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Getting a master in math after an econ PhD
Ok guys, I know this is a weird question.
I have found that the opposite has been asked many times, however I could not find opinion in how useful would be to get a master in math after completing a phd in econ.
I am at an advanced state in my PhD and I do not want to give up now, because I stil believe I can make it to the end. However, I believe that I will never fully understand some topics without having some intense training in math. So I am considering to successfully complete this path to start a degree in math that could also give me some research ideas for my future career.
What would you say of this atypical question? What are good institutions to learn math (better if linked to good economics department) in Europe?
Thanks in advance for your consideration.

It seems like a very strange route to take, and I'm not sure how it would be received since I've not seen anyone take more math after their PhD in econ.
Did you have differential equations and real analysis before starting your PhD?  If you covered those common bases, you might still gain a few useful things if you go a highly theoretical route, but you've already got most of the math you should need done.
If your interests are more empirical, it definitely does not seem like a good use of time to me.  If your interests are theoretical and you were able to keep up with PhD-level theory in econometrics, macro, and micro, it's probably still not a great use of your time, especially compared to actually getting to work in an econ field.
The best I can say about it is that it probably wouldn't actively hurt anything directly, except for the opportunity cost of publishing economic papers, and it might give you a route into doing more heavy theory.

If what you want is to become an economist, and not some technician that wants to apply mathematics using economic examples and models, then I would heartily applaud this decision: here is a person that is determined to have his economic research written in the most transparent way, namely, by robustly and concretely using math to clearly state assumptions, constraints etc of their models, away from the vagueness of verbal arguments (every economist should know what happened when J.M. Keynes wrote the book he wrote: we spent decades discussing "what Keynes really meant").
Just make sure that the Master you will take deals with the parts of mathematics that economists use, and this should initially guide you in targeting Universities. I suspect something like "Applied" should be in the title of the program.
PS: And yes, I almost totally agree with you, Kenneth Arrow is probably the best.

I generally agree with Alecos +1 answer, in economics you can never know enough math.
However, I would question the usefulness of formally pursuing masters in mathematics. If you are able to complete PhD in economics you should already have some solid foundations in mathematical topics commonly used in economics.
If you take masters in mathematics you will likely learn more than you already know but you will also be forced to repeat many topics. At the same time from job market perspective, MS in mathematics in itself won’t matter as much as your job market paper and rank of your university where you get your PhD. So formally taking the masters in mathematics will not give you much benefit besides learning more mathematics.
If you care solely about your math skills there are better options in my opinion. Consider sitting the math classes at the MS in mathematics at your university (if your university has math department). Usually professors would allow you to sit their classes even without being enrolled in their class. Many would even share with you course resources. In this way you could pick and choose exactly just advanced classes or classes in areas you think you need for your research.
Nowadays there are also quite high quality MOOC math courses often offered by top universities. The only downside that they have is that you don’t have the personal experience but in these times of pandemic you would most likely not get that with masters as well.
To sum it up, I think that you can never go wrong with trying to learn more math if you want to do research in economics. You will always feel that you never know enough math. But at the same time I would question whether the decision of getting masters in mathematics would pass cost benefit analysis.


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On average how many research questions do you come up with before finding the one worth pursuing?
Like every other Ph.D. student, I am having a tough time finding a good research question.
Thanks to Varian's advice "how to build a model in your spare time", I can come up with a lot of interesting topics and questions (judged by my peers and supervisors). Still, when I start looking at the literature or the data structure I need, I find myself in one of the following situations:

There is already a published article way better than what I thought explaining the issue
The problem is worth pursuing and there is a gap. Yet, the dataset is not available or too costly for my budget

This process seems very time and energy-consuming, and while the latter resource may be renewable, the former is not.
Am I doing something wrong? How many research questions does an experienced researcher throw away as not worth pursuing?

I don't feel it is possible to quantify "number of research questions".

Aside from this being a request for opinions or anecdotal information, talk with your doctoral advisor. If they have grant funding, the work does not get done by itself. If they do not have grant funding, then that talking part is even more important. Best of success!

@BryanKrause why would you say so? In my case, I have explored two research areas in the last year finding four questions that were judged as interesting enough to pursue. In the end, I had to start again because I find myself in the situation above.

Maybe in your field there are more well-defined research questions, but in mine we could discuss a couple dozen in one meeting. Do those all count? How far do we pursue them before it counts as having explored a direction? Alternatively, I could say I've spent the past 12+ years working on a single research question. I could also choose any number in between by simply adjusting the definition of "research question".

@BryanKrause, I now understand what you mean. In my context, I am basically cut out from the whole department due to the pandemic, so the few ideas I get and I explore take at least a month of work to understand that it's a dead end. I am now convinced that the problem is the lacking discussion phase, as Ed V suggested.

It is unending.  For every research question I come up with, I generate N more questions.  This continues forever.

I guess the only valid answer to this question is literally, "As many as it takes". Research is about diving into the unknown and that is fundamentally the issue. When you start, you don't know.
First an anecdote, then some advice.
I worked on three problems for my dissertation work. The first was too easy and I was able to prove theorems every day. Easy, but therefore not significant. I gave up after a couple of weeks. The second problem was too hard. Nothing I thought of could make a dent in any way in the problem and insight was elusive. The third was just right. It was hard, but do-able, and it turned into quite a significant piece of work.
But, and this is the advice part, along the way to solving the third problem I developed insight into not only that problem but into other problems that were related, some closely and some not. I was smart enough to capture those ideas as they occurred as possible future work and when I finished the dissertation I had a file of potential expansions and parallel things to work on in the future. That is a very big deal. That file of ideas that may be more than you can do at the moment, but should be looked at later.
So, as you are doing your literature search, look for those possible extensions and/or parallel tracks that might prove fruitful and keep a file of those ideas. You can attack the most promising ones now and it might lead to success but you will probably also have other ideas as you work. Add those to your file.
If you are really doing research then there are no guarantees that anything will be both doable and significant. You have to keep looking. A good advisor (I was lucky there) can help greatly in this. But the unknown is unknown until someone makes it known.

