very few reviewers now have a complete picture of any single field. Thus it should be common for more mistakes to be published (in a journal or in a conference).
This said, it is very uncommon for anyone to (at least successfully) edit an article after it has been published.
Some reasons for editing may include:

a (reasonably minor) error has been spotted, e.g., a negative sign is missing, typos that are not simply grammatical mistakes.
an important reference that was missed.
a result which has been proven wrong because of a very technical edge case that everyone has missed, but was not essential to the proof.
simulation was off by a tiny factor
some other minor, and not detrimental issue to the paper, such as a misplaced figure, mis-referenced equation (cannot tell you how many published papers have [?] in them)

Nor are there really any mechanism in place to promote authors to fix errors after publication. Yet plenty options for authors to repeat upload till "final version".
I am very curious as to why this is the case.

The primary reason is that journals are "publications of record". They just record a specific version of a paper, namely the one that actually gets printed, along with important data such as who wrote it and when it was submitted.
You are of course free to put corrected versions onto your website, or maybe onto preprint servers. But in the end, that's not the "version of record" as you can change whatever you want on it -- you can add and remove authors, etc., and it's hard for anyone to track down when exactly a particular change was made if a dispute should arise who came up with an idea first. It's of course true that journals today could just do that on their websites: allow newer versions of papers to supersede older versions, but then that would require some kind of editorial process that journals are not equipped to handle.

Completely separately, though, I take issue with your opening statement: "very few reviewers now have a complete picture of any single field. Thus it should be common for more mistakes to be published". I don't think that there is proof that that is true -- science was difficult 50 years ago, and it is difficult today. I don't believe that authors or reviewers or editors are any worse equipped today to assess the contents of papers than they were 50 years ago, and so I see no reason why we should expect more mistakes.

I agree. Regarding the second part of your answer, note that in some fields of research such as biological sciences, reviewers actually are worse equipped today. This is because there has been a significant inflation in the amount of data required for a paper to be published, especially in top journals, resulting in much larger and more complicated papers.

To add to @WolfgangBangerth's answer:

We to have the tool of errata in place. If the mistake is non-negligible, but not so substantial that a new paper is warranted, write an erratum.

For books, we have editions. This could be done for papers as well, an indeed e.g. arXiv does that (calling it version rather than edition).

Papers are supposed to record the cutting edge of research. Thus, we expect or at least need to consider that their content may become outdated.

They give a record of what was known at the time of their writing. "Known" includes what the authors realized back then, not what the authors could have realized from their data had they already had the enlightening insightful thought that in fact happened only years later.
It is important to keep record of this, we do not want to muddle historical tracks.
It is maybe not worth while fixing typos & Co. a few years after publication in a situation where the reader anyways has to do their due diligence on updates of the topic/content.
The effort could better be spent towards gaining new insights.


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How are arXiv papers cited using IEEE citation style?
I have been trying to find an IEEE publication which cites an arXiv paper.
However, it seems that electrical engineers shy away from citing anything arXiv related.
I have been looking around for a while but couldn't find any, can anyone provide a reference to a sample IEEE paper that cites an arXiv paper IEEE style?

it seems that electrical engineers shy away from citing anything arXiv related — Weird. When I did a Scholar search for arxiv, restricted to the ieee.org domain, close to 37k results were returned.

I used Zotero to generate the following citation in IEEE style (see original paper here). You can manually duplicate it if you wish, but I highly encourage you to consider using a reference manager to make your life simpler.

J. Nettelblad and C. Nettelblad, “CannyFS: Opportunistically Maximizing I/O Throughput Exploiting the Transactional Nature of Batch-Mode Data Processing,” arXiv:1612.06830 [cs], Dec. 2016.

Also see here for more info on how to create a reference to a specific arXiv paper/version.

HI I downloaded Zotero, and after downloading the PDF, I right click on the PDF and click on "Create Bio from item", but it tells me "The items you have selected contain no references. Please select one or more references and try again.". How do I generate the citation like you did?

@MachineLearningisnotGod: Try this -- install the browser extension for Zotero. Then go to the arXiv webpage for the article and click "Save to Zotero". Should automagically download the paper and save all of the reference information :) Alternatively, you can manually enter it -- when you click on the PDF, you fill in the "Info" section on the right. But again, the browser extension makes this very easy (and works with a wide variety of sites!).

I see, it seems for some paper it just automatically generates like "R. Meir and D. Parkes, “On Sex, Evolution, and the Multiplicative Weights Update Algorithm,” arXiv:1502.05056 [cs], Feb. 2015.", but not for others. I tried it on two different pdfs, for one it just created biblio for me, the other says no reference info

@MachineLearningisnotGod: See qsp's answer. If you can get a .bib file, you can import that into Zotero and it should do the same thing.

Papers in arXiv are indexed by DBLP, which provides, among other things, Bibtex entries for those papers. Copy the Bibtex entry into your .bib file, and that's it. Latex will do the rest.

DBLP is very reliable and a good source for any bibtex entries!

A Google search on (ieee reference format arxiv) should find the IEEE guide.
https://ieeeauthorcenter.ieee.org/wp-content/uploads/IEEE-Reference-Guide.pdf
Search the guide for arxiv, which appears twice.

This answer would be more useful if you could quote the relevant portions. Also, the link may change any time in the future making the answer inaccessible.

In this guide, an ArXiv Paper is cited as follows: "S. Urazhdin, N. O. Birge, W. P. Pratt Jr., and J. Bass, “Current-driven  magnetic  excitations  in permalloy-based multilayer nanopillars,” 2003. [Online]. Available: arXiv:cond-mat/0303149."


text:
Why is that when your first upload a paper onto ArXiv, Google Search shows that it has been uploaded to "https://128.84.21.199"
Has anyone else noticed this?
When I uploaded a paper onto ArXiv, and after two days when it finally shows up on Google (in Google Search, of course), Google says the paper can be found via the link https://128.84.21.199/pdf/arxiv_ID_of_your_paper
This wouldn't have been a problem if wasn't for my browser issuing a warning before clicking on it

Can anyone explain what is going on here?

