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How do really talented people in academia think about people who are less capable than them?
To be more specific, how do really top professors think about students who are much less smart than them, the students can be their Ph.D. students or just students who were taking his/her class.
This is a main problem I am concerned about when I have something I don't understand, and because of this, I am often hesitant to ask my professors or other friends, because I am afraid that they would look down upon me and think I am too stupid/useless/incapable, etc?
Can someone who know this give me some advice to overcome this unhealthy attitude?

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The question asks something different than what it says in the title...

Agreed with @TomášZato - the title is entirely misleading.  The real question here is about dealing with self-confidence issues - what some professors may or may not think about a poorly specified group of "people" has nothing to do with it.

My attempt to edit it was rejected though.

I wouldn't say I'm a 'top' professor - hopefully someday, heh - but here's my take on it.
I couldn't care less how 'smart' my students are or aren't. It's tough to quantify, and different people have different strengths, and it's easy to mistake knowledge/experience for intelligence. At any rate I feel that my job is the opposite of competing with my students in any respect. I want to help them do well in (class/research/etc.) and find it all interesting and rewarding.
I always urge my students to ask me for help if need be, because:

I do try to explain things well and clearly, but I don't always know if it totally gets across
All of my students are different in a gazillion respects, meaning that they're not all going to understand the same things easily
Providing extra assistance is part of my job!

I tell my undergrads that someone who has gotten an A in my class and gotten lots of help from me deserves that A exactly as much as someone who has gotten an A in my class with no help. Everyone is entitled to my assistance, even on a weekly basis or whatever. I don't think poorly of students who request extra assistance. The course is meant to have my students learn a thing or two; if they're a bit confused, I'm more than happy to clarify. The students I worry about the most are the ones who could benefit from extra help - which all of my students are permitted to seek whenever they'd like - but who haven't sought it out!
The only students I actually get at all impatient with are the ones who show indisputable signs of dishonesty or implausible excuse-making or picking on classmates or whatnot. Those ones irritate me. The rest are a joy, whether or not they seek extra help.

I agree with this quite a bit.  For me it's always about effort.  Some students will come from backgrounds where for whatever reason they're more quickly able to grasp the concepts than others.  I've had students understand a subject in fifteen minutes that others don't get by the end of the semester.  But is that quick-study coasting or taking advantage of his gift?  Is the more challenged student rising to the challenge or giving up?  There are a lot of smart, lazy people.  Give me a not-so-smart hard working one any day.

I agree with this also.  It's all about attitude.  I have students who are 'poor 'but very good attitude towards learning, and they turned out to be outstanding.  I have 'smart' students who show no respect for teachers, and those I hate most.  End of the day, if you show a good working attitude, you should be fine.  Top professors are workers, and they like to see a mirror image of themselves.  All birds of feather flock together. Don't be a sloth.

upvoted just after reading first line, but then again, reading through answer, you deserved it ;)

As a relatively senior person at a relatively highly-rated place, and having experienced grad school and post-docs at elite places: in math, at least, the basic point is that we're all inadequate to really penetrate the most serious mysteries. Check. So, by the harshest standard, we all fail. Ok, so that's not such an interesting standard. In grad school at an elite place, it quickly became clear that an absolute novice could not interestingly or usefully "compete with" the decades-more-experienced faculty. Check. But the real point was that asking (inescapably naive) questions of such people was a terrific opportunity, which few people have. If ego were in play, it just diminished acquisition of critical, rare information. Bad.
My subsequent experience and observation: well, sure, people vary. Some people are quick, some are quick-but-shallow, some are slower, etc. Some are more ego-oriented, which I think impairs investigation of serious mathematical things, since, by this year, the low-hanging fruit that anyone cares about has been picked. So what remains is inevitably going to be less-immediately gratifying, etc.
In any case, smartness (or height, or handsomeness, or ...) is not a moral virtue. Plus, having a good head but not applying it, or having various perversely nonconstructive bad attitudes, is less effectual than having more modest brains but being focused and sincere (perhaps less ego-ful).
That is, what gets my respect involves not so much the individual's personal gifts, but how they use those gifts, that is, to advance mathematics in contrast to advancing just themselves. That kind of thing.

Please take conversations to [chat] and keep it polite.

People say stupid stuff all the time, even 'top professors'. I believe that most professors would not judge you for asking a question about something you don't understand. Even if what you ask is silly.
If you feel shy about asking questions during lectures, visit the professor during office hours.
I can tell you from experience that professors usually will not remember what questions you asked, but they will remember that you asked questions. At the very least that shows that you are making an effort and they will probably view you in a more positive light than before.
Another thing to keep in mind:
If you don't ask questions and do poorly in the class, the professor will probably think that you do not care about the class and that is why you did poorly.
If you do poorly despite asking questions, the professor may think that you made an effort, and you deserve a better grade than the guy who didn't care.

A reasonable answer, but, in fact, I do remember what questions people ask. Memories vary. But, more to the point, yes, asking questions is always good. Asking no questions is not so good... unless by chance one magically does understand everything already. Better to ask silly/dumb questions than none, etc.

Here's an anecdote from my own career. I just retired from a small, private, liberal arts school. At my school, most of the students think most of their math profs are geniuses (we're not). A few years back, I had a student who was originally a business major and had taken a business math course from my wife. He had done a fair job in her course and then decided he wanted to be a math major because he enjoyed it so much. He signed up for my calculus course and I figured we'll see how this goes. He took several more courses from me as well. He kept asking questions, silly ones in the beginning, but gradually more insightful. What more could I ask for than to see a student growing mathematically right in front of me? I had significant reservations about his prospects as a math major in the beginning, but I never let on to him. What I wanted to do was encourage him and help him as much as possible. The end result was that he was elected to the math honor society and I cannot tell you how proud I was for him when I got to hand him his membership certificate.
The moral to this story is pretty simple, and has been echoed by others in their answers and comments. I have never looked down on a student who was willing to try, even if they didn't get great marks. The ones who really irritated me were the ones who had discernable talent and didn't use it, or the ones who couldn't care less about the course.
In my experience, I have had but a handful of times when I thought that a professor or colloquiam speaker looked down on someone. After all, our job as professors is to inform our students and develop them, not to put them down.

What does "elected to math honor society" mean?  Top X percent of mathematics students?

@zyx - He was elected to a national honorary mathematics society. The chapter at our school has more stringent requirements than the organization actually specifies.

A friend of mine got some advice from his dad that he passed on to me once.

Don't worry about what other people are thinking of you. Most people are mostly thinking about themselves.

I mean, each of us thinks that life's a movie and we're the star, and internally interprets everyone else's actions as part of the plot of our lives.  But everybody else is doing the same thing.
To be more specific, many professors are introverts and may seem intimidating, but usually they are passionate about their discipline. It may be the one thing they love to talk about.

Academia is as much about self-replication as about research or teaching.  What professors privately value (and devalue) about their students correlates with what traits they value in themselves.
Different professors attained their positions through different relative proportions of ability, work, and other factors.  Hard workers are likelier to want hard-working students, and to expect hard work from their students.  Those who were seen, and see themselves, as having spectacular innate talent are likelier to value evidence of high natural ability in their students.   Some people may have done a cold analysis that tells them it is optimal in their field to prefer people with a different mixture of skills, but more are looking for proteges who resemble their younger selves.
Because selection into academia demands high levels of many traits it is not always obvious how a particular professor sees themselves.  A born superstar may also be a hard worker and value that aspect the most.  But it is not so typical for a lazy genius to prefer hard workers, or vice versa.
The usual qualifiers apply.  On the average / all else being equal / in my opinion and experience / exceptions exist / ...

I think there is one important aspect missing in previous answers: as a professor, your resources are limited (resources meaning mostly time and money).
I don't know about other areas, but in math, independent of whether you are "top" or not, one can sometimes see people who would be actually better off changing their career. And I am not saying this to boast, or out of spite, in fact they may have my deepest respect for who they are (including how hard-working they are). Nevertheless, in (almost?) any kind of a job one needs a certain degree of efficiency. (Please note, that it does include many different aspects, i.a., if you like what you do. If you do not like something and get burned-out completely, then you become terribly inefficient.)
Thus, I would treat even the most stupid relevant question seriously and try to answer to the best of my ability, but I will get annoyed if I see signs of huge inefficiency. The reason is that I have other matters to attend. Situation would be different if I had any free time to spare, but the truth is there is always something else to do.
To give some examples of inefficiencies related to students asking questions:

students coming to ask a question despite the answer being easily available in some other way (say on the web), even without any special vocabulary (which I understand that the students might not know),
students coming with the very same question or making the very same error for the 42nd time,
one group of students asking more questions after getting enough answers to previous questions to get them started and some other group of students waiting with their questions wasting time just sitting in my office and not doing anything else.

Even if I get downvoted into oblivion, I hope it will get you an additional perspective.

Thanks! I am quite afraid that I fall into one of the three categories you listed, though...