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How can I apologize to my former research professor whom I ghosted?
At my university, I worked with a professor in knot theory for about a year. I am an undergraduate, and I wanted some experience in research. This professor was one I had a fairly good relationship with, and he actually helped me be able to skip some classes which I had already self-studied. Because I enjoyed the professor, I decided I wanted to work with him and his research group. However, I have discovered that I currently do not enjoy knot theory; it's a rather esoteric subject with few resources from which I could learn it from and gain some intuitive understanding, and one needs a solid grounding in topology to do much in it (I do not have a solid grounding in topology).
Ultimately, I didn't really do much during my research (I both thoroughly disliked it and wasn't able to do much; the latter fact probably influenced the former) and when COVID-19 hit I simply fell off on researching and communication with the professor. I fully realize that both my lack of effort while researching and the actual ghosting was quite deeply wrong. I have no plans to do anything similar to my current research mentor or any future ones regardless of how the research goes, so please do not lambast me too much for this. I now do research in physics (where I am much, much happier), but I feel quite horrible for what I did to my professor. To make matters worse, I have several books on topology that I would like to return to him (on somewhat of a tangent, Munkres's books, while good, are not exactly the most stimulating textbooks I've read, so I didn't learn too much topology). I very much want to apologize for my actions and offer to return the books, but I don't know how to do so gracefully. If any advice could be granted, I'd appreciate it immensely.

Google “how to apologize”, you’ll find plenty of good advice. There is nothing specific to academia about your question.

It will vary from person-to-person.  From my perspective, just return my books :)  We understand that students lose interest over time, or have 'better' things to do with their life.   Just be honest.   An experience teacher will know there is no point trying to flog a dead horse.  We will wish you well.

I agree fully with Spark's answer that this isn't a big deal.  That said, I would not write several of the things you said above in your email.  "Esoteric" comes off as somewhat insulting to the field, and "few resources" could come off as implying that the advisor did a poor job connecting you to the right resources.  Keep it short and don't blame the subject.  You don't have to explain your reasoning; just apologize, ask about arranging a drop-off of the books, and thank the professor for all their efforts.

Often enough in these kinds of interactions, the situation feels much more dire than it really is because you're not in touch with the professor. You are left to your own devices, building scenarios of how much this professor must hate you now and how terrible it is that you left.
You're fine.
Knot theory is knot for everyone (ha ha!), a fact your professor is probably well aware of. Sure, it would have been nice if you had let them know earlier, but I'm quite sure they realized it during your internship.
The best thing to do now is to reach out to them, apologize for not being in touch earlier. Keep the email short and to the point, no need to write a 1000 word essay. You're likely to get a short reply acknowledging your email and that would be that.
The only point that might have genuinely pissed them off is the books you took and didn't return. Offer to return those as soon as you can, at your expense. While I share your opinion about Munkres, an unpleasant read even for seasoned mathematicians, the books belong to someone else and should be returned.

I'd add that given pretty much everyone has been impacted by the pandemic in one way or another, this situation is even more understandable than it usually would be.

"Knot theory is knot for everyone..." (+1)

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(Paper submission) Institution vs affiliation
I'm about to submit a paper to a scientific journal. among the info required there are 1) "institution" which is mandatory and 2) " affiliation".
My question is: what's the difference?
I'm an Adjunct Professor now, so I think in my case that for the institution it refers to the place where I got my PhD while for the affiliation it refers to the place where I'm actually working. However, I want to stress that my role in academia is reserved for teaching activities.
What do you think?

It's (almost) all about the address you can be reached under. The remaining part is about where the work was done. In the context of paper submission I'd see "affiliation" and "institution" as synonyms.

Institution usually refers to the institution that the work was done at, or at least who pays the bills for that particular author most of the time.  For many authors this is the only institution they are affiliated with, so it really makes no difference.
Affiliation refers to other organizations that the author is affiliated with.  For instance, say I am a researcher at university A, but a medical doctor at an associated hospital (I'm not, but just say...).  Then I might list the university as my institution (because they paid for my lab space, perhaps they had the research ethics board etc) but I am affiliated with the hospital as well, which is where the research subjects came from.  I would list both, because both organizations should be recognized for their financial or in-kind contributions to the work.
Sometimes, authors have multiple affiliations just because they've been given appointments by other organizations, whether because they want to boost their prestige or because there was a relevant reason for this to happen.  For instance, if a university researcher is working on a space mission and they are given appointments by some NASA research centers, they might list those appointments as their affiliations.  These organizations may have contributed lab space, equipment, funding, personnel etc, all under the guidance of the researcher, and the organizations should therefore be listed.
Sometimes it is necessary to divulge a conflict of interest as well.  Say that I am a university researcher doing research on a drug for a company that I am also on the board of directors for.  I should mention that company in my affiliations (among other things)

In a simpler case, for a researcher in university department without any outside entanglements, the institution would refer to the university, whereas the affiliation usually includes finer details like the department.