I'm voting to close this question as off-topic because it concerns an Internet problem, not academia.

That number is the IP address for arxiv. Typing "arxiv.org" into your browser is effectively the same as typing that number (the domain name will get converted for you).
Why the error? The HTTPS certificate is assigned to a domain name, not to the IP address (which is good, because IP addresses may change). Even though in this case, the domain name would result in this IP address, your browser thinks it is trying to use a false certificate.
To avoid this error message, just replace that number in the URL with "arxiv.org" and the error will go away. A worse workaround would be to replace "HTTPS" with "HTTP".


text:
Is it okay to add a lecturer on LinkedIn
I'm a graduate student and I recently attended a course by a very inspiring lecturer (associate professor).
Do you think it is okay add him on LinkedIn? Do I push him into an uncomfortable situation by doing that?

Have you finished the course or not? If yes, then there should be no problem, if no and you feel like you are pushing him then you can wait till the end of course - semester etc. Facebook on the other hand.....

Yes, i've already finished the course.

I wouldn't say he would have an issue, I've actually done it a few times; everyone is different - but what do you have to lose!

I do not believe an educator would feel they were put in an uncomfortable position by a student sending a LinkedIn request.
You should not, however, expect that the lecturer will accept your request. Some lecturers like to be very close to their students. Personally, I like to keep a professional distance from my students, even after they graduate. Of course, if a student happens to share a common area of research as me and wants to work together, that would be different but I certainly do not accept many requests to "connect" to students, even after they graduate.
What you should avoid is sending multiple requests or following up in person "Hey, did you get my 'quest? It would be super-kul if you'd add me." If they want to connect they will. If not, they will just consider you a student who is interested in having a closer connection than they want and they will ignore it.
Either way, I do not believe any lecturer would be made uncomfortable by your gesture of interest.

"You should not, however, expect that the lecturer will accept your request" is the key point.  Everyone's standards for contacts is different.  One may accept, another may not.  Do not be afraid to ask.  Do not be offended if you're not accepted, it's generally not personal, you may simply not fit the requirements.


text:
Formal Title for Someone with a Masters Degree?
We all know that someone with a doctorate is called a Doctor (or abbreviated as Dr.), is there a formal title for someone with a Masters degree? I've never heard someone refer to a person with a masters as "Master". I've also heard that Esquire is sometimes used as a formal title for someone with a masters, is this correct or is there another title?

In Italy, from the bachelor's degree on, we are all doctors, just with a different qualifier, but those with a  master's degree in engineering are commonly titled engineer, even if this title should be in principle reserved for those who have passed the exam to enter a professional society. So, for instance, I have a PhD but no one calls me doctor. Actually no one calls me engineer either. Luckily, because I hate titles.

I don't think "Master XX" is used in academia... Used in Star Wars though :)

In The Netherlands in Dutch, you would be Drs.

In the United States there's no formal pre-nominal title held by individuals holding a Master's degree that I know of, so it's very unlike Dr. Xxxx that one holding a Ph.D., etc. might be addressed. In text, you would address such a person with a post-nominal suffix like M.A., MBA, etc. I'm sure the logic is different among specific types of degree, where Esq. for Esquire is a post-nominal suffix for those in the legal profession in the US. To give you an example, though: If I hold an M.Sc., you might refer to me as "Kendall, M.Sc." if you wanted to address me in an email or letter, but I would realistically expect Mr. Kendall or what have you face-to-face.
I should also add that courtesy titles like Esq. or Mr., and academic titles don't get used at the same time. Kendall, Esq. M.Sc. would be wrong, as would Mr. Kendall, M.Sc.!

at the same time ... In Germany, one can be addressed: Herr Professor Doktor Schmidt.  And if he holds two doctorates, Herr Professor Doktor Doktor Schmidt

As a counterpoint, in Spanish speaking countries (or at the very least in Mexico) it is customary to use M. en C. (for Maestro/a en Ciencias), or its equivalent, as a pre-nominal title.

As a counterpoint, in Québec, it is illegal to use the Dr. prefix for someone with a PhD. Only Doctor es medicine are allowed, PhD can still use Dr., but it must be after your name.

A somewhat archaic title someone holding a Masters degree is "Magister". Similar to Doctor, it comes from a Latin word for teacher.
In the English speaking world, this title has essentially disappeared though, so would be met with incomprehension. In many other places Magisters degrees are conferred, but tend to be equivalent to  doctorate, thus making use of the term even more inadvisable (but a fun thing to know about).

whenever someone refers to me inappropriately I correct them thus:  "that magister evil.  I didn't go through 2 years of evil school for nothing."

The official title is "Master of xxx" for someone who has attained a Master's degree in a given topic. I have also heard the phrase "Mistress of xxx" been used for a female; though I cannot speak to whether it is a traditional title. However, as others have said it is now customary to address someone with a master's or bachelor's degree with a post-nominal suffix rather than as a "master" or a "bachelor".
The merits of the title have evolved over time -- in the late middle ages, someone who had been granted the title of master was typically eligible to teach at a university. In addition, in those times it was considered more proper to refer to someone as a master if they had earned such a degree in a university. However, having a higher degree in those times was much less common than it is today.
It is worth noting that this question was asked on the English stack exchange board as well.

http://www.merriam-webster.com/dictionary/master -- Note that the definition is a person holding the degree, not the degree itself.

http://dictionary.reference.com/browse/master?s=t -- The same definition holds here

If I come across any primary sources where the usage is seen I will post them here as well.


text:
Meaning of the term "studies leading to a degree"
I am slightly confused about the meaning of the term "studies leading to a degree" in an application form.
Does it mean only studies that lead to an actual degree, in which case incomplete studies that did not lead to a degree are not covered by this term?
Or does it denote any studies that were initially started as part of a degree program, irrespective of whether the studies were completed or a degree was awarded or not?