People are different. Talented people in academia are people too. Thus follows, some of these may not behave as one would expect, and any general answer like this one won't apply to all of them. Nevertheless here's an answer that focuses on the last sentence of your question:
People judge you when you leave an impression. Whenever you leave a new impression, that judgement changes. If you never open your mouth you will be judged, at best, as one of them many faceless people that are unimportant.
Whenever it doesn't matter if you're judged as unimportant or as stupid, open your mouth, because you've got nothing to lose.
Even better, if things go bad, and as a result people do think you're not as smart as they are, you can use the situation as a learning experience. If you never go through such learning experiences you will indeed not be as experienced/smart as others are.

+1, "People are different" is the correct answer. There is a reason why questions asking for personal anecdotes are usually closed on SE sites - the answers make a very convincing impression, but the impression is rarely an accurate representation of the truth. Sure, as an academic myself, I would love to think that the top people in science are not arrogant jerks, but the truth is that some of them are, while others are not. Answers which try to convince the reader otherwise are misleading.

When I was a student, I will tell you frankly, I did not generally divide up my professors, instructors, TAs, and fellow students, into the "top brains", the "medium brains" and the "mediocre brains".  I suppose I had some awareness of that in the background... but mainly I focused on how best to partner with each of them so as to optimize my progress in my studies.  Each instructor is an individual, with strengths and weaknesses as a pedagogue.  This approach is similar to going into a relationship with a medical provider with the attitude that the patient and the provider are going to work together toward a common goal.
Think about how it feels from the instructor's point of view.  It is hard to help a student who doesn't interact with you!
There are more ways to interact with an instructor than just by asking questions.  You can also make a comment, to let the instructor know what was most interesting for you, and what connections you were able to make between what was presented in class, and some other thing you have learned or noticed.
I hope this helps.

The man who asks a question is a fool for a minute, the man who does
  not ask is a fool for life.

-Confucius(?)
Note: I debated removing this answer, but I really believe it strikes at the heart of OP's conundrum.

Your answer is fine except Confucius never said that. Please see the question on Chinese SE. (Actually, I doubt it's a Chinese proverb and I am a native Chinese speaker). I won't down vote this answer because downvoting should be done for bad answers. Your answer is not bad.

Thank you. Quotes are often misattributed! And I browsed your link, but I don't speak/read/write Chinese, so other than debunking the Confucius/Chinese origin I don't know what the correct source is.

I am not saying that I am a smart person. (This is something that my colleagues say, which I know is not actually true in many cases). Anyway, as someone who is presumably on the other side of your argument, I have taught some courses to some students whose IQ levels were seemingly way below my expectations. I hope it is OK to share my personal experiences in here.
To be honest, I felt very uncomfortable at first to see that my students couldn't understand some trivial things and had a lot of trouble with some really easy concepts. One of my regrets is that at first I treated them in a humiliating way. And I often mocked their seemingly stupid questions. You know, I wasn't used to this and didn't know that humiliating others doesn't make you look smarter, but rather an a**hole. It took me some time to somehow get used to this and learn some manners.
Now let me tell you something, the more you learn, the more you realize that knowing something or being fast at learning something does not necessarily make you a better person. And if someone thinks that these talents give him/her the privilege to think high of himself/herself, the best thing you can do is to feel sorry for him/her. In my point of view, teaching to a person with lower IQ who is doing his best and struggling with easy concepts is way more enjoyable than teaching to a presumably smarter one. Note the key is to do your best, regardless of how fast you get things.

Being stupid is not that bad; we were all stupid at some stage, and some of us are still stupid now. The professors were stupid as kids and are likely to get stupid if they survive till 100. That's how things go.
Use them while they are clever and you are stupid. Professors know to never underestimate a student. They are prepared for that. It's their job to teach you and answer your questions regardless how stupid you or your questions are.
Said that, as a student, you can typically only profit from asking. But, to be polite to the society that surrounds you, think over a question a bit harder before asking, simply not to lose the time of your environment.

How long is the professor's career in the field? Decades?
How long is the student's career in the field? Years?
The true top professor (teacher, mentor) knows about this difference and take it to the account. They expect the student to know less than them and assess the student's performance with respect to the expected knowledge rather than their knowledge. Bad professors (teachers) use their (long gathered) knowledge to outclass people with shorter (time to gather the) knowledge.
Some students are slow to connect informations they are given. That does not make them dull. Some students tend to miss or forget some links. That does not make them dull either. True question is whether the student is interested in deeper knowledge of the subject.
If you want to be sure your ideas are true; if you want to know more you must ask.
You may think the question is dull (for the professor). But he may think of the question as "they are asking for A, because they do not know about B and C (are rlative to A) yet." And the response won't be "How do yo dare to ask that", but "That is good question" instead.


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Can a graduate school change its decision, from rejection to acceptance?
I have heard stories that graduate schools revoke their offers because of various reasons, such as lying in the application and some other serious misconducts.
As the title suggests, can the opposite happen? And can you recall any such events? If you have, why did they happen?

Don’t think the universities will publish figures for this, or even keep a record.

The typical process that happens in graduate application selection is that you subdivide applicants into three groups:

Accepted applications: These are your first choice of candidates, and you offer them a position. This list need not be ranked.
Waitlist: These are the applications you think are good enough to accept, but not so good that you want to make them an offer right away. You rank this list, and go top to bottom as people who have previously been offered a position decline.
Reject: These are the applications you think aren't good enough to succeed in the program. There is no need to rank these candidates because you don't anticipate ever tapping into this pool.

The point I'm trying to make is that the rejected applications are candidates you don't think are good enough to succeed in the program. You're probably going to ask what happens if everyone declines and you're out of names on your waitlist? Well, then you just don't make any more offers. That's because you've previously decided that the ones on the "Reject" list aren't good enough to succeed.
The only thing that's worse than not being able to fill all graduate student slots is to fill these slots with students who you believe will not succeed in the program. That's a sunk cost: you're paying for people who aren't good enough to do the job they're paid for.
So, under the assumption that all universities work on such a system (which I think is, in essence, the case), there is no reason ever to turn a rejection into an acceptance.
(Now, has it ever happened? Almost certainly, given just the sheer number of cases. Does it happen on a regular basis? No.)

In an ideal world, this would be the case, but there might be pressure, administrative or otherwise to fill all slots, even if this means taking people from the rejected list. After all with funding, it's often spend it or lose it. In particular unfilled slots in one year might prompt whoever is doing the budget to give you fewer in the next. But I agree, normally, the waitlist should be long enough to avoid such situations.

@mlk Trust me, departments have other ways of spending money that's left over :-)

Most probably this is institution specific and if it happens, an extremely small number of this type of events occur. The main reasoning behind such a U-turn is that an applicant who accepted or was sent an offer, did not take it within a certain time. But even in this case, most graduate schools work with waiting lists and are likely to use them to send a second batch of offers.
Thus, technically possible, it is very unlikely that someone will have a rejection turned later into an offer. The only scenario I could think of is that someone came second in the application process and the school has unexpectedly received another grant allowing more students, but then would be a matter of the group wanting to run a second application process or just use a previous list of applicants.

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Should I change a graduate class grade to pass/fail? Will it harm my PHD applications?
I am an MS student in machine learning just finished my first semester at a U.S. university, and I plan to apply to PhD programs in computer science in electrical engineering or operations research for next year (also for machine learning and optimization).
I took three STEM advanced graduate courses this semester (two EE, one math course), did well on the engineering courses but only got a B on the math course (measure theory) because of a bad final. Even though B is not exactly a disastrous grade, but it is not good at our school because the graduate courses are heavily curved. My school offers an option this year to get a special Pass/Fail grade, where they will mention something like "pass/fail because of the global pandemic". This past semester was indeed hard for me as I was living in a different time zone because of travel restrictions and the classes usually took place at 1-3 a.m.
I am still thinking whether I should use this option. On one hand, I have heard multiple times that graduate schools frown upon P/F grades, but on the other hand, this course is not directly related to my research area (may be useful one day, though). I would appreciate any advice!

Grades matter when applying to graduate programs...until they do not. For the most part, a B is never a disqualifier for getting into a PhD program. (Getting a C or D...or F might be more worrisome). As long as you have a 3.8 or higher in your masters program, I usually would not even dig too far into the specifics of your grades if I was reviewing your submission.
When I evaluate graduate student applications, I place much more weight on letters of recommendation and personal statements. Especially where the measure theory class is not a core topic in your field, getting a B should not matter too much. Get strong LORs and write a good personal statement and you should be fine. You even could mention the challenges of COVID in your statement. (Although, I honestly would not even bring up the B. Least said, soonest mended).
I would not recommend changing the grade to a Pass; this looks like you actually are trying to hide something. Move on from the B and focus on building a good resume of experience and connections.

Especially if the course is not relevant to your research area, leave it.  Even then, a B in a graduate course isn't all that bad.  As you noted, many schools will understand that some people may have faced difficulties over the past year because of the pandemic as you have mentioned.  Just focus on getting more research experience, since that will be better, both for PhD admission and in your long term career.