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Is this tenured professor plagiarizing his lectures?
A tenured professor at my university has hand-copied an out of print textbook in his field. His lectures consist of reading his hand-written notes from the text to his students. He does not deviate from his notes. He does not reveal the source of his notes. He often refers in class to "my notes" and "my lectures." His lectures are the same, year after year. Students do not have to go to class if they get good notes from others who took the course in previous years. Is this plagiarism?

Even if he did, what do you expect to achieve by knowing or reporting this?

What exactly should be the plagiarism here? I take it he says it is from the book?

If he lets you know which book then it isn't plagiarism. If it is a text book, then it was written so that people could lecture from it. There is no violation here. If he teaches the same course in the same way year after year it is not a violation of anything, especially if the material is settled knowledge. This would be true of most undergraduate courses. He might be a more effective teacher with different practices, but he isn't violating any rules, provided he tells you the source; a form of citation. Of course his other teaching practices might make him a great teacher. Can't say.

Do you know which textbook it is?  Is the concern that he's hiding it, or merely that he doesn't declare it outright and up front?

If he is reading his hand written notes, doesn't that indicate it's his own work ? I doubt he has copied out an old text book in long hand.

This is plagiarism in the purest form. You may be using a source whose priginal author allows you to use it as you like. This means you're not violating copyright. But plagiarism is different, using somebody's work and passing it off as your own is plagiarism and he is a poor excuse for a teacher. And definitely should not be a professor. This is not rare, I keep seeing it all the time to some extent but do nothing because the problem is too big and this behavious is widely accepted.

While there are a number of issues with this teaching style, there is no plagiarism because there is no expectation of originality in teaching. He could teach better, probably, but it's not like you can report him for plagiarizing his lecture notes.

"there is no expectation of originality in teaching."  This is not a valid reason not to cite sources.  There is no expectation of originality in a review article or a textbook, but those documents must cite all sources used.

@AnonymousPhysicist It is hard to evaluate this without more details. We do not even know the field.

@AzorAhai-him- Then a less certain answer might be warranted, instead of a verdict of not guilty.

@lighthousekeeper I suppose it depends on how you interpret "he does not reveal the source of his notes." But nevertheless, I do not see a situation in which the OP's description could be considered plagiarism. Could you suggest one?

@AzorAhai-him: Copy-pasting from a textbook and keeping this secret is no different than copypasting in a researchpaper while mentioning that this is a known result, but not saying the source. I agree with you that one cannot report this (nobody is interested in how a tenured prof teaches),but I don't find it so unthinkable that this could be plagiarism as your comment seems to indicate.

@user It's obviously not secret or else OP wouldn't know

@AzorAhai-him-: I had a prof who copied his notes onto the blackboard, never mentioning where they come from. We googled one time about the subject and found lecture notes (by someone else) which were 1 to 1 the prof's notes. (Of course, "reporting" would not yield any action except for a worse treatment at the exam). I interpret OP's "he does not reveal the source" the same way: the prof doesn't tell, but somebody once found out. I don't think it's obvious that this is not the interpretation of this sentence.

@user111388 Again, it doesn't really matter. It might be generally good pedagogy to share if you do something like that, but since lecture notes are not "works" with any sort of standards, the prof doesn't have to share anything. This sounds like an intro class (if an out-of-print textbook is still relevant) so citations aren't as relevant as in an advanced class.

It doesn't seem like the OP is trying to track down references and failing - it sounds like they're trying to "catch" their professor, like a lot of plagiarism questions here that treat plagiarizing as a game between student and professor.

In Germany this is very common in the undergraduate lectures. Usually we were able to go to the library after the first few lectures, look up all the popular books on the subject and find the one that the lecturer was following. You could then sit with it in the lecture and always predict what was said next. Some lecturers told us which books they were following, others had it directly on their desk, some tried to hide it, and some changed mid-term because the next topic was covered better in a different book.
Ultimately this practice helps everyone. A professor is supposed to do research and not spend days preparing an original lecture, and the popular literature on the topic will be much better structured and presented then your professor could probably do. Please be also aware that even when not published as a book, lecturers usually have material collections that they pass on when somebody else is giving their lecture in the next term.
So I am strongly suggesting that you report nothing as you will be probably laughed of by the department while leaving a bad impression.
Edit: There is also a general philosophy of "a lecture is not public", and therefore the usual rules for citations (and also copyright) do not apply.

"It helps everyone": I have a really hard time figuring out why "copying everything and hiding the book's name" helps everyone when the prof could instead "copy everything and not hiding the name" (and why in the former case, profs have more rime for research). Mentioning the book's name sets a goos example and the students know where they can look something up in case they couldn't read a symbol on the blackboard.

The students are not forced to attend the lectures, lecturers are explicitly forbidden to write down the attendance of students and can only base their grade for each student on the final exam at the end of the semester, not on participation or no-showing of students during the term. With these rules, many professors feel that openly communicating the book they are using will result in an empty lecture hall and ultimately to worse performance of the students as the majority does not read a book at home with the same attention that they follow a lecture.

Well, yes, they may fear this (and it probably is correct) - but this is the student's responsibility and no reason to hide the name. (And I know students who stopped coming to useless lectures, learning the stuff from books and know the contents better than those in the lecture). It definitely helps not everyone to hide the name.

"A professor is supposed to do research and not spend days preparing an original lecture" Teaching ought to be prioritized over research, but it often is not.