What is the usual context of the term?  If it's asked for in regard to current education, then it need not have been completed yet, as it's still in progress.  There are options that include college courses and college-like courses that do not lead to a degree, such as job training schools.  There's also nothing (that I can see, as I've never attempted it) stopping one from taking college courses that would normally be part of a degree program, while not being enrolled in a degree program.

In every case I've seen, this term referred to coursework that was part of a degree curriculum, whether or not that was earned. I suspect this is because organizations can simply specify the degree itself if they need the latter distinction. However, without the actual context it's difficult to be certain.


text:
Converting a degree program to a non degree one
Is it possible to convert a degree program into a non degree program?
For example if someone has started a degree program and is not able to complete it, or decided not to complete it, can he/she convert it into a non degree program?
I know different university may have different rules regarding this but does anyone has any experience or information abut this?

Non-degree programs are usually reserved for people who already have a bachelor's degree but want to pay a university to take some courses without planning to claim a degree at the end. Sometimes people do this out of sheer interest, but in other cases they might be seeking to bolster their transcript before seeking graduate admission in a subject very different from their bachelor's degree.
As such, simply stopping taking courses is a fine way to unofficially convert a degree into a non-degree program. If you don't finish, you don't get the degree. At that point, the only difference I can think of surrounds what happens when you have taken too many credit hours but still haven't graduated. Many universities have some thresholds in place after which incentives start to push students towards graduation. That might be more expensive tuition or hard caps on the number of hours they can take without graduating. Given all this, I don't think many universities would allow a student to convert their degree program into a non-degree program.


text:
How do I cite ebooks without page numbers?
I am directly quoting a sentence from an ebook. Thus, I want to add the page numbering to its citation. However, different to the print version, which I do not have, this ebook (Amazon Kindle version) does not have page numberings but rather "positions".
Do I just pretend it's a page numbering and note in the bibliography that it is a Kindle version? Or is there another way?
In case this is of interest, I am using Latex with Bibtex.

I just want to add that I sympathize with your question. It bugs me that a lot of online books and other online resources don't provide any guidelines for how to cite specific information in them. Therefore I always try to obtain a printed version.

You are not providing page numbers with citations for their own sake, but to help readers to locate the cited passage, e.g., if they want to verify it or see it in context. (Therefore page numbers are already diminished in their usefulness for regular books as soon as there are two editions with significantly different paging.)
The arguably easiest way to locate a verbatim quote in an e-book is to just feed a few words into a full-text search. Thus giving page numbers or similar information has no purpose anymore. However, you could ease finding the location of the quote in a classical book by giving edition-independent location information, such as chapter and section numbers.
Note that this is a “utilitaristic” approach to citations. A relevant reader of your publication (e.g., a supervisor or reviewer) might have a “dogmatic” view on such things and thus require page numbers or similar for their own sake.

This is why you always include the edition in citing a paper book, if it is >1. Chapter and section numbers will often also not be edition-independent. And unless you cite something verbatim, a full text search will not necessarily find the spot in an ebook that your citation refers to.

Sure, but the usefulness of page numbers is still diminished (and I claimed nothing more) as even libraries often do not have all editions of a book available. 2) True, but if the target of a non-verbatim cite is so small that chapter numbers etc. do not provide sufficiently accurate location information, neither would page numbers or similar, at least in most cases.

Since your quote is direct, I would not bother myself so much about it. Just cite the book and give a note that it's an e-book. You can add a chapter or section number if it exists. Anyways, it's a direct quote: people should trust you that it is there. And if they needed, then can use full-text search if they needed.
However, it is necessary to provide as precise version information of the file as possible!

In my opinion, in this case, it may be a good idea to cite your reference regarding the section and part from which you are directly quoting a sentence. I mean, you may cite the ebook the same as you used to do before, but, when you want the reader to be informed about the exact part in which your quotation exists; you may refer to the section and part instead of page numbers which do not exist. Another good idea may be mentioning the phrase: "PDF file position: Page ???" in the same place of citation in which the page number is mentioned and the reader will easily find the part of the reference.


text:
How to properly credit other people when writing a text book?
In many textbooks, authors usually write about other people's research results without the type of detailed and extensive citations typically seen in a research paper.
Often times without any credit to the original researchers/authors.
In fact, the type of "neutral" tone used when authors talk about recent research areas makes it seems as if those areas have existed for hundreds of years.

For example, consider the sentence, "Xtacking is a type of 3D NAND with higher bit density and faster time-to-market." Xtacking was invented in 2018, and no authors
  is attributed.

I think this is more or less an accepted convention. And I understanding that having an excessive amount of citations will hinder readability.
However, I wonder what is the most acceptable way to credit the original authors when talking about results in a textbook context.

I have seen textbooks with references in footnotes, or at the end of each chapter or in a references section at the end of the book...

Generally speaking, textbooks have the same responsibility to cite their sources as any other type of scholarly work. The one reasonable exception I can think of is a textbook about a very old and established subject like calculus, linear algebra etc. It is already sufficiently well-documented who deserves credit for these old ideas.
One slight difference in how the responsibility for citing sources is interpreted for textbooks as opposed to research publications is that the ideas in a textbook are not by default assumed to be the author’s. Thus, if an author fails to cite their sources, their readers will probably assume that this is due to sloppiness or laziness on the author’s part, may be annoyed by it or in an extreme case might even consider it a mildly unethical thing to do, but will likely not regard it as a form of plagiarism, unless the author phrased their words in an obviously misleading way to create the impression that the idea they are writing about is their own.
In other words, not giving detailed sources in a textbook is definitely bad practice, but may not get you into the same kind of trouble as it would in other contexts.
As for how to include the citations, it’s true that including them in the body of the text (especially if you also want to add a discussion with more details about the contributions of different authors) can be tedious. One common method, which I used in my book and I have seen used in many other places, is to add endnotes at the end of each chapter or at the end of the book.