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How to get rid of the awkwardness and feeling of inferiority for being a fairly old graduate/PHD student?
I am a first year MS student in an STEM area. For many reasons I didn't enter this subject area and didn't gain ANY research experience until last summer, when I was 26 (now 27). So starting next fall in 2023 I'll likely be a PHD student either in my current school or some other school.
So I'll be 28 when I start my PHD, and if nothing goes wrong, I will get my PHD between the age of 32 and 34... From what I know, this age will not bring me any disadvantage in the job market, either in academia or industry in most of the western countries (not 100% sure, please correct me if this is wrong).
I believe my depression from this mainly comes from the psychological factor: I feel I am inferior compared to younger people in my program who started their PHD at a younger age; even worse, this is my second MS and I didn't even have any significant work experience in industry, so I don't have that excuse either. For a few years, this has often caused me severe psychological trauma and many times an urge to cry, especially when I socialize with those kids and we (casually) talk about age. This isn't right, but I do care about others' opinions, sometimes to an extreme level, and I constantly fear being regarded as inferior or incompetent by my school mates. I also fear that I'll never be as successful as people who started PHD young (I know there are many counter-examples on this, but I don't have that confidence on myself).
Weird enough, in my group there is a student who is even a few years older than me, and seems to be comfortable. I don't have any prejudice against him at all and we are good friends. But when the same thing happens on me, I just can't get through it.
For people with similar experience, how would you get rid of it? Any help or insight is appreciated.

You need to speak to a mental health professional about this.

Over the years, it dawned on me that my perception of what other people think of me is usually flawed, close to 100% of the time.  Our mind goes to the extreme; i.e., worst case scenario, but in actual fact, it's far from the truth.  So remind yourself when your thinking becomes negative.  It also helps to socialize more.  In academia, many times, we are alone thinking about our research and live in a bubble thinking about the 'outside' world.

What did you do in the intervening years? That is, what did you do in the time when you were as young as the other students and now?

It takes a 27 year-old to think that starting a PhD at 28 constitutes being old; best for us not to give an answer to a question with such a ridiculous premise.

I recommend reading this inspiring article published in Nature entitled "Why I got a PhD at age 61" (https://www.nature.com/articles/d41586-022-00949-z). It may help you realize that you are still young with decades of exciting opportunities ahead of you.

I'm in the exact same situation as you, same age. Although I don't fear so much of what others will think of me, I am mostly just frustrated that I am past my cognitive prime (20-25). In the last few years, I've noticed my brain becoming slower and my memory failing more and more. So I can't help but feel like I have wasted my potential to a certain extent.


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How can I help to participate in data collection or research work as a field researcher?
To clarify my question, due to length limitations in question part.
For PHD, Researcher allowed to take part as research subject for data collection/analysis? How to include personal accounts of/experiences of a research phenomenon? Thoughts/decision making processes when playing a specific game on world class level?
This then mean a specific game where there are limited /very few really have mastered the game and subjects are not easily contactable. Also potential research participants are a handful 5 to 12.
To explain. If a researcher want to ask how tennis players think his accessibility to the top 20 of the world tennis players are really only 20 and not just anyone around the corner that wannabee play tennis.

Sorry but your question is not clear: do you mean that you are yourself a professional sport player, and you are also doing a PhD specifically on top players in this sport? Please edit the question to clarify. In general scientific principles strongly discourage an author of a study also taking part in the study themselves as a subject.

Yes, I myself are a gaming esport player, and myself also want to do a PhD specifically on top players in this esport game.

The first step before starting a PhD would be to find a potential supervisor who has some expertise in the research domain (not necessarily the specific topic). First there will be some discussion with this supervisor about the exact research topic and the motivations for the research: a PhD student's expertise in a particular topic is not enough to justify research on this topic, there must be some scientific reasons why this topic is a relevant research area.
Then you will see with your supervisor about the best method(s) to achieve these research goals. Imho it's unlikely that a supervisor would agree with a method which involves you as a subject, but I'm not at all in this kind of domain. In any case your expertise would certainly be useful in contacting subjects and targeting the right research questions.

Thanks for your answers. Much appreciated. I will then take the stance always be non-bias and that personal bias or experimenter bias are only kept on interpretation on qualitative design. The topic I want to research is is new and not been researched before.


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Writing "thank you" note to professor who will write more LOR's?
I have been working with a professor for research for over a year and will continue to for at least another year.
The professor has written several letters of recommendation for me in the past, and has agreed to submit more in the coming years.
Should I write a "thank you" note for the past letters, even though I still work with this professor regularly and will likely ask for more letters in the future?

I am still a student and do not know if one "should" write a note or not. But I write to them or thank them personally as a matter of courtesy, just like I thank anyone who helps me. Like I said before I do not know if it's a norm but I consider it a nice gesture without any harm (I guess!).

If you are worried that sending such a letter would be something of a bribe for the future letters, you can rest easy. No one is likely to think that. But there may be a lot of reasons to thank professors, including what they contribute to your education.
But in the case that someone writes you a letter and you get an award or offer partly as a result, then you should definitely thank them.


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Is it harder for academics to make fundamental discoveries than in the past?
In present day academia, it seems much harder to make foundational breakthroughs than it was in the past. Most work now synthesizes previously discovered results to study something extremely specific. Although this extremely specific thing may be valuable to know, it generally does not have the potential to rewrite the field.
For example, in physics, the beginning of the 20th century saw the revolutionary development of general relativity and quantum mechanics. While there is still much to be learned in modern physics research, it is much more difficult for someone to make large, fundamental contributions to the field, simply based on the fact that the large, fundamental contributions were already made. Now, even an extremely productive researcher may only become well-known in their immediate subfield. Similar notions can be applied to art and a variety of other academic disciplines, in which it is more difficult for one single artist's work to be foundational to the field.
Do academics worry much about the growing insignificance (for lack of a better word) of their work? Or is any knowledge gained worth the effort, simply because the academic enjoys studying the topic (no matter how esoteric)? Any sort of discussion about this concept would be enlightening.

One might suggest that there are only so many 'fundamental discoveries' or 'foundational breakthroughs' out there. You just pay attention to them, and don't notice all the other work going on around them at the time. But, I don't see really how this question can be answered here.

How do you know that the 'large, fundamental contributions' in physics are all already made? A lot of people in the second half of the 19th century believed that physics was mostly done and didn't have much of a future as a research discipline. Today we can't properly mesh quantum physics and general relativity and we don't understand situations where both are relevant.

Problems that remain unsolved in contemporary physics include (1) the nature of dark matter, (2) the nature of dark energy, and (3) quantum theory of gravity. The solution of any of these is, I think, likely to be a foundational breakthrough or at least lead directly to a foundational breakthrough. A problem may look specialized (e.g., black body radiation spectrum, or the Michelson-Morley experiment) until its solution turns out to rewrite the foundations of physics.

@quarague exactly.  the true masters make the impossible seem trivial.  if I have seen farther, it is because I have stood on the shoulders of giants.  I got good grades in my calculus classes and I mastered the material well.  This in no way implies I could have discovered calculus had I been born several centuries earlier.

Actually, exactly the same question might have been asked around 1900 when Henri Poincaré ruled the world.
There is a tradeoff, of course. Some fields get saturated and the seemingly important questions get answered, closing the field in some ways. But those fundamental breakthroughs may open new lines of inquiry. And there is the corresponding effect that other fields open up. Mathematics is like the latter. People today think about a lot of mathematical ideas that didn't really exist historically.
Whether physics is a fixed field in which everything will eventually be known is, I think, an open and debatable question. I suspect that there will be new ways of thinking about things and thus new and important questions as long as humans can manage to still exist. Quantum entanglement is still pretty "spooky".
And in the social sciences we may be only at the beginning of what can be known.
Moreover, each new generation of scientists, in whatever field, starts out at a higher level than their predecessors, and so, have a base on which to reach still higher, with a deeper understanding. Poincaré had problems grokking relativity, as did many of those in his generation. After they started to actually die, relativity came to the fore.

+1 -- Even if some fields are decidedly "solved", there will never be an end to science itself.