"There is also a general philosophy of "a lecture is not public", and therefore the usual rules for citations (and also copyright) do not apply."  Wrong.   Academic honest applies to private academic activities.  Grant applications are an obvious example.

"Professor is supposed to do research and not spend days preparing an original lecture" WRONG. Teaching is their job and we pay them to teach us. If they only care about their research and neglect teaching they they're not doing the job they're being paid to do and should be dismissed.

I have a couple of observations from personal experience. As a grad student, I audited a course in functional analysis. We had a required text for the course. Each day, the professor came into class, opened the book to the appropriate place and started lecturing. In another course, which I actually took, the text was a well-known text on complex projective varieties. After a few days, I realized that what the professor was writing on the board looked awfully familiar, and checked the text (in class) and discovered that he was writing his lecture, verbatim, from the book. In neither case did I have a problem with what was happening. In fact, it made my job easier. As @Terri mentioned in another answer, this allowed me to concentrate on the material, instead of trying to copy it down. I read ahead and knew what was coming. Any useful asides that the prof mentioned were duly noted. Perhaps we were more indulgent of our professors back in the day.
In any event, I have been around the block a few times. There are things that are worth getting upset about. I don't think this is one of them.

What I don't understand is why it helped you more than if the prof said the name of the book and "I will copy-paste from the book."

@user111388 -  At that time, we didn't have copy-paste capability in the current sense. We already had the text. The main benefit was not having to write detailed notes.

No sorry, I mean you seem to say it helped you more that the professor lectured from the book without mentioning the book's name instead of lecturing from the book and mentioning the name. I also had both types of profs (who copied their notes from a boom and read them out loud and we copied them). One said where the notes come from, one didn't. I still can't see what was "better" for the hiding one. In both cases, you could concentrate on the material, no?

@user111388 - We're on the same page here. Concentrating on the material was the principal advantage. Had I not been reading ahead in the book, I never would have known what the prof was doing. I don't know if he "hid" the book per se. Maybe he just assumed we would see what was happening. As I recall, some of my classmates supported my conclusion when I made it, the others were oblivious. I guess this is kind of the nature of things, even at the graduate level.

Plagiarism refers to passing off others' ideas as one's own. If you are writing a research paper (researcher) or an assignment (student), there is an expectation that you are articulating your own ideas, unless you specify otherwise. If you are conversing with friends over coffee, less so. Class lectures are somewhere in between.
There may be many good reasons to hew extremely closely to the presentation in a book in lectures, especially in certain fields like math. It takes a lot of work to write a compelling set of notes on one's own, and there may be little to gain versus using something already canonical in the field. Of course, parrotting a random book from years ago may also indicate just laziness.
I have definitely at various parts of my academic career lectured "from the [assigned] book", as well as on occasion presented my own material or lectured on part of the material from a different book. I definitely openly mentioned the source, as a natural habit of giving credit where credit is due, and of guiding students where to look (which in the case you mention may be more difficult if the book is out of print, of course). So it does seem weird the professor makes no mention of it, whether it is by design or by accident.
On its own, the use of the words "my notes" or "my lectures" could be using the word "my" as demonstrative, not possessive, i.e. merely which notes he is referring to (the ones he is transmitting to you) rather than taking intellectual credit for them.
All in all, the most likely interpretation seems to be of a pedagogically lazy dinosaur, rather than a nefarious plagiarist, or conversely a brilliant pedagogue bringing you a carefully selected optimal, but unfortunately out of print, presentation of the material.
Finally, putting words in your mouth to be sure, I'm sensing a feeling of injured inequality and hypocrisy here - "how come when we [students] do It it's plagiarism but when a tenured prof does It no-one calls it that". If that's the case, hopefully the distinction regarding assumed level of originality of ideas depending on the context will be helpful to explain it. It's worth also noting that the current level of vigilance about plagiarism on University campuses comes as a direct result of the ease of copying (without attribution) from the internet, with minimal reflection or internalization of the material. Being a bit of an old dinosaur myself, it is just not a theme we thought about as much years ago, when copying something meant manually transcribing it, and so was essentially as much work as rewording it. Still highly relevant for actual research, of course, but less top of mind for lectures, assignments, and the like. So if you pointed out to the professor that you were aware he was presenting "from X", he might well smile warmly at you and say "Oh yes, great that you're aware of X. Such a shame it's no longer in print. In my day, we all learnt [...] by copying out its presentation to understand it" and continue along serenely, with no thought of plagiarism in his mind.


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Why do fundamentals matter?
In certain situations, fundamentals may not matter, but very often, especially for long term learning, they really matter. Since this is a deeply held belief, perhaps moulded by experience, I find it tricky to articulate to an intelligent skeptic why they should bother learning fundamentals. They often have surprisingly strong rebuttals, including:

experts do not find such basic material interesting

I empathise: if someone in a specific niche is getting along just fine without understanding fundamentals, they may have no motivation to learn fundamentals, especially if they're already recognised as an expert (not necessarily by peers, but perhaps by students, clients, or consumers of their research).
Question
What lines of reasoning or resources (preferably canonical ones) do you use to demonstrate the value of fundamentals to those who may be sceptical of the value in learning them?
One Example
This happens to be from a physicist, Richard Feynman:

In physics, when you discover new things, it looks more simple

(when) We learn about a greater experience .. the laws look complicated ... but .. every now and then we have these integrations .. (and) it turns out to be simpler that it looked before

The corollary being that when we understand something on a fundamental level, it's actually much easier to communicate, understand, model and predict.