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Patented algorithm: what authors are allowed to do?
I work for an industrial research lab, which requires everybody to file 2 patents a year to achieve 100% in annual performance evaluation. Once the patent is filed, the algorithm in the patent is allowed (and is encouraged) to be published in a conference.
When I started, I signed a document saying all my inventions belong to the company. When I leave the current company, what I can do and cannot do with the patents I filed.

If the algorithm in the patent is not published in a conference, can I publish it as (i) an independent researcher or (ii) an employee of another company?
If the algorithm in the patent is published in a conference, can I build an (open source) tool from scratch to implement it? can I implement it for another company?

Part 2 is a completely legal question and not an academic one.

Yeah, this site isn't the place to get advice on what is or isn't legal. Can you revise your question to ask only things that can be answered by academics who are not patent attorneys?  E.g. about publishing ethics.

A good rule of thumb regarding patent law: It doesn’t matter what the law says, what matters is whether someone will come after you. Many patent suits are baseless, but it’s easier to settle than to fight.

A patent is a monopoly on the invention, to sell or derive new products to sell. If the company owns the patent then they have the monopoly; the fact that you invented it doesn't grant you special rights to do anything. You can use it in academic research or something perhaps, as long as you never make any money from it.

If the algorithm in the patent is not published in a conference, can I publish it as (i) an independent researcher or (ii) an employee of another company?

You most likely signed a non-disclosure agreement which will prohibit you from publishing any work product. You can ask your employer to sign a waiver permitting publication.

If the algorithm in the patent is published in a conference, can I build an (open source) tool from scratch to implement it? can I implement it for another company?

A goal of the patent system is to share knowledge in exchange for an exclusive right to exploit the invention for a limited period. It is country specific as to whether private or non-commercial use is excluded. WIPO's Exceptions and Limitations to Patent Rights: Private and/or Non Commercial Use (SCP/20/3) provides a useful starting point.

Requiring "2 patents a year" is dumb, it encourages quantity over quality.


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How do you know if university is right for you?
At the secondary school I went there was an implicit sense that all students were expected to go to university. For example councillors would come into our English classes to give presentations on how to make smooth transition to a university. I guess I always had the assumption that a university degree is necessary to a) make a living and b) make a living doing something you enjoy. Now that I'm a little older and a little more experienced I know this is not always the case. There are plenty of people (especially in business) who did not complete a university program. How do you decide if university is right for you? Is the correct approach to decide on the job you want and then, if university is required, get the degree for it?

You go there and find out.

@BenBitdiddle I don't think that's a very practical method. There are many universities and many programs offered by each university. If you don't like the current program you're in that doesn't necessarily mean university is not right for you. Conversely there are too many options to just try out. Also the cost (and time investment) could be prohibitive.

What do you want to do with your life? University is one way of getting to some of the answers. Trade school or apprenticing is another, if you think that's closer to what you want to spend your life doing.
It's also legitimate to say you don't know yet -- in which case you need to decide whether starting classes would help you decide what interests you, or if doing something else for a year makes more sense.
I knew what I wanted to study (or thought I did; turns out I was close but not on the mark), but even so I decided to take a year off before college; I needed a bit of maturation time, and to switch from being the youngest in the class to being one of the older kids, for my own comfort. Spent the year doing volunteer work in a hospital (electronic repair, "biomedical engineering"), which was certainly educational in the general sense, helped build my self confidence, and may actually have helped my college application stand out from others.
"... There are nine and sixty ways / of constructing tribal lays, / And every single one of them is right!" -- Kipling

There are plenty of people (especially in business) who did not complete a university program.

Make no mistake, university is still required for the vast majority of jobs at the vast majority of employers. There are certainly plenty of outliers, but they are a small percentage of professionals.

Is the correct approach to decide on the job you want and then, if university is required, get the degree for it?

No. University isn't job training, it's education. An education provides you with the tools necessary to be a better person. A better employee for sure, but also a better entrepreneur, a better wife/husband, a better father/mother, a better solider, a better scientist... whatever.
The degree itself will open all sorts of professional doors, but it's the education that is valuable. The only reason to not get one is if you think you can get a better education doing something else. All things being equal though, attending an institution specializing in educating you is most likely to actually provide you with a worthwhile education.

Unlike in the USA, in many countries university doesn't provide general education.  That's something people get in school before they're 18.  When they apply for university, they choose a full programme, e.g. architecture, and study precisely that (not all sorts of general things then wonder about choosing a "major" a couple of years in).  With an architecture degree you won't be able to become a German translator.  And without an architecture degree you won't become an architect.

You certainly sound of the opinion the university is right for everyone.

@Celeritas - it's not, but it's hard to tell ahead of time. It's certainly the safe choice for everyone.


text:
Should I copyright my notes?
I generate detailed notes throughout the school year to help out the students. Most of these notes are in the range of 30 - 50 pages.
I wonder if I should attempt to copyright my notes to ensure that it is not copied without attributing me as the creator.
If so, how can I go about doing this to the maximum effectiveness? As for now, all I am thinking is to place a copyright icon somewhere in the notes.

In countries that follow the Berne convention, which is most of them, your notes are already copyrighted as soon as you write them, and nobody has the right to copy them at all without your permission (with certain exceptions that vary between countries).

@NateEldredge This should probably be an answer.