Your answer resonates with a recent find in our university library:  «Breakthroughs in Statistics» edited by Samuel Kotz and Norman L. Johnson.  In the second volume, Gosset's / Student's contribution to statistics by his $t$-test is presented by Lehman including the statement «The importance of Student's new approach was not immediately realized by his contemporaries. Not too much blame should be attached to them for this lack of perspicuity since Student himself does not seem to have been
aware of the significance of his contribution.» (doi 10.1007/978-1-4612-4380-9_3, p. 30)

Do academics worry much about the growing insignificance (for lack of a better word) of their work?
This looks like a personal question, so I'll give a personal answer. I have no idea how widely my opinion is shared, so don't attach too much "statistical significance" to it. IMHO, most of us (myself included) have never had any chance to make any "major breakthrough" in anything by ourselves. Such breakthroughs can occasionally be made out of the blue (at least, in mathematics) but more often than not they just occur when the time is ripe meaning that the relevant tools and ideas get slowly developed to solve lesser problems, many of which will be later just forgotten. So, I view my task as merely trying to figure out things that haven't been figured out yet in the hope that in the process I'll find some new approach or, at least, a new twist of an old technique that will come handy later when some people smarter than I will solve some "big problems". The nice thing (again, I can confidently say it about mathematics  only, but it may apply to other sciences as well) is that our knowledge is (at least currently) resembling not a solid disk like in that famous  depiction of PhD, but rather the Sierpinski carpet, so you can make a small side step from any position and find yourself on an uncharted territory where life immediately gets interesting enough to render all your existing knowledge if not totally irrelevant, then, at least, rather hard to use. Moreover, you don't need to search hard for those side steps.
is any knowledge gained worth the effort I would say yes, but not
simply because the academic enjoys studying the topic.
To start with, enjoyment is a rare event. The normal state is somewhere between slight frustration and deep depression and the main feeling is that of being totally inept and stupid. Normally with any problem worth being called by that name you start as "a blind kitten in a dark alley" going by touch, bumping your head against everything, and backtracking from dead ends at every turn. Slowly you may start seeing some light and distinguish some shapes (the more alien they look, the more interesting). Finally, if you are lucky (more often than not that event never comes), your eyes suddenly open fully and you see the surroundings and your way through. Then you have your few minutes of "enjoyment".
The value of any piece of knowledge comes primarily from the fact that the connections between problems, their relative significance, etc. are totally unclear until everything is done (by which time one writes short end elegant textbook expositions for students using about 1% of the work that went into obtaining a theorem). You cannot possibly predict what effect the solution of any particular "small problem" will have "on the big scale" as long as that solution is not achieved by totally routine means that have been available before. Usually you are just collecting sand grains that will be later mixed with water and cement powder to make blocks that later will be put together to form walls of magnificent buildings that together will form the city we call "scientific knowledge". Thinking of great cities, one rarely thinks even of cement blocks, let alone the sand particles (though some individual buildings may still come to mind and, on rare occasions, even the architect's names, but not the names of more numerous masons that did the work). The same with mathematics. The collectors of sand particles get always forgotten and the sand itself just becomes "common building material" available in abundance, but it is an endless process of sand collecting that makes the higher level building possible in principle. So, I'm personally quite content with being a "sand collector".
One may argue endlessly about whether there exists a qualitative difference between the process of obtaining a mathematical equivalent of a sand grain and that of building a grand theory. I would just say that a good theory builder works at higher level than a bad sand collector and a good sand collector works at higher level than a bad theory builder and stop at that (like a good CEO is worth more than a bad janitor but a good janitor is worth more than a bad CEO).
As to "most large contributions have already been made", I doubt it very much (though, by the very nature of the question, I am unable to come with explicit examples of the large contributions to be made within the next 50 years). The life is abundant with crazy twists and so is science. One just plays the game and sees how much he can score, leaving the erection of various "Halls of Fame" to future generations. Let me ask you one question however: you mention "general relativity" and "quantum mechanics". How well do you know either one? (I should confess that I'm almost a total ignoramus). If not really well, then those "major contributions" haven't happened in your life yet (though you can benefit from them indirectly), so it may be a good idea to scale down a bit and see how many relatively major things happened recently in the domain you have good knowledge about (say, within the particular area of research you work on) and then project the number upward making (perhaps, unwarranted) assumption that you just don't see the whole large picture but it is not dissimilar to the smaller scale one.

This all tallies pretty well with my own perspective (also from within mathematics).

Agree with this perspective, I think it holds in computer science as well (even the more applied subareas). (+1)

In present day academia, it seems much harder to make foundational breakthroughs than it was in the past. Most work now synthesizes previously discovered results to study something extremely specific. Although this extremely specific thing may be valuable to know, it generally does not have the potential to rewrite the field.

I see at least two factors at play in explaining this phenomenon, and the upshot may not be as cynical as it seems.
1. It only seems harder, due to survivor bias
Comparing academics today to Einstein is not a fair comparison due to survivor bias. Einstein was not the only physicist working in his day. For every Einstein there were at least hundreds of other people who tried to work on physics but failed to invent general relativity. For every Archimedes and Euclid there were at least dozens of other mathematicians who failed to make a name for themself reaching into the present day. In fact, it is impossible to even tell how many there were, as most have been lost to history: they will not have a Wikipedia page, or any mention on the internet, etc.
In other words, you are comparing the average academic of today with the most successful academics of the past, so you are not comparing apples to apples.
If we were to compare the average academic today and in the past, would we see a difference in how difficult it is to make foundational breakthrough? I expect that there would still be some effect, but it would not be nearly as pronounced.
2. Scientific progress inherently involves specialization
Looking back on foundational results like Einstein's theory of relativity (or Turing's definition of a computer, or Mendeleev's discovery of the periodic table), we get the feeling that a "breakthrough" is something like a huge paradigm shift, where everything we knew before was wrong, and now some new theory is found to be correct instead. But as science progresses, paradigm shifts may become less and less common, because we see that many prior breakthroughs turned out to be correct, so we must build on them rather than replace them. And the way that this happens is that subfields develop which build on the previous (now thought to be correct) theories in different ways, and/or explore the limits where those theories do not apply.
But is it accurate to say that these "specialized" results as less "foundational"? When Turing invented the definition of computer, he was a mathematician, not a computer scientist: at that time, you could say that computer science was just a small subset of math. But it later grew into its own field (and separated from engineering as well, a century later). So today, "computer science" is its own field, along with "physics", "chemistry", "biology", etc.
In summary, the possibility for foundational results within a field is independent of time; it is just that the set of fields changes. For example, today, rather than making foundational results in physics as a whole, you might try to make foundational results in quantum mechanics or in fluid dynamics.

I'm unsure about aspect 1. I think the comparison is not between an average scientist of today and Einstein, but about the best scientist of today and Einstein, the point being that not any such revolutionary discoveries as general relativity are made today.

@lighthousekeeper True, but I was responding especially to this part: Most work now synthesizes previously discovered results to study something extremely specific. That is talking about most work, not the best work. If the question is about the best work today and in the past, then the answer would be different. And I think it is easy to compare the present and past incorrectly, failing to account for survivor bias.

@lighthousekeeper The thing is, it's hard to tell today whether any of the best scientists of the current decades will go down in history as Einsteins. I suspect some will - there is still much we have to learn in many fields.

@6005 I agree, your response to that particular part is valid. Possibly the question would be more interesting without that part.

@xLeitix There is much to to learn indeed, but do you see anything that has the potential to entirely change the way we see the world, like Einstein did? I'm pessimistic, but would be excited to be proven wrong.

@lighthousekeeper Public key crypto was only invented in 1976. In computer science that's as foundational as relativity. I think we see similarly foundational results at least a few times a decade (although I can't tell whether the pace is slowing down or speeding up!)

@lighthousekeeper I honestly don't know (and I would distrust anybody who claims to know).

@6005 Now that you say it, I suspect if quantum computing becomes a real thing it will change computer science comparably to how relativity changed physics.

The problem is not that there are no fundamental problems to solve. The problem is seeing the obvious big problem just at your feet while you are checking the horizon.
This happens more often than one would think. Perhaps not in the magnitude of the great two theories of QM and relativity, but there are quite amazing surprises lurking all around us. Just to give an example, in game-playing AI, the rediscovery (for the second time) of deep feed-forward networks and their combination with Monte Carlo Tree Search cracked a problem that was considered open for another 30 years (winning against the human Go champion).
Yes, this was a numbers' game, but with the old techniques, even with all number crunching power available, we probably would still be far off.
Information theory is a big one. After its discovery by Shannon, confined for a long time to the computation of point-to-point data transmission and a bit of glorified correlation measure, has now become an incredibly powerful Swiss army knife for all kinds of analyses and AI algorithms with major subbranches emerging every few years.
Or remember Quantum Computing, with its complete rethinking of what computation means.
Or the Quantum Decoherence framework which does away with the ad hoc Kopenhagen Interpretation axiom of measurement and embeds the latter organically as part of QM proper which leads to (experimentally verifiable) models for the dynamics of measurement in QM. This is particularly remarkable, because essentially for a long time any attempt to "understand" measurement properly in the QM framework was bluntly dismissed by the mainstream community with reference to Kopenhagen. This may have held back our theoretical understanding by decades. Zurek and his colleagues, however, understood that here is an important phenomenon to characterise here, and while the relevant mathematics is not particularly difficult in principle, and matches effectively what Kopenhagen had to postulate as axiom, they needed to attack the belief that what seemed obvious most certainly wasn't.
In short (I do not know who to attribute this saying to): "The fish is the last to discover water." - The water is there, but recognising it is the actual challenge.


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Is it allowed to write notes during the "read instructions" stage of a TOEFL exam?
Is it allowed to take notes during the "read instructions" stage of TOEFL? At this stage the timer is stopped and it's a good time to take notes such as drawing tables for speaking and writing sections. But I'm not sure on whether it is allowed in the exam. I'm asking this question because I didn't find any section of the TOEFL rules that addresses this scenario.

I don't think anyone's written about it because it's not cheating and accepted as a valid strategy, otherwise someone would've written about it. You're gonna get reports like "I tried it and it worked", or "I tried it and I got written up"? ... If you get none of the latter, that's good.

I watched the test procedure video. At about 2:47 the paper was described as "scratch paper for your use during timed sections of the test". To me, that suggests you are not allowed to write on it outside the timed sections. You should be able to ask during check-in.