Can you give an example of a "fundamental" whose pedagogical value you doubt?

@cag51 I don't doubt, but frequently see cases where someone doesn't see value in fundamentals. Some quick, specific examples (others may have some much better ones). In software, when someone needs to get something working quickly, copying code from stack overflow and running it without any understanding of what it's doing. In biology, racing to research a topical and easy (or "sexy") area of research, while neglecting more fundamental areas which may be more difficult but of much greater importance (that's subjective, I know). Economic principles which seem so simple they're not scrutinised.

@Roland I think papers like the one you point out are actually more common than is realised. And even more common in research that isn't thoroughly peer reviewed (e.g. some government or private sector research). I'm not sure if you intended to, but you provided an answer: to avoid embarrassment. That's pretty funny, and brutal, and actually the best answer I have so far. But then the problem is what if the party without the understanding of fundamentals is simply not at all embarrassed? What other reasoning or appeals can or should be made?

@Roland: Hmm, I'd argue that rather than the paper itself, its considerable number of citations (which has also been mentioned by @DanielHatton) provides strong evidence of a general lack of "understanding the fundamentals".

@JochenGlueck but how many of those citations are from papers pointing out the mistake or using it as an example of lack of understanding?

@stevec - Could you give one concrete example that applies to your question? Your examples in the comment above are quite vague.

@astronat: Ah, sorry - I just noted that I forgot to reply to your comment. (Fortunately, it seems tha DanielHatton has already replied instead of me. ;-) )

You can't read Shakespeare without knowing the alphabet, but that doesn't mean you find the alphabet very interesting.

@Andrew but is finding something uninteresting grounds for excluding it from research or learning? I have experienced it being used as an excuse for avoidance of fundamentals. i thought creating the case for fundamentals to be very easy, until I actually went to do it. I believed in fundamentals almost as through it were religion! So I seek evidence or canon that supports learning fundamentals, and most importantly, explains why it is important. A good example I stumbled upon 2 days ago was Principia Mathematica spending some ~200 pages to prove that 1 + 1 = 2

Hm. Well, it depends a bit on exactly what you mean, this is a bit too abstract for me to understand. You certainly can fall into a trap of getting lost in the weeds and not getting anything done. The 200 pages were not really there to prove 1+1=2 -- as I recall in the book that theorem has a note like "this is a relatively unimportant result we prove due to historical interest" -- but to build this logical edifice which was the main goal. If your goal is not to build a logical edifice for all math, spending 200 pages on 1+1=2 is probably a waste of time.

Also famously the logical edifice of the Principia Mathematica doesn't work in the way the authors intended, due to Godel's incompleteness theorem. So... your mileage may vary :D


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What is a Research Scientist position?
In an advert, I read:
"[University U] is inviting applications for a multi-year fully funded Post-Doctoral Associate position. Highly qualified candidates may also be considered for a Research Scientist position."
What is a Research Scientist compare to a Post-Doctoral Associate position in an USA Academic like environment ?

Every university is different. However, my university (UT Austin) has, roughly, three research-only track positions: Research Associate, Research Scientist, and Research Professor. None of them are tenure-track or require teaching, and they all are roughly equivalent to the tenure-track positions: Assistant Professor, Associate Professor, Professor. Research Scientist has roughly the same promotion requirements as Associate Professor but only requires 3 outside letters rather than 8, and is a little lighter than the research and service requirements to the best of my knowledge. Both tracks can be proceeded by a postdoc position, but often do not. I started at UT as a Research Associate straight out of my PhD program and was later promoted to Research Scientist.
These positions are offered to give the university a place for professional researchers in non-teaching roles to work without the constraints or requirements of a teaching job. We have lots of them only mostly grant/soft money at the computing center where I work.

You're right, of course, that every university uses at least slightly different terminology.  I'm a bit surprised that UT has a nontenure track position called "Research Professor".  That seems to invite confusion.  On the other hand I once held a position called "Research Assistant Professor"...which was a part-time postdoctoral position.  So maybe the moral is that you never know what these titles really mean.

@PeteL.Clark, it is confusing, and AFAIK, there aren't a ton of them at UT. UT System's Handbook of Operating Procedures defines these things and is public. It's still hard to sort it all out. Presumably one could change tracks along the way if one wanted the benefits (and responsibilities) of tenure. I think that mostly the Research track is used outside of departments and in other units that don't teach or grant degrees.

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How to start in updating a published paper
In 2004 I published a paper on Graduate Surgical Education in a local journal. For some reason the paper has received a lot of credit and now I am approached by a Society in the USA that wants to re-publish it because according to them it is a reference paper. How do I start updating it. I never had to do this before. Thank you

Can you [edit] your post to clarify: do they want to republish the article as is, or did they ask you to make some changes and submit a new version of the article?

Are you sure you are allowed to "republish" the paper? Who owns the copyright?

Write the paper anew, with the new data since 2004. Compare both versions, try to keep as much as possible form the original (if that is what is being asked for).

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Current status "minor review" what is next?
I submitted a paper in a journal under Taylor and Francis and after the first review the status of the paper is "minor review". Both of the reviewers said that my manuscript can be accepted with some minor revisions. I am currently editing the paper according to their suggestions. My question is after I submit again will it go to the same reviewers or new reviewers will be assigned? How long will it take from a minor review to acceptance? I have no problem if it goes through multiple minor reviews but my main concern is to get acceptance notice since it is mandatory for my thesis defense, even "acceptance with minor review" status will work.