I think the OP wants effectiveness in discouraging people from plagiarizing the notes, rather than make such plagiarism illegal. If so, the Berne convention is irrelevant. In my experience, the best discouragement is publicly posting the notes online somewhere; this way, if a teacher reuses them without attribution, students will easily find out (and they will notice -- I have seen at least one rant about a professor that mentioned his reuse of other people's notes as evidence for bad teaching here on academia.SE lately).

@darij Grinberg that's another great answer.

@NateEldredge This is true, but if the infringement is in the US, that automatic copyright is pretty much worthless. Per 17 USC 411, you generally have to register copyright before you can go to court to enforce it.

You should absolutely place your notes explicitly under an open source license if you want to let students, colleagues, and other interested parties know that they are free to e.g. redistribute, edit, improve, etc. They will always have to credit you as the original author, but they will also be able to offer them a second life when you stopped caring about them or lost the original source :-) https://creativecommons.org/ licenses are generally a good choice for this type of usage.

Two misconceptions here:

I need to "copyright" my intellectual property to protect it. - No. Unless you explicitly indicate otherwise, you already automatically get exclusive copyright to your notes. There is no "copyrighting" process like applying for a patent. The common "Copyright 2018" notice serves as a reminder of this, as well as suggesting a relevant entity to contact about getting permission and to pre-empt any arguments in court that "well it didn't say it was copyrighted". The last point is superfluous, since court would not require the copyright notice either way.
Holding exclusive copyright physically prevents people from copying my intellectual property. - No. While unauthorized copying is illegal, the copyright is not a magic incantation. You still have to find unauthorized copiers, ask them to stop, then sue if they refuse.

So your copyright is only as good as the steps you're willing to take to enforce it. Will you spend your free time trying to track down people who copy your notes? Will you pay a lawyer to send letters to everyone who copies the notes without permission? Will you shell out hundreds or thousands in legal fees to sue when they refuse?
I'm guessing you're just hoping a scary sounding warning will discourage people. In this day and age, I doubt many would be discouraged. At best you could contact their institution (if they have one) and put pressure on them that way. But ultimately, what are you trying to protect here? A few students passing around copied notes? So what?
If you're thinking somebody will take the notes and use them to write a textbook and sell it for money, forget it. If they're planning to do that they can easily change your notes slightly and even if you had a case, you would have to waste horrendous amounts of time and money in court. If your notes are so great that they have non-trivial financial value on their own, just publish them yourself. Otherwise, stop worrying and move on with your life.

Your point #1 is technically true, but it needs a major qualifier. Under US law, although copyright is established automatically at creation, it's generally unenforceable unless you have paid to register that copyright with the US Copyright Office. Without registration, your copyright is pretty much worthless against US-based infringement. Cite: 17 USC S411: https://www.law.cornell.edu/uscode/text/17/411

From your post, it appears that you want to discourage people from plagiarizing the notes (i.e., copying them and passing them as their own), rather than make such plagiarism illegal (which, as @NateEldredge has observed in his comment, may already be the case if you do nothing). If so, the Berne convention is irrelevant. In my experience, the best discouragement is publicly posting the notes online somewhere; this way, if a teacher reuses them without attribution, students will easily find out (and they will notice -- I have seen at least one rant about a professor that mentioned his reuse of other people's notes as evidence for bad teaching here on academia.SE lately).
If you want to ensure that people can legally copy your notes with attribution but not without, then a good option is the CC BY license (or any other CC license more restrictive than that -- but I'd go with CC BY if this is your only issue).
[Comment extended to answer.]


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How do mathematicians conduct research?
I am curious as to how mathematicians conduct research. I hope some of you can help me solve this little mystery.
To me, mathematics is a branch where you either get it or you don't. If you see the solution, then you've solved the problem, otherwise you will have to tackle it bit by bit. Exactly how this is done is elusive to me.
Unlike physicists, chemists, engineers or even sociologists, I can't see where a mathematician (other than statisticians) gather their data from. Also, unlike the other professions mentioned above, it is not apparent that mathematicians perform any experiments.
Additionally, a huge amount of work has already been laid down by other mathematicians, I wonder if there is a lot of "copy and pasting" as we see in software engineering (think of using other people's code)
So my question is, where do mathematicians get their research topics from and how do they go about conducting research? What is considered acceptable progress in mathematics?

I like the question just fine, but: you do realize that mathematics as an academic field is not uniquely characterized by a lack of data and experiments, right?  In other words, you correctly point out that theoretical mathematics is not a science.  There are other non-sciences too...

@Pete some might disagree with you on the science thing: "Mathematics is the queen of the sciences and number theory is the queen of mathematics" (you're in number theory, right? :))

ff524: The NSF disagrees with me on the science thing, sometimes to the extent of putting money in my pocket.  Nevertheless I think that everyone agrees that there is a sense in which (traditional, theoretical) mathematics is not a science: deductive versus inductive reasoning and all that.  My point is that the OP seems to express wonderment about an academic field which lies largely outside of the scientific method.  I agree and say: more amazing still, there are multiple fields like that.

I have the opposite problem: I don't understand how you can call collecting some numbers from nowhere and deducing some non-sense from them without giving proper evidence (proof) as conducting research :D

Legend has it that mathematics research consists of the following iterations coffee -> think -> coffee -> theorem -> coffee -> paper. Rinse and repeat. There may be more coffee steps involved but the general idea boils down to this (pun intended).

@ff524 -- I consider math to be part of philosophy. It's essentially a specialized form of reductionism.

@ff524: The oxford dictionary has the following definition for science: "The intellectual and practical activity encompassing the systematic study of the structure and behaviour of the physical and natural world through observation and experiment". I've never heard of anyone applying the scientific method to math problems either.

You can find a video clip on YouTube of two characters from the show "The Big Bang Theory" acting like they are "doing research", set to the song "Eye of the Tiger". The characters are playing physicists, but the clip is frighteningly accurate for what much mathematical research looks like.