Afaik the sections are sequential so you don’t get all the material in one go.
Then the reading time is reading time not writing time.
And I have run these exams in the past following their detailed instructions for each section.

The 'read instruction' section is before the actual test. It will tell you how the actual test is structured and what you are and aren't allowed to do. It is also available online and doesn't depend on the particular instance of the test you get. So if you do a mock exam in preparation, this mock exam will have the exact same 'read instruction' section as the real test. You can and should familiarize yourself with the general structure of the test before taking it but I don't see what kind of notes you would want to take during this section of the actual TOEFL.


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Is it possible to get perfect score in TOEFL's Speaking Question Type 1 (Personal preference) without using examples?
The ideal way to approach Question Type 1 (Personal preference) type questions is to state your preference/opinion along with 2 reasons and examples to support each of them. Personally, I find it a bit too tedious to come up with 2 examples to support 2 reasons. I can only manage to think of the reasons. I'm planning to skip the examples and elaborate on the 2 reasons instead. Will doing this refrain me from getting a perfect score in Question Type1?
Alternatively, I can manage to come up with only 1 reason with a strong example to support it. Is this better than my previous approach i.e using 2 reasons with no examples?

I'm not sure about the relevancy of TOEFL prep questions on the Academia Stack Exchange (you're probably better off using a forum like this one) but to answer your question: The official guide to the TOEFL published by ETS states:

This question will always ask you both to describe something (for example, an  important event, a favorite activity, an influential person) and to give reasons-to  explain why the event was important, why the activity is one of your favorites,  how the person influenced you, and so on. Be sure to respond to all parts of the  question. Your response should include specific details and/or examples because they will make your description informative and your reasons comprehensible.

If you think you can make your description informative and your reasons clear without concrete examples, do so. In my opinion, it is better to stick the official guide's recommendation. However, it does not specify any specific number of reasons and examples. I got a full score and I only gave one reason but elaborated on it with a specific example and a detailed argument.


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Question about the authorship of mathematical equation
Recently, I felt thrilled because I was finally (after few months of non-stop work) able to mathematically prove the mathematical (physical) transformation which I use to prove some new laws of physics. Everything adds up so nicely using this transformation and everything seems logical. To much of my disappointment, I have learned that in 1950's two papers are written where exactly the same mathematical transformation appears. However, in neither of these two papers this mathematical transformation was not proven and it was only guessed from physical laws. Probably because of this lack of proof, both papers were forgotten, otherwise I suppose these papers would be breakthrough papers. These two researchers were not only researchers trying to find the correct form of this transform and in last century there is at least dozen of papers trying to find this transform (although not explicitly stated).  Now, I've been able to mathematically prove this transform and I am writing the paper about some new physical laws emerging from this transform. My question is should I mention these papers at all? Since no one before (without fake modesty) was able to prove it and the rest of the papers were on this track (but not explicitly stated) I was thinking about not mentioning these papers at all. Otherwise I would have to explain what these researchers did and its rather irrelevant for my paper (sole discussion about this would represent another paper). What do you people think about this? I would like to hear your opinions, and of course, the constructive criticism from you

Yes you should reference them.  You can say they conjectured the same transformation formula.

So, you think it would be wise to write the paragraph or two about the history of transform? The problem is that one of these 1950's authors states that this transform is correct without the shred of mathematical proof and this physicist, although deceased was very influential at the time. One of his peer's, after his death in 2000's stated that his research was breakthrough but it was never accepted as such (probably because of lack of proof). So I would rather skip discussion about this and simply present the derivation of this transform. However, I am not sure this is the best approach

You should decide how much you want to say about their work based on how much it would contribute to the narrative you want to tell.  A single sentence could be perfectly fine.  That said, don't belittle their works (just be factual: they did not provide proofs) and don't speculate (e.g. on the reason why it didn't revolutionalize the field).

As a general rule: When in doubt, cite it.

gallileo skipping that is not proper to the earlier researcher.  It's also not INTERESTING because you are leaving part of the history out.  If, while presenting the history, you can give yourself a little credit (after all it was kind of a lost idea that you rediscovered), I would do that.  [Do it subtley though.]

You have an opportunity to validate another scientists hard work and contributions, and you don't want to? You would want future generations to treat your work better than that.

@gallieo1985 So you think it is wise to not mention that  you found prove for a formular that a very influential physicist could only conjecture? Think about the bragging rights you earn :). To be honest this might even make your breakthrough greater because you did something other people were not able to, so give them a heads up. In comparison: Everybody talks about things that Einstein conjectured/foretold and that are just proven today.

Sincere thanks for answers, I've included proper references to previous work. The root of my doubt came from the fact that I didn't want to accuse prominent physicist of that time that he didn't do the proof nor the derivation of the transform. Although I know this transformation is correct as he wrote it I've expanded it a bit and proven it. I've simply mentioned that the transform appears in somewhat simple form in paper X and Y without the proof . Thanks to all for advice

If something has appeared, pretty much in any form, you need to cite it. If you don't you will always be open to a charge of plagiarism.
I'll note that the proof is more important, in the grand scheme of mathematics, than the statement of it, so you don't lose anything by citing past work.
Authorship is different from "ownership". You can't own mathematics, but you can copyright your own expression of it (or anything, basically).
But if you don't cite it and someone later asks "why didn't he/she know about this" then it is a negative for you. Always cite your predecessors. Celebrate their work as well as your own advances.
Some of the intervening work has now been put on a firmer ground by your work, but that will only be obvious if you make the connection.

Thank you very much for your elaborate answer, I will be writing about the history of this equation. You helped resolving my dilemma;)

You have to cite it.  If you can (gracefully) mention that you found the effect before seeing the papers, this would be nice to yourself.  I'm not sure exactly how, but I would give it some shot:  "After deriving this theoretical result, we became aware of earlier experimental work that made these conjectures but did not prove the effects or develop the implications."  Be careful about being too personal, but I would be motivated to give yourself some credit.

@guest, what you suggest might be appropriate in a memoir, but not in a scientific/mathematical paper. Don't try to make it about you. The result and its proof stands on its own. Your proof is all the credit that you need.

That;s why I said you had to be sly.  Subtle it up a little more, maybe.

@guest, sorry. No. Do mathematics. Leave it at that. There is no reason to make yourself look foolish in a math paper.

I think you may still be able to get away with something.  For instance in the context of the introduction where you discuss the motivation and evolution of the study. (Especially if you publish in a science journal, not the holiest of math journals).

@guest, please stop digging. "get away with something"???? Why don't you think mathematics itself is enough. Primp and preen??? Please.

Let us continue this discussion in chat.


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Question about mentioning gap year in SOP
I took a gap year after my high school. It technically wasn't a gap year since I reappeared for my 12th grade(senior year) examination to increase my score. In 12th grade, I scored 62% in 2012 and then I improved it to 79% in 2013. The main reason I went for the gap year was to explore more about the 2 engineering fields I was confused about going into (CS and aeronautical engineering). During the gap year, I explored both the fields and decided to go with CS. Now, I've graduated. I'm applying to schools in the US for masters. Should I mention about the gap year in my SOP? If yes, what reason should I mention? Are universities very serious about this stuff?

In the intervening years did you earn a bachelor's degree?

Yes I did. I earned a bachelors degree in CS. The gap year was before undergrad

First, make your SoP forward looking, not backward. Only bring up past actions to support the idea that you are an excellent candidate who is well prepared and motivated and has excellent prospects for success. Your CV explains you past. Your SoP is for the future.
But I see no need to mention anywhere that you have a gap. Your transcripts and record will probably indicate something like that, so it isn't a question of deceit or hiding anything. It is (a) just too long ago to be very relevant and (b) too easily explained if anyone should ask about it.
Your record is what it is and you can't change it. Your future is your own to choose. Put the emphasis in the SoP on forward looking things and why they are achievable. Don't, in particular, apologize for anything in an SoP.
And, finally, I doubt most would notice the gap and fewer would care. Especially if you had some reasons - even a year in the South of France.

Thanks a lot! Yeah I have good academics and internship experience. The only bad thing was the gap year. Thanks. I appreciate it!


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PhD CV with not experience in academia job
after many years of working on telecommunications for various companies, I decided to change my career to Linguistics, and language technology. to do this I graduated from BA in Modern Languages and did a MA in Linguistics.  Just few weeks ago I saw and advert for a paid linguistics PhD position in The Netherlands. I have never contemplated the idea of pursuing a PhD, but the research project is very attractive to me.
So, I am working on my CV, however I don’t have papers published nor academia working experience.  and the only research I have undertaken was during my MA – assignments and dissertation.
I wonder if you can advise, how I can overcome the lack of academia -research experience in my CV?
Many thanks!
Sarita


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Is it possible for an applicant to be disadvantaged by negative comments sent via emails without his/her consent?
I saw some reports about how corrupt teaching staff in some colleges in some countries forces their students to comply with their unreasonable demands (e.g. to conceal a huge flaw in the teacher's research, or to stop speaking their own native language) by threatening to write negative emails and letters to disadvantaged their students' job or academic application.
Of course, such teaching staff will, hopefully, eventually get punished. (Note that we cannot always find evidence of their unethical behaviour, so some get away with it.) But even if they are punished, there is probably no means to stop them from making negative comments directly to the admission office or even one or two professors/employers who make the final decision.
What should students do to protect their own rights? Is it likely that some real damage will be caused by such malicious emails?
Some may complain that I should not ask this because it is not happening on myself - but the situation I describe is NOT hypothetical, and it might happen on anyone, so it is helpful to know how to tackle the situation.