This was closed while I wrote an answer that gives some information not in the linked question... somewhat annoying that this was closed!

@Lewian I'd be happy to reopen if the OP can specify how their question is not contained in the duplicate one. If your answer instead contains details about the review process that have not been described in the duplicate, which is a canonical question exactly for these cases, and which can be of interest for the general case, I encourage you to propose an edit to the answer therein.

I had something about my personal experiences as editor at the specific stage the question here is about. Probably too focused on that stage for the other thread.

Update: i submitted minor revision on 6th and within few hours the admin made it "unsubstituted". Possibly he was the editor and he gave more suggestions. I again submitted on 10th and finally got accepted on 20th.

Ask the editor for guidance on this. It is hard to predict how long any review will take since the time available to reviewers for this work varies so much and is usually unpaid. Whether it goes to the same reviewers or not is up to the editors. If they want things done quickly (not a given) then going back to the same reviewers (or a subset) helps move it along.
But perhaps you can get some assurance, though not a guarantee, that the paper will actually get published. Let the editor know why this is important to you at the moment and that you aren't just anxious as all authors tend to be.


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What does "Awaiting Assignment to Batch" mean?
My paper was accepted a week ago, at that time the status in the ScholarOne manuscript center changed from "accept" to "awaiting production checklist". They also said I would receive an email regarding the proof check. However, till today I haven't received any email. Today the status again changed to "Awaiting Assignment to Batch". I am curious what is this mean? According to the journal, it takes 2 weeks(on average) to get published "online pre-print" from the acceptance date. I am just worried if I am missing something.

First, congratulations!!
"Awaiting Assignment to Batch" is part of the accepted workflow. Once accepted, some journals have a set of tasks that a manuscript goes through. One of the steps available (and being used here) is batching and sending of the manuscript to the journals production service. It will wait until a predetermined condition (so many ready to go, or a regular timed interval), then be added to a large zip file (along with others in the "batch"), and sent to the production server.
Hope this helps!
NOTE: I am am employee of ScholarOne, but my opinions and answers are only my own.

Thanks a lot. This is my first time submitting in a journal so I am just anxious.


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Is completely remote collaboration with colleagues from other cities/regions/countries possible in practice? (technical and natural sciences)
In fact, one group of scientists from one city/country for another group from another city/country are remote co-workers (employees). This means that you need to choose one of several formats for interacting with each other. In my understanding, there are 3 such formats:

The project is divided into “areas of responsibility”. One scientific group does its part of the work and transfers the results to another (e-mail, mail, freight). The second group does its part of the work and passes it on to the third. And so on.
If there is a need to solve some problems in real time, then the groups agree to meet on a certain date, at a certain site with certain software and equipment and carry out the necessary work in a live format.
Similar to the second point, but when the tasks are mainly of a research nature without the need to build experimental samples and move on to full-scale experiments.

I would like to know from the experience of other people whether completely remote collaboration with colleagues from other cities/regions/countries is possible in practice?
It would be desirable to have examples of such collaborations among several physicists, groups of physicists, groups of engineers, or a group of physicists + a group of engineers.

To a large degree this is how a lot of NASA projects (the really big ones) occur.  The project is managed in one location and various components are designed/built in multiple locations.  You just need to communicate (and travel).

This sounds like every multi-university research collaboration I have ever witnessed or been part of for 20 years.  recent changes have just added easier video and presentation sharing to regular telecons, and reduced the number of necessary in person meetings with performers or sponsors

My current project works like these and we have 5 different groups, working on different universities, for a specific project. Some insights I can share, one year in, and having several years of experience working in industry to let you know what can be the general situation:

Yearly meeting to catch up: I think this is good even though COVID normalized "remote" meetings, but since there is no "overshadow" leadership forcing people to turn the cameras on, you may find it a bit odd to just see default pictures in meetings. For our group, we have monthly meetings and we "know" each other, but I think it is useful to have meetings to have at least yearly meetings just to meet your actual colleagues.
Monthly meetings: Here I think is where I have most of the "could improve" messages, as most likely the group will be interdisciplinary and thus there may be a lot of strength in one area (e.g. A lot of chemists working with a smaller physicists/engineering group) so the meetings may be "too in the weeds" for some. Attendance is also not mandatory so it may be difficult to present work. I think my PI meets more often but for the PhD meetings it is nice to at least roughly know what the others are doing.
Work (may be) slow: By the nature of not being able to just walk down the aisle and find your colleague, responses can be slow and a bit frustrating if you have a lot of dependencies on other people's plates. It is best to spread work among different packages in order to avoid getting stuck to often, and try to find a compromise with colleagues who have important deliverables for you (e.g. a person doing measurements or providing chemicals).
Cultural differences: This is something that can possibly happen and is particularly true in academia, you may have colleagues who are not used to "being bossed around" by collaborators and rely only on their PI for work instructions. Some PIs may prefer to have full control of the communications, and some may prefer to only be notified by their own students. In general, try to understand how your direct dependents (e.g. direct collaborators) prefer to work and try to accommodate to their cultural caveats.
Lack of support: This may be a bit specific and I don't feel it too hard, but for example you may be in a critical "middle step" between application engineers (using chemicals for specific applications) or too far out (theoretical simulations of said chemicals). With that being said, depending on which end of the chain you are, your work may be more or less stressful. For example, if I need a specific chemical that is produced slowly and the chemists are busy with other projects and I don't get the chemicals, some of my work may be stopped, but in the end, I need to find a way to continue working and avoid halting the work too much (as time is limited). Understanding what the current status of the project is and what is your role is important to work more relaxed
Other projects take priority: It can also happen that other teams have another project in their PhD project and you happen to be on the "low priority" project. I have not personally experienced it, but I have colleagues signed up for 2 projects in their PhD and sometimes they take months to update their "low prio" project.