@OswaldVeblen: Well, they're theoretical physicists :-)

@PeteL.Clark Yes, Sciences are, by definition, Empirical disciplines, and Theoretical Mathematics are Logical ones. So pure math is not a science, nonetheless, it is almost always organizationally categorized as one, both because 1) traditionally (i.e., before Gauss) it was empirical and thus a science, and 2) the rest of Science's extreme dependence on it and deep integration of it within their disciplines.  Or to put it another way, the application of mathematics is subject to empirical criteria and so can be called scientific, but the theoretical is logic only.

Surely the answer is https://www.youtube.com/watch?v=gXlfXirQF3A.

My old high school professor was provocatively claiming that "maths is an experimental science" (and was actually coming to class wearing a lab coat). Checking the Goldbach conjectureis actually collecting datas that hint the conjecture may be true. If a counter-example to the conjecture were found, it could be considered as the "black swan" of mathematics!

@MarcClaesen “A mathematician is a machine for turning coffee into theorems.”  Who said that again?

@xebtl I guess you've already found the answer, so I'm mainly commenting for the benefit of others: It was said by Alfréd Rényi, though the quote has often been ascribed to Paul Erdős.

As far as pure mathematics, you are quite right: there are neither data nor experiments.
Drastically oversimplified, a mathematics research project goes like this:

Develop, or select from the existing literature, a mathematical statement ("conjecture") that you think will be of interest to other mathematicians, and whose truth or falsity is not known.  (For example, "There are infinitely many pairs of prime numbers that differ by 2.")  This is your problem.
Construct a mathematical proof (or disproof) of this statement.  See below.   This is the solution of the problem.
Write a paper explaining your proof, and submit it to a journal.  Peer reviewers will decide whether your problem is interesting and whether your solution is logically correct.  If so, it can be published, and the conjecture is now a theorem.

The following discussion will make much more sense to anyone who has tried to write mathematical proofs at any level, but I'll try an analogy.  A mathematical proof is often described as a chain of logical deductions, starting from something that is known (or generally agreed) to be true, and ending with the statement you are trying to prove.  Each link must be a logical consequence of the one before it.
For a very simple problem, a proof might have only one link: in that case one can often see the solution immediately.  This would normally not be interesting enough to publish on its own, though mathematics papers typically contain several such results ("lemmas") used as intermediate steps on the way to something more interesting.
So one is left to, as you say, "tackle it bit by bit".  You construct the chain a link at a time.  Maybe you start at the beginning (something that is already known to be true) and try to build toward the statement you want to prove.  Maybe you go the other way: from the desired statement, work backward toward something that is known.  Maybe you try to build free-standing lengths of chain in the middle and hope that you will later manage to link them together.  You need a certain amount of experience and intuition to guess which direction you should direct your chain to eventually get it where it needs to go.  There are generally lots of false starts and dead ends before you complete the chain. (If, indeed, you ever do.  Maybe you just get completely stuck, abandon the project, and find a new one to work on.  I suspect this happens to the vast majority of mathematics research projects that are ever started.)
Of course, you want to take advantage of work already done by other people: using their theorems to justify steps in your proof.  In an abstract sense, you are taking their chain and splicing it into your own.  But in mathematics, as in software design, copy-and-paste is a poor methodology for code reuse.  You don't repeat their proof; you just cite their paper and use their theorem.  In the software analogy, you link your program against their library.
You might also find a published theorem that doesn't prove exactly the piece you need, but whose proof can be adapted.  So this sometimes turns into the equivalent of copying and pasting someone else's code (giving them due credit, of course) but changing a few lines where needed.  More often the changes are more extensive and your version ends up looking like a reimplementation from scratch, which now supports the necessary extra features.
"Acceptable progress" is quite subjective and usually based on how interesting or useful your theorem is, compared to the existing body of knowledge.  In some cases, a theorem that looks like a very slight improvement on something previously known can be a huge breakthrough.  In other cases, a theorem could have all sorts of new results, but maybe they are not useful for proving further theorems that anyone finds interesting, and so nobody cares.
Now, through this whole process, here is what an outside observer actually sees you doing:

Search for books and papers.
Read them.
Stare into space for a while.
Scribble inscrutable symbols on a chalkboard.  (The symbols themselves are usually meaningful to other mathematicians, but at any given moment, the context in which they make sense may exist only in your head.)
Scribble similar inscrutable symbols on paper.
Use LaTeX to produce beautifully-typeset inscrutable symbols interspersed with incomprehensible technical terms, connected by lots of "therefore"s and "hence"s.
Loop until done.
Submit said beautifully-typeset gibberish to a journal.
Apply for funding.
Attend a conference, where you speak unintelligibly about your gibberish, and listen to others do the same about theirs.
Loop until emeritus, or perhaps until dead (in the sense of Erdős).

What's interesting is that sometimes in the course of proving something, you might invent an entirely new kind of mathematics, which in turn winds up being useful for other purposes.  This is very loosely analogous to inventing new programming languages for the purpose of more efficiently expressing your intention and hence developing things more quickly.  Many of the names of our everyday mathematical abstractions come from the names of the living, breathing people who spent their lives constructing and refining them.

In my own experience, it's not that common to begin with a specific problem. More often, I begin with a feeling that something I've read or heard about could be done more elegantly or more clearly. My initial goal is then just to understand better what someone else has done, but if I can really achieve a better understanding, then that often suggests improvements or generalizations of that work. Indeed, it sometimes makes such improvements obvious. If the improvement is big enough, it can constitute a paper; if not, it can sometimes become part of a paper, or of a talk.

Rather than starting with a conjecture (although I sometimes do that), I more often start with an idea: some specific thing that I'd like to understand. This is based on my intuition about what problems seem likely to have interesting results. As I work through the thing I am studying, I come up with specific conjectures and theorems. But the beginning of the project rarely has specific conjectures, just goals.