This is a supper difficult problem and is responsible for much of what is wrong with academia.
Its definitely not unheard of for a recruiting academic to call contacts at institutions a candidate has been associated with and ask.
If you are in Europe, and you are turned down for a job you were sure you were the best candidate for, you can issue a GDPR demand to the universities in question, and they must turn over any materials that contain information about you. This should include both formal and informal references. Obviously if the bad-mouthing happened over the phone, there will be no record of it, which is exactly why people often use the phone for this sort of thing.
You could then try claiming that the university treated you unfairly in the hiring process. You'd have to be careful because the university could try saying "We didn't select this candidate for other reasons, nothing to do with the reference. Here is the documentation that lists the criteria we used and the candidate's scores".
You could also try suing the phantom referee for libel/defamation if you were really into long drawn out legal battles.

Depending on the contents such emails can of course cause serious damage. For example I once heard of an email sent between graduate schools that went "we've confirmed that so-and-so applicant fabricated his test scores and his recommendation letter is actually written by his wife". Needless to say that was the kiss of death.
You are asking about a different kind of email, which will depend on different things:

Is the person writing the email reputable? If not (s)he's much more likely to be ignored - he's after all acting out of the norm.
If so, what can (s)he truthfully say?
Do those things actually matter? E.g. if the complaint is that the applicant starts work at 6am and leaves at 4pm, many departments are not likely to care.

How to stop this is a much easier question - just don't tell the person where you're applying to. They can't write to everyone.

You cannot assume they tell truth - they are corrupt as hell.

@ipyudfrh then they're not reputable and nobody would believe them, no?

What should students do to protect their own rights?

Don't study at corrupt universities.
Don't tell corrupt people that you are applying for a job or degree program.

Is it likely that some real damage will be caused by such malicious emails?

Somebody sending an email like that might send it to the wrong person, but if they send it to the right recipient it probably will cause serious damage.  At that point, nothing can be done to fix the problem.
What you should not do is contact employers and tell them that someone might spread lies about you.  That makes you look paranoid or guilty.

"What you should not do is contact employers and tell them that someone might spread lies about you. That makes you look paranoid or guilty." They should better know that countries out there can be super corrupt as hell. Wouldn't make things horrifically worse to experiment with such a policy for a while.

Its got nothing to do with countries or universities.... These things happen in all countries and at the "best" universities. If someone is reading you application and see you were in the same dept as a friend, an academic might well pick up the phone and ask if you were known. Unfortunately, there isn't much you can do about this.


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Applying for graduate school with uncertain GPA
I'm currently applying for Ph.D programs (applications are due in mid December, my semester ends in early December, and I am applying for the Fall semester) and I am asked to list my GPA. I currently have a 4.0 GPA, but that might change in between the end of my semester and the due date for applications. My question is, should I list my GPA as 4.0 on my applications and let the school know if this changes? Should I list it as a 4.0 and not let them know, even if I end up with a B or two this semester (this feels unethical to me)? Should I just wait to submit my application after I've gotten my grades for this semester? I would like to avoid doing anything unethical or dishonest that would involve the admissions committee believing I have a GPA that I no longer have, as I understand they might not even look at my application until next year, and at that point, I may not even have the GPA that I said I had.

Submit your current GPA. Don't do anything else unless required by the school.
No one thinks you're going to know your final GPA now. Schools wants your current GPA to get an idea of what sort of student you are and will make their decision based upon that.
That said, a school may require future transcripts to ensure you haven't bombed all your classes and that you've actually graduated. Any acceptance you get will be dependent upon you graduating. Some schools might also only accept you pending your final grades. As long as your GPA doesn't drop too much (or you don't have a good excuse if it does), you're in the clear.
If you're still concerned you should contact the schools' admission departments, tell them you're still awaiting your semester grades and ask them if your current GPA is fine.

This kind of overlap happens all the time. The usual approach would be to write something along the lines of "GPA 4.0 (last term pending)".

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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Turning a Master's Dissertation into a Journal Article
I'm supposed to turn my masters dissertation into a journal article. The journal has no problem with me doing so as long as my work has not been published before, which it hasn't. However, I was wondering whether using word for word from my dissertation would be considered self-plagiarism? and I was hoping for tips on useful links to websites which can explain how to turn my dissertation into an article?
I'm still fresh in the world of academia, so I really have no clue.

Congratulations, that's really cool! Most likely, the journal has a specific audience that you might want to rework or rewrite your thesis work a bit for, on top of wanting to avoid self-plagiarism. There may also be guidelines and style choices that you need to adhere to, for example with regard to manuscript length. Those can usually be found under "Author guidelines" on the journal's website.

As long as your thesis hasn't been published (and in some cases even when it has) you still hold copyright. To avoid self plagiarism what you need to do is cite the thesis, even if generally: "Much of the following is taken verbatim from my thesis...(title, university...)". That makes the origin clear and permits (in theory) a reader to find the original.
I doubt that in a case like this you need to use quotes or paraphrase the earlier work as you have made the origin clear. Rules against self plagiarism (as opposed to the general case) are there to permit backward searches of context, which is only one part of general plagiarism. The key parts of my doctoral thesis were published (by TransAMS) like that.
In theory, but depending on the publisher, it might be possible to just submit the thesis as is for publication.

"Much of the following is taken verbatim from my thesis." I disagree with this advice. Dissertations are regularly turned into one or more publications. Those articles are important for an early scholar's career. The statement you're suggesting would strongly diminish the career value of the article. Also, "self-plagiarism" is a legal term. If the dissertation has not been published by someone who owns the copyright, there is no self-plagiarism and hence no need for such a statement.

@Eggy, Sorry, but this comment seems wrong in every respect. You don't seem to understand self-plagiarism.

I deal with self-plagiarism very often in my work as an academic editor. The poster is specifically referring to how a journal would perceive her submitting her dissertation verbatim. This pertains to copyrights, and to the journal's wish to not republish material that's been published elsewhere. Feel free to be more specific about what you think I misunderstand about self-plagiarism.

How long is your master's dissertation? And what is your main goal in publishing it? Are you intending to pursue a career in teaching and research?
If you're planning on a scholarly career and you think that publishing an article would enhance your career, there are some things to keep in mind. A journal article is a step above your dissertation in prestige. Therefore it needs to demonstrate a new level of skill, namely, the ability to select a narrow topic and write about it concisely, in a compelling way that will be interesting to read.
Second, in my opinion, it's better to create something new for your article, rather than rehashing your thesis verbatim. It's just not that impressive to publish what you've already done, which was probably enhanced by your advisors. "Something new" could mean focusing on a particular subtopic, adding new works to the literature review, expanding the content, and so on.
I don't mean that publishing a summary of your whole topic is necessarily bad, but I recommend that you approach this article as a new piece of writing. At the very least, you will need to shorten your dissertation, which involves selecting the main themes you want to cover and the details you want to include, creating new transitional sentences to connect ideas, reducing excess verbiage to achieve the length limit, reducing the number of tables and figures, and so on.
So here are the steps to follow:
(1) Read the journal's author guidelines. Note the word limit, the required sections of the article, the style (APA, CMS, etc.), subheads, spelling (Britsh vs US),and so on.
(2) Review some sample articles in the journal, noting the writing style and how they're laid out.
(3) Select a topic that fits the journal's scope. Write a very clear and concise topic statement for your own use.
(4) Identify the journal's readership so you can gear your writing to their level of background knowledge of your topic.
(5) Most importantly, make an outline for your article. First list the main sections. Those might be, for example, Abstract, Introduction, Background and Literature Review, Methodology, Results, Discussion, Conclusion. These could be very similar to the sections or chapters in your dissertation. Then make a list of five or so main points under each main subhead.
(6) Recheck your topic statement. Is everything in your outline directly related to your topic statement? Does your outline adequately cover all the important aspects of your topic statement?
(7) Learn what should be covered in each section of the article. The introduction is especially important. Try to avoid saying exactly the same thing in the introduction and conclusion. The conclusion might include a summary of the problem and study results, practical applications or utility of your study, limitations of your study, and recommendations for future research.
(8) Write, revise, format, edit.
(9) As you did with your dissertation, make sure all works cited in the text appear in the reference list and vice versa. Make sure all links in the reference list are current.
(10) Write an email for the journal editor. Briefly describe your paper and why it's important that it be published.
Some or much of the above will vary according to your field and the nature of your research. Hopefully all of the above skills are familiar to you from having written your dissertation.