Thanks for your reply! Could you tell me in a little more detail what kind of research this is and any memorable result obtained during well-coordinated but remote work, when you were able to contact colleagues only through telecommunications? Otherwise, I would say that this is a mini-tutorial on team collaboration, highlighting many important aspects.

The project is based on nonlinear materials for light generation, thus the reference to chemists. I am in the physics/engineering part (application and conventional spectroscopy), and about 60% of the team are chemists. I am lucky that I onboarded on the 2nd funding period so the chemicals library is extensive and ready, so I don't have much friction for my deliverables. We have a Teams group to discuss together and publications are reviewed internally for cross-functional papers. We ship and receive chemicals and samples across 2 cities quite smoothly on a regular (monthly) basis. It works!

In my experience, these types of projects are quite common for professional researchers, especially for more applied research.
They are only uncommon for graduate students working on their degrees, because graduate students tend to be inexperienced (thus not very good at collaboration) and poorly managed (because we don't ask, train, or budget professors to be good managers).
There are many, many ways to organize such projects, and the main challenges are organization based, not location-based: I've often been able to collaborate better with a well-aligned researcher on another continent than one who is just down the hall but not as well integrated.

Thanks for your reply! Could you give an example from your experience of such a well-run research and the most memorable result obtained during this well-run remote work?

Sure, @dtn: here's an interlaboratory study that we ran with 244 collaborating laboratories: https://www.nature.com/articles/s42003-020-01127-5 All told, there were a little over 1400 authors, of which 12 of us were organizers. We were spread across 8 institutions on 3 continents and collaborated primarily by email and weekly meetings. The organizers collectively designed the study and materials, and some of them did prep and testing, then sent materials to all the labs to collect data, which came back to us for analysis. The project took 9 months to run and another 12 to write the manuscript.


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The employer gives a job, but asks for a “plan” of work with a horizon until the end of summer
So, this is a continuation of my topics :) This and this.
I need to consult specifically with the academic community.
I found a scientific group (part of a large scientific institute). The lab staff includes several dozen people, about half permanently live in another city, but periodically they gather in the parent organization.
I sent my resume, they were interested in it, the head of this laboratory contacted me and told me that they could use someone with my experience, what the laboratory does, what I have to do, what software to work with, they sent me by mail some equipment for the software debugging stage. In addition to the manager, I also communicated with a heating engineer, an electronics engineer and a mathematician. In principle, everything is consistent.
The trick is that I have programming experience, but not in their industry. That is, it is understood that I will still gain the necessary competencies on the spot.
Today we again called the head of the laboratory and discussed what to do next. In short, “he started the process, but in organizations like ours, things can slow down due to bureaucracy, but tomorrow they promised to send him a draft agreement” and “in the meantime, I would like to see from you a rough plan with control points with a horizon until about the end of the summer on the topic you will be studying"
Usually, when I used to get a job somewhere, I went through a full interview, passed a medical examination, collected a package of necessary documents, applied for a job and started working.
Here they ask me for some kind of plan (despite the fact that I still don’t really know anything about them, in fact), they don’t conduct a typical interview. And I just want to get to work first. For a regular job. I don’t know anything yet about future grants, articles, etc.
In short, a lot of strange things...Can anyone help me with this and share similar experiences, what do you think about it?

I don't think this sounds strange at all, I think it sounds like you're being hired for a position with higher expectations than what you're used to. It sounds like you're used to being a drone, and this job expects you to use your brain.

@BryanKrause I really can’t imagine what kind of “plan” one could write.  Without knowing anything about the work of the laboratory, except for their publications.  And without even having enough experience.  They will probably want to see something close to reality, but most likely they will only see my “fantasies on the topic...”.  For now I'm at a dead end.

You can ask for more guidance, but from the text you've provided it sounds like they're expecting you to be more independent. From your previous posts, can I assume this is a postdoctoral position? Post docs are often expected to be quite self-directed. If this isn't what you want, it might not be a good role for you after all and you might be better looking for a more ordinary job.

@BryanKrause No, this is not a postdoc position.  This is the position of a regular engineer.  Even the requirements indicate purely engineering responsibilities.  No requirements for publications, hypotheses, etc.

I see, well, it sounds like you need to talk to the person who is hiring you to help set expectations between you both. You think it's just an engineering job, they're asking what you expect to study between now and the end of summer.

@BryanKrause I have already started to master some things on my own.  And he even outlined a certain range of tasks, which, in principle, is consistent with the initial tasks of the engineer at this place.  The only thing I didn’t know was where to take this development further so that it would be consistent with the practice of their laboratory.  I need to think about this too.

Why do you ask random strangers on the internet what your employer is expecting of you based on a partial description of your interactions? Seriously...

@N.I. Of course, we are talking about an employment contract and full-fledged hiring.  This is exactly what we discussed and this is what I called the agreement. I'm interested in hearing other people's opinions.  Suddenly they see something that I might have missed.