You forgot "meet with a colleague, stare at a blackboard together and argue passionately on which definition looks the most beautiful". Pretty accurate nevertheless.

Nate, pardon the dumb questions, but does this apply for undergraduate (pure) mathematical research as well? What about for master's?

@Jack: The goal of pure mathematics research at any level is as I described: to be able to prove or disprove statements whose truth or falsity was not previously known.  At the undergraduate level, it often begins with computations (by hand or computer) to try to evaluate whether a conjecture is plausible, and sometimes it doesn't get any further than that.  There will also be a lot more interaction with an advisor.

@Jack: I'm not sure what to say about master's programs. Around here most master's programs are based on coursework and/or expository theses, and don't have original research as a requirement.

Nate, actually that's kind of what I was wondering. If a PhD is original research and bachelor's and master's are not, does that mean bachelor and master level mathematicians don't prove? I mean when you prove something no one else has proven before it sounds like original research...? What do you mean by expository thesis? Sounds interesting

Actually, even in pure mathematics, it very often is possible to do experiments of a sort.
It's very common to come up with a hypothesis that seems plausible but you're not sure if it's true or not. If it's true, proving that is probably quite a lot of work; if it's false, proving that could be quite a lot of work, too. But, if it's true, trying to prove that it's false is a huge amount of work! Before you invest a lot of effort into trying to prove the wrong direction, it's good to gain some intuition about the situation and whether the statement seems more likely to be true or to be false.  Computers can be very useful for this kind of thing: you can generate lots of examples and see if they satisfy your hypothesis. If they do, you might try to prove your hypothesis is true; if they don't, you might try to refine your hypothesis by adding more conditions to it.
See also Oswald Veblen's answer which talks about doing similar "experiments" by hand.

I "do experiments" by working out conjectures in the context of specific examples. If the conjecture works out in several examples, that makes me more confident that it may be true in general.

Unlike physicists, chemists, engineers or even sociologists, I can't see where a mathematician (other than statisticians) gather their data from. Also, unlike the other professions mentioned above, it is not apparent that mathematicians perform any experiments.

I "gather data" and perform experiments" by working out my conjectures in the context of specific examples. If the conjecture works out in several examples, that makes me more confident that it may be true in general.
For example, suppose that I think that every topological space of a certain form has a particular property. I will start by looking at some "simple" spaces, like the real line, and see if they have the property. If they do, I may look at some more complicated space. Often, when I look at what specific attributes of the examples were necessary to show they had the property in question, it tells me what hypotheses I need to add to make my conjecture into a theorem.
This is not the same as scientific experimentation, nor the same as computer experimentation, which is also important in various areas of mathematics. But it is its own form of experimentation, nevertheless.

I think this is an important answer (especially in light of my comments above).  From a philosophy of science standpoint, one must be clear that theoretical mathematics does not follow the scientific method.  However, an important part of what mathematicians do in practice bears a lot of similarity to scientific experimentation.  As a result, mathematical research has a similar flavor to scientific research in many respects.  (There are other academic fields in which one really doesn't do experiments in any sense: philosophy, literature, law...)

One point to note is that, for some questions, it is possible to do experiments to get data. Certain questions are things we now have computer programs to generate, and previously they could have been done on a far more limited scale by hand. So in some cases mathematicians do work more like experimental scientists. On the other hand, once they've found what seems to be a pattern, they change approach. Gathering further examples isn't much use (unless you then find a counter-example, but it can be encouraging) - you need to find an actual proof.
More generally, nearly every big result will come from some 'experiments': you try special cases, cases with more hypotheses, extreme cases that might result in failures...
On the 'copy-and-paste' point, mathematicians do use a lot of what other people have done (generally they must), but whereas you might copy someone's code to use it, when you cite a theorem you don't need to copy out the proof. So in terms of written space in a paper, the 'copied' section is very small. There are (fairly large) exceptions to this: fairly often a proof someone has given is very close to what you need, but not quite good enough, because you want to use it for something different to what they did. So you may end up writing out something very similar, but with your own subtle tweaks. I guess you could see this as like adjusting someone else's machine (we call things machines too, but here I mean a physical one). The difference is that generally in order to do this sort of thing you must completely understand what the machine does. Another big reason for 'copying' is that you may need (for actual theoretical reasons or for expositional ones) to build on the actual workings of the machine, not just on the output it gives.
More to the point of the question:
As a mathematician, you generally read, and aim to understand, what other people have done. That gives you a bank of tools you can use - results (which you may or may or may not be completely able to prove yourself), and methods that have worked in the past. You build up an idea of things that tend to work, and how to adapt things slightly to work in similar situations. You do a fair amount of trial and error - you try something, but realise you get stuck at some point. Then you try and understand why you are stuck, and if there's a way round. You try proving the opposite to what you want, and see where you get stuck (or don't!).
Once you have a working proof, you see whether there are closely related things you can/can't prove. What happens if you remove/change a hypothesis? Also, does the reverse statement hold? If not entirely, are there some cases in which it does? Can you give examples to show your result is as good as possible? Can you combine it with other things you know about?
Another source of questions is what other people are interested in. Sometimes you know how to do something they want doing, but you didn't think of it until they asked.
One more point I'd like to make in the 'methods of proof category' is that, for me at least, there's a degree to which I work by 'feel'. You know those puzzles where all the pieces seem to be jammed in place but you're meant to take them apart (and put them back together again)? You sort of play around until you feel a bit that's looser than the rest, right? Sometimes proofs are a bit like that. When you understand something well, you can 'feel' where things are wedged tight and where they are looser.
Sometimes you also hope that lightning (inspiration) will strike. Occasionally it does.
(All of this may not exactly answer the question, but hopefully it gives some insight.)

"whereas you might copy someone's code to use it, when you cite a theorem you don't need to copy out the proof" - and when you call someone else's function, you don't need to copy the source. If you're copying the source, that's a bad sign.