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arXiv CS.AI and CS.CL endorsement
I have been working with a newly created startup as a machine learning researcher. I've been working on two research papers snd they were reviewed by my professor st my university and they told me some issues that I needed to address and the final result is done. However, it has been a major issue as in how to publish these papers in arXiv since I don't know any of my professors who publishes in arXiv. I need an endorser for these papers. Since I'm in a startup environment, there's no other researcher than me.
Thank you in advance

This question is similar to: How to find an arXiv endorser. If you believe it’s different, please edit the question, make it clear how it’s different and/or how the answers on that question are not helpful for your problem.

I agree. There is no question mark in your post. If the question is "How do I find an endorser?", then please see the link. If the question is "will someone here endorse me?", we don't do that. If the question is something else, please [edit] your post to contain a question. (Also, why can't the professor who reviewed your paper endorse you?).


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Presented at IEEE, paper accepted but delayed for a year. No clarity. Need advice on next steps
I have presented my research paper at an IEEE conference. It has also been accepted at that respective IEEE conference but the publishing is being delayed. It has almost been a year but they don't provide any clarifications on the issue and just keep delaying the process. Please help with what actions to be taken. The IEEE conference is ICCST 2023 which was held at Defence Institute of Advanced Technology in Pune.

Have you contacted IEEE yet?

Contact the conference organizers. There is an email address on the website.

According to (https://ieeexplore.ieee.org/xpl/conhome/10474215/proceeding), it seems all/most of the papers have been published and are available on the IEEE xplore database. Is your paper not in the list?


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Master's in Germany for an applicant from India who has two Bachelor's degrees
I have completed a Bachelor's degree in History (Honors) from Delhi University, and I am currently pursuing a second Bachelor's degree in Computer Applications (BCA) from Amity University Online. My BCA program started in 2023 and is expected to finish by 2026.
I am interested in applying for a Master's degree in Germany after completing my BCA. Would having two different Bachelor's degrees (one in History and one in Computer Applications) affect my eligibility or chances of being accepted into a Master's program in Germany? Specifically, I'm curious about how German universities view applicants with diverse academic backgrounds and whether both degrees will be considered during the admission process.
Additionally, are there any specific challenges or advantages I should be aware of when applying for a Master's program in Germany with this academic profile?

Germany is a federal state and universities have additional autonomies. I am looking at the Masters in Informatik of Hamburg University. You need to have a Bachelors in a closely related field with minimum number of courses in computer science and mathematics, that correspond to the curriculum of the bachelor's degree at Hamburg University. If you almost fulfill these requirements, you can get a conditional admission, at least as a German student.
Your application might receive additional scrutiny because your BCA degree is online. Also, this seems to be a three year degree and you might not have enough courses in either Computer Science or in Mathematics, though the B.Sc. in Germany is three years as a rule. I would worry about having enough classes in Mathematics.
You would also have to have prove an excellent command of German.
In general, recognition of a "foreign degree" is a non-trivial procedure.
This is only the result of reading the requirements for one German university. You need to go through a few of them and see where you are. It occurs to me that you might be able to make up a small deficit by taking courses at my alma mater, the FernUniversität Hagen. (You could even get a degree there while staying in India).


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Is there a general guideline to conjure up a mathematical expression to convey a system?
Pardon my naivety. I'm new to academic paper authorship. I would like to understand, is there a general guideline on how to think & express concepts in terms of mathematical expression.
Often times (in my personal intellectual capacity) when I see papers with lot of mathematical constructs I feel intimidated and wonder how the authors have constructed the expression. But when I understand the paper, little bit deeper, I come to know the underlying concept is just common sense which could have expressed with just literature. So I wonder sometimes these Mathematical expressions are sometimes used as an intellectual garnish to uplift the novelty of the paper. Though I'm sold on this practise, I still don't understand how do I make use of it. I did some research on symbol meaning (such as ∑ for aggregation, ∆ for change in value etc), but is there any generic guideline / method that can be used to convert a concrete system / concept to a mathematical expression?

‘Mathematical expressions are sometimes used as an intellectual garnish to uplift the novelty of the paper.’ I’m interested to see a few examples of this. Please share.

You misunderstand the purpose of using such mathematical expressions rather than "just literature". Such expressions are both compact and precise, whereas literature is often at least a bit ambiguous. Words in a given language seldom have an absolutely precise meaning and when used in combination, various interpretations are possible.
That ambiguity (potential) is the reason that there is no reliable automatic system for converting ordinary language into mathematical symbols and expressions. For things that have existed for a long time it may be possible to do something with, say, an LLM, but not for newly created ideas. Language can give an "idea" of what is going on, and provide metaphors for understanding, but precision is required for the accurate transmission of ideas; hence equations and such.
What is needed is experience and insight, which is gained from long practice and deep thinking. You seem to admit this yourself when you write of deeper understanding. Once you have the concept precisely internalized, it seems natural and the language can follow as long as peers accept the "translation".

The craft of converting vaguer qualitative notions into precise ones is precisely the history of modern science. We can assume that quite certainly smarter members of society, especially in "leisurly" positions of priests and astronomers might have had a pretty good understanding of what was going on in the skies (there is famously a cave painting about 30,000 years old, possibly predating organized statehood, showing the phases of the moon), but making it precise requires language.
So, calendars were probably the first step to achieve that, and as tools were refined (think Euclid's geometry), suddenly new insights were possible. And that continued with Archimedes, Galilei, Newton and so on.
In short: science is the craft of giving precision to vague or unexpressed insights into the nature of the world. Maybe AI will make that easier, but for now that should give you an impression for the magnitude of the problem you are talking about.


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Can I use "Member, IEEE" as my affiliation for publishing papers?
I work in industry but I would like to publish some papers in arXiv, IEEE etc. The work I do is not related and not affiliated to my employer. At the same time I'm not studying / associated with any university. However I do hold active IEEE membership but I'm not a Senior / Fellow / Life member in IEEE.
With above said, Can I use "Member, IEEE" as my affiliation while publishing academic papers ?

Are you required to provide an affiliation?

The affiliation represents where the work was done. Your work was not done at IEEE, so you should not list it.

@Aruralreader At least on arXiv or any other general IEEE form I see, they make affiliation as a mandatory field. Hence I assume there has to be some form of affiliation to have some credibility for those publishing houses to accept the submission.

@R1NaNo - I see your point. So affiliation strictly means either where the work for performed (i.e where the intellectual property belongs to) or where it was supported by any means. Got it.

When publishing in IEEE journals, the author's IEEE member rank and year of advancement is listed in the bio. That's only for IEEE journals. Other societies may do something similar, again with the author's status within their society.

@ViswaKumar "independent researcher", "private researcher", "private investigator" or you can create a research company and list it. Kumar Research Ltd.

I would if I were reading a preprint somewhere or reviewing a submission see listing an association membership like this as an affiliation as a pretty big red flag. Simply listing no affiliation would be much more normal and less likely to get a negative reaction.

Why is it a red flag?

@AndrewLeach Three reasons. 1) affiliations are generally for institutions where on actually did work at or were supported by. That doesn't apply to an association member, so it is misunderstanding what that normally means.  2) It looks desperate to have some sort of official affiliation. 3) At a meta level, it suggests that one did not have anyone else look at it, since anyone in the field would likely suggest as one of their first things for you to remove it.

Thank you. I think this answers my direct question as to whether am I allowed to use "Member, IEEE" as affiliation. Does that mean that, for all the papers where "Senior Member, IEEE" was listed against the author, they either got support "from" / performed the work "with" IEEE ?

@ViswaKumar, I've never seen that listed, but I would guess so.

@ViswaKumar I don't know if this is universal, but in one submission we made to an IEEE journal the IEEE membership tag for one of the authors (such as "Senior Member, IEEE") was added by the journal copyeditors after we submitted the final manuscript to them. We did not add it ourselves.

authors: Vladimir F Героям слава


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Can an international student email a professor at a foreign university for an internship opportunity?
I was recently ranked 71/+1000 in a national competition (a series of final exams taken to join the country’s big engineering schools) and I am now a mechanical engineering student.
I want to be able to intern abroad. Is it a good idea to email a number of professors whose work and research interest me and ask, or is there no chance?

Are you already a student at the university you want to intern at?

Yes, you can always email and ask. However, internships may be limited based upon specific universities and nationalities as well as other specific poliies.

Voting to leave open, but also down-voting. IMHO this is a legitimate question that is difficult to answer.

Yes, you can email, but, unless they have advertised for interns, expect most of your mails to be ignored. Perhaps you get a polite response saying "not at this time."
Before you mail, you should investigate what they do and how you fit their program. Otherwise, again, ignored or polite "no".
I used to get lots of such requests along with CVs and such where it was obvious they had no idea who I was or what I did. Sent to trash with no reply. That's just the way it is. Blind emails are easy to ignore.
However, one way to, perhaps, find success is if you have a professor who knows you well, make an enquiry on your behalf. It is harder to ignore a mail from a colleague, especially one who is known to them.
Or, examine university departmental websites and faculty web pages looking for opportunities that are advertised. You might find something, but it will take a lot of work to do it.
(I truly love your user name)

Why? You get some bright, motivated young person, recently educated in your field, to work on research ideas you don't have time for. You will probably get a publication out of it, why say 'no'?

@Ivana The problem with blind emails is that it is not obvious whether the person who is emailing is capable of working on research ideas. This is why a recommendation from a professor can help! Or a tailored message that demonstrates familiarity with a specific professors' research. But mass emails have to go straight to trash, because there is simply not enough time to sort through these students. I don't think professors should feel guilty about this; they're devoting as much time to the student as the student devoted to them (none).

@Ivana Managing juniors is a job. You cannot just toss them a "research idea you don’t have time for" and collect a free coauthorship six months later. You have to follow up on their progress, help them when they are stuck, etc. From my experience, even the most self-sufficient interns need 1h/week of supervision on a good week (30-40min weekly meeting + a couple of very short chats here and there); it easily shoots up to 5h/week or more if the intern is stuck on a tricky point or if there is paperwork to sort out. (...)

(...) Also, that is a purely utilitarian perspective of "giving my work drones just enough maintenance that they continue working". I would argue that as a supervisor you have ethical duties beyond that - for instance, you will "waste" time explaining stuff (when you could refer them to Wikipedia or a standard paper), or helping them navigate university admin, or letting them attend seminars (which does not make them more productive in the short run).

You also need to arrange for their visas, and arrange to pay them (unless it's volunteer), finding a source of funds not restricted to citizens.  It's not a small lift, and there are easier pools to target.

@Ivana is also worth pointing out that unpaid internships are illegal in some countries.

Yes it is totally possible, I've secured internships two years in a row like this.
As pointed out before, most of your emails will stay unanswered, but emails are free, and you have nothing to lose.
It helps to do some research about the professors you're contacting though, maybe read a couple of their publications, and explain why you are interested in what they do.

Upvoted, I've secured the internship that I used for my master thesis this way. Be aware you will probably have to pay your own way during your internship. But maybe your university has some program to help you.

On the other hand, consider the faculty getting "free" emails from students from all over with "nothing to [lose]."

As far as I know, both my supervisors were quite happy I contacted them.

Yes you can totally try this! Make sure to write a specific e-mail, that is, know the professor's work and list some topics that you work on, as well as skills/knowledge that you have and will come in helpful. There will always be researchers that do not have time/aren't interested, but you can try to pique their interest that way. I got one of my MSc placements by reading about an open postdoc position in their lab, and asking to do something similar.
In addition, it helps if you can show that you thought this through: show them possible funds (within the EU, Erasmus is the go-to option) that will support you through the visit, and maybe link to information about your study programme and thesis requirements.


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PhD thesis Report has questions from reviewer
I submitted my PhD thesis to a EU university and I already have the review reports of the two reviewers.
They both accepted the thesis for the viva.
One reviewer left a couple of remarks, while the other left some remarks but many questions.
My supervisor told me what I should provide a response letter to both reviewers, addressing all the questions in the case of one reviewer.
-Why do reviewers ask questions on the report and ask for the answers before the viva?
-They both told me that my thesis is very good.
I am able to answer all the questions well, at least in my opinion. Can I still fail the viva?
-People tell that PhD defense is just a formality, however, I am afraid of failing it after so many years of hard work.
Please let me know your experiences on this matter
Thanks in advance,
Best wishes,
King Baboon

Specifiying your country may help you get specific answers. The viva is not just a formality in the UK, for example.

Are you sure that the reviewers are not expecting you to revise your thesis to answer the given questions? Maybe this is the common procedure at their universities.

My experience is the US, not the EU, but, while the "defense" is mostly pretty pro-forma, you still need to give a reasonable answer to any question asked there. In rare cases the candidate failed the defense and failed to get the degree for responding to a question wrongly when they "should have known" the answer.
I think that the written questions are given as a favor to the candidate, though the questions will most likely be only about the dissertation rather than general questions about the field as a whole. In some places you need to be prepared for both. But if you can answer the written questions you have a good idea about what a careful reader of your work might still want to know. This prepares you for the first, but not the second sort of questions - about the field as a whole.
The lesson here is not to focus so closely on the dissertation itself that you forget everything else you know. Freezing up can be an issue for some people, so it is good if you have practice in speaking generally (say through teaching) and have ways to calm yourself quickly if asked an odd question. This is more of an issue in those places that have an "out of field" member of the defense committee - a person from a totally different field who will not have read your work. Your answers need to be reasonable, even when not strictly correct.


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Is it possible to become an independent researcher with a PhD degree in Mechanical Engineering
Dear Fellow Researchers,
I got my PhD degree in Mechanical Engineering from a EU university some time ago. I've got a good cv in terms of publications, peer-review work, participation in R&D projects, conferences, etc.
I think I've got some good ideas for research and development projects. However, in a Post-Doctoral position, I am very likely to be working on already approved projects, not my own ones.
So my question is: Is it possible to become an independent researcher?
All I need is to be able to apply for research funding. Is it possible? I can create a company or whatever is needed to get an affiliation, if that is needed.
What funding organizations would accept proposals in the field of Mechanical Engineering for those not currently working at a University/Research Centre? I am looking for EU funding organizations, but I am willing to accept those in the USA/CA/AU.
Any help appreciated,
Best Regards,
King Baboon

The question starting "What funding organizations" seems like a "shopping question".

It is quite common in Germany and the Netherlands for "advanced" postdocs to write their own grant proposal. So I would challenge your assumption that you need to become independent in order to do your own research as a postdoc. Instead I would suggest that staying within academia and write your grant proposal there, has a much higher chance of success.

Yes, it is possible. Your best bet would be to partner up with an organization or a company that is interested in the same thing what you are interested in. Then you can establish a non-profit organization and look for grant funding. Or start a for-profit limited liability company and, ideally, get a contract from a partner/customer to do your particular research, or find investors and get help from those multiple EU organizations that fund high tech startups and then look for customers as your research and develop your prototype/minimum viable product. You can try both ways if you have time and not too many bills to pay. They are not mutually exclusive.


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PhD by published work
I have developed a logical and consistent body of research of 8 papers about a research topic. I've heard I can do a PhD by published work.
It is just compiling the papers and writing the scope and importance of the papers  in 5000-10000 words, then the viva.
I know universities in the UK where I can do this, but they charge like 4,000 - 5,000 GBP for the submission.
Do you know other universities in other countries that charge less? I am thinking of Norway, Finland, Germany as they seem to have low tuition fees. However, I am willing to consider any country in Europe.
I am living in Portugal, so I would need to submit my thesis online, and travel to the university for the viva.
Any help appreciated.
Thanks,

Do the 5000 GBP scare you? I would think that it's a good investment for future job prospects, and this investment gets better the better the university is that you get the degree from. Skimping on a couple of 1000 pounds in return for degree from an unknown university does not seem like a wise investment.

Is this possible to be done in Portugal?

What is the point of obtaining a PhD from a university if you never really attended the university?

@AustinHenley Some people would find the on-paper credential to be useful for professional development and job applications, but have worked for years in research or research adjacent work.

Proceed with extreme caution.
What you are describing is known as a stapler thesis or sandwich thesis. This is a common practice for submitting theses, if the advisor, department, and university permit it.
However, such theses are submitted by students who are already enrolled at a university. Virtually all reputable universities will require you to enroll as a student for a period of time before you are eligible to submit your theses, and you generally have to show that you have made contributions to your field during your period of enrollment. Taking a bunch of previously submitted papers and submitting them as a thesis at a school you have never attended, particularly for a large fee, reeks of a school being a diploma mill, a plain old scam, or just desperate for cash.
While the UK offers such programs, they are normally for their own alumni and employees, and it can be a very time-consuming and frustrating process. Moreover, such programs are not well regarded by many employers, and you will be at a disadvantage for many jobs if you have to compete with recipients of standard research PhD’s.

Although I don’t doubt that many of these are diploma mills, Warwick certainly isn’t. In general, it seems like there are several reputable universities in the UK that allow for this.

@StellaBiderman: this is true. That’s also why I added the last paragraph: even if it’s not a scam, such degrees aren’t going to be looked on favorably.

This is possible at Danish universities. See
http://www.medicine.aau.dk/doctoral-school/phd/become-phd-student/phddegree-without-previous-studies/
and
http://www.dtu.dk/english/Education/PhD/Rules/PhDguide/Thesis
for more information.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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How to allocate my time for two subjects?
I am working at my undergraduate university as a research assistant with my supervisor. Our group's research interest is in security and web, so we do projects about middlebox, encrypted searchable database etc. However, my personal research interest is in reinforcement learning and game AI. The reasons I joined a group that has a different research interest are:

I am entering my graduate university (different than my undergraduate one) in around 6 months, and I need a job before that. Staying in academia gives me chances to publish papers than joining a company.
For some reason, I had no better choice of research group in my university.

I am perfectly fine with doing research in a new subject, but I still want to make progress in my own area(which I am not sure is possible), since I plan to return to it in my postgraduate program.
Is it better to devote 100% energy and time in my group's research or allocate some time for my own research?

100% into your main activity unless you are such a brilliant person that you can split it up differently.

You just have 6 months for this current job. Your personal interest can stay with you forever, and you can invest more on that when you have joined the grad school.
For now, I would recommend giving your 100% to the current research and get more productive outcomes on this, with good papers and collaborations. If you feel like you have too much time, energy, and enthusiasm, give 200% of it to your current work!