@user2357112 or a sign that they don't provide a library, just an integrated implementation; or that the full library has too many requirements, or does not compile on your system. Seriously, in academic code you can usually find truly horrific things, and just copying the body of a function is one of the least abhorrent things.


text:
How to find exercise problems as a graduate student?
I took my first graduate course as an undergrad last semester and it seemed that graduate student exams are much more open ended. Not only do they require you actually know more stuff (i.e. remember the theorem, the general approach) but they also require a lot more creativity, time management and general problem solving smarts.
But flipping open a text at the graduate level (Birkhauser, Springer-Verlag type), not only are most books filled with theorems, lemmas, proofs etc from head to toe, covering a very large array of concepts, but the much needed exercise at the end of the chapter is replaced with a list of references. Where are the exercises? And the course I took was sort of commonly taught I believe - stochastic networks.
I can see how this can be very problematic as one climb up the academic ladder. How would you ever find a text on "lower dimensional topology of autonomous robotic system", "Brain chaos in semi-aquatic faunas" or "Renal-sarcomere interaction theory" (three completely made up course).
How should graduate students approach a subject or an emerging field where there exercises scarce aside from what is introduced during the lecture or in existing literature?

First, let me reassure you that many graduate classes are similar to undergraduate classes, in that often there will be regular homeworks and plenty of exercises in the books, with undergrad style exams, just harder.  Of course, not all of them are like this--some are more like what you might think of as seminars, but this is sometimes true for undergrad classes as well.  It depends on both the level and the focus of the course.
As for how you find exercises, learning how to ask your own questions and find your own (typically terribly naive) understanding of a subject is a large part of becoming a researcher.  In graduate school, you should have an advisor who can help direct you with things and may suggest exercises or warm-up problems for you.
To give more a practical answer:

If a subject is fairly well studied, you should look for other books which may have exercises.
If there are no exercises, you can make your own by trying to come
up with your own proof, or working out things in special cases, such
as computing examples.
If it is a more recent area or specialized topic, where there are no
great texts, sometimes there may be good online notes from a course
or summer school someone has given.
Lastly, I think a great way to learn a topic is to start writing
your own notes on it, and this works well for advanced/specialized topics where exercises are hard to come by.  Trying to explain something to someone (even
yourself or a vague nonexistent reader) forces you to ask yourself
basic questions about the topic, which helps you understand both the
ideas involved and larger context.

By the way, here's a related question you may be interested in:  http://academia.stackexchange.com/q/40487/19607

The purpose of an exercise is to have you start applying the material to a problem, which helps you learn it.
As a graduate student, you're going to have started working on applications of your own.  If you want to start applying the material you are learning, why not try applying it to work that you are engaged with?  You will be in a less-constrained environment and without clearly provided answers, but, well, that's practically the definition of the difference between undergraduate and graduate education...


text:
Which of the items below are worth mentioning in my admission documents?
I really worried about what should I write in my admission documents, such as resume/CV, statement of purpose, informal email communications with professors. From the list below, please tell me what items have enough academic value to be mentioned in such documents?
Note that its a application in PhD program in computer science for US universities

Stack Overflow (generally Stack Exchange) reputation and badges
Coursera accomplished courses
Small-scaled programming projects (absolutely with no academic value)
Github programming repositories

This list does reflect your technical abilities and not your research-based activities.
Therefore, all things listed here should be packaged and be presented under a section
(e.g., such as 'Related Technical Activities'); to represent your technical abilities to program and contribute (e.g., Github).

It would also be useful to highlight these as evidence that you are able to collaborate, to keep up with the latest trends in technology and software development, and that you have good skills in tutoring (Stack Overflow).


text:
Is my work a good research work?
I am a master student in computer science and am working on a static program analysis project as my thesis. I used existing platforms and frameworks along with existing approaches for static analysis of a program.
However my work would solve a problem in the area I am working in. In better words, for Android OS there is not yet a good work on static analysis of native binaries. This is what I am working on.
I think my work is not a good research work, because my work is all about implementation and dealing with existing tools. As far as I know, a good research work should not engage itself in implementation complexities and should be as abstract as it can be with a great degree of novelty.
In my opinion my work is novel, but it is not an abstract solution as it is mostly about technological stuff. So, I am in doubt if I am thinking right or not.
PS: By "good research work", I mean it can be published as a good research paper.

Does it solve a novel problem or offer a novel solution to a known problem?

@CaptainEmacs It's a known problem, but there isn't a good solution yet.

And yours is? Then you have your answer.

Reading Hammings 'you and your research' might be good at your stage. (or any stage actually)

Good scientific research is anything that increases the knowledge of humanity.  Sometimes that involves creation of new things, sometimes that involves putting together existing things in a way that creates a new capability.
What you have described might or might not be scientific research, depending on the particulars of the work.

If there is an interesting reason why Android static analysis hasn't been done yet (e.g., something incompatible between Android's organization and typical static analysis approaches), then explaining that reason and how you overcame it can be the core of a good scientific paper.
If, on the other hand, it's just technical drudge work (e.g., like rewriting an application from C to Java), then even if it is difficult and valuable it will not be particularly scientifically interesting.

Even if the application itself turns out not to be scientifically interesting, however, what you learn once you start applying static analysis to Android programs might well be...

In my opinion, academic research work should be focused more on learning in general and learning how to perform research correctly in particular, rather than on doing grandiose, novel or even "the right" research. This is especially applicable to the Master's level research, where implementation-focused work and theses are very popular (obviously, it is quite field-dependent, but here I imply the software engineering / computer science areas of research).
I don't see any reasons for why an good implementation-focused research work could not be published as a research paper in a solid journal. In fact, I have seen a lot of such papers (of varied quality), especially in the above-mentioned domains, published in respected peer-reviewed outlets.