This is a standard project management task --- treat it as part of the interview process and do a good job
This is not a particularly unusual request when an organisation considers hiring a professional who is expected to plan and  drive their own work independently.  The task serves two purposes: (1) to ensure that you have a reasonable plan ready to "hit the ground running" when you start working there; and (2) to demonstrate that you have the executive skills to undertake project management.  A small amount of preliminary unpaid labour of this kind is not unusual for applications for executive positions or research positions where there is some significant component of managing your own work.
If you have not previously undertaken a task like this, I recommend you familiarise yourself with standard planning tools often used in project management and use these to create your plan.  This is an opportunity for you to impress the hiring panel by showing them that you are a skilled project manager so err on the side of being too detailed and formal rather than doing it in a perfunctory manner.  At a minimum, write up a proposed schedule using a Gantt chart and make sure it includes all necessary elements of the work and reasonable timelines for completion.  If needed you can augment this with a work breakdown structure and network diagrams, though these are only likely to be necessary if you have a large and complex project.  You can also mention estimated resourcing requirements or costs for any parts of the project where these can be reasonably estimated.
If it were me, I would write up a full set of powerpoint slides giving a project management plan with a Gantt chart and work breakdown structure.  I would also mention estimated resourcing requirements and costs.  For anything that is impossible to estimate reasonbly due to lack of familiarity with the organisation, I would include space for this but leave it labelled as "[To be discussed]" or some similar notation.  I would then present this as a formal draft plan for the project, with the expectation that it will be refined and finalised upon commencement of employment.

Ben, thank you for your extensive and detailed response. What would you recommend to rely on when drawing up a plan?

From your question, it sounds like you have been briefed on some possible work avenues.  I would therefore develop the plan around these work avenues, but supplement it with any ideas of your own for additional work you could do to uplift the organisation.

I made a plan keeping your recommendation in mind. The plan suited the employer.

@dtn: Nice work!


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Vicious academic circle
I received some answers in this thread, but there are new ones that I would like to discuss with the academic community.
A little less than a year ago I received my PhD degree. By this time, my scientific interests had changed, so I decided to change my field of activity.
I found a scientific group that has extensive experience and material and technical resources in the area of interest to me.
Hypothetically, they could be a good starting point for me.
But the attempt to get to them was a failure.
According to the head of the group, today they have no open vacancies, and besides, I am not suitable either for the publications I wrote or for the proposed format of the job (they are located in a neighboring city, and I offered to work part of the time remotely, and part of the time to come to them).
And of course, I was ready to start from the basics with the starting salary for a young specialist.
They just don’t want to hire me and it’s a vicious circle. To get to them, I need to develop some kind of base. And in order to develop a base, I need to get into a similar scientific group.
Has anyone encountered such situations? How to find a way out of them?
P.S. It turns out that the specialization of PhD still imposes restrictions on the scientist?

I don't see this as 'viscous' - there is no guarantee that you would fit a particular job at a particular place, period. You keep looking.

@JonCuster That is, is it worth continuing to search for a group that will hire me (probationary period and “credit” of trust to develop a background)?

In addition to the valid points made by others, let me add that it doesn't seem like a good idea to combine unsolicited inquiries about possible positions (which are in and of themselves ok) with special requests like "offering" (you mean requesting) to work remotely part of the time, especially if you have a weak bargaining position to begin with (i.e. you do not have a verifiable history of contributions to the relevant subject matter).

There are multiple issues being addressed, such as being turned down for a job, looking for the right fit, and professional communication, that are worth discussing, but the question should be more specific and the author should reframe based on the other comments in rewriting the post.

If you want to switch topics, you have to start where your expertise is and slowly "ease" yourself in the new directions. Best to go to a group which appreciates/needs your background and has an interdisciplinary outlook, from where you can slowly develop in the desired directly. It's a multi-year process.

"It turns out that the specialization of PhD still imposes restrictions on the scientist?" Well ... yes? You haven't said how different these fields are, but I'm not expecting a GIS group to hire me, even though I think it's cool.

How is this different to your previous question?

There are two types of postdocs I hire:
(A) great scientists/engineers that could themselves be group leaders. As long as they have an interest in my group's work, I am not concerned about their specific background (within reason, and still broadly within the general field), but rather what unique things from their background they can bring to furthering my group's research (and also what they can learn while working with me). These are rare(r).
(B) solid technicians who can fill a technical role in support of a project. If you aren't a superstar but have the background knowledge to contribute to a project, you are in. Not everyone who postdocs can be faculty (statistically, even most from type A mentioned above won't get a chance either). Most people I have worked with are this category.
So I guess the question is, what do you bring to a team? Did you set yourself up with a highly marketable CV that opens many doors? If not (yet), then perhaps a better fit for your current skills may be the way to go as you hopefully build up a strong profile that will help you leverage a more desired position. Go be a solid Type B postdoc somewhere, there's no shame in that.
As for repetitively trying to get into one group, that would just be a bit awkward. Take the rejection and move on.

Thank you for your answer. I position myself as an interdisciplinary specialist (working at the intersection of technical and natural sciences). Of course, I am not a great scientist/engineer or a genius, but I think that it would not be difficult for me to master the necessary tools and perform the corresponding work, while simultaneously building a set of basic knowledge. And of course, I will look for other opportunities. In the group I wanted to join, there are still too many “pure” astronomers (including the group leader).

Then you need to make it evident that what you bring has value and that your background is strong enough to support it. It's a competitive market.

It sounds like you were turned down for a job. This happens. It may happen many times before you find a job. That is normal.
The next step is not to discover some convoluted multi-stage process to get into this group. Attempting this is very not normal and will likely permanently damage your relationship with the people involved and may even lead to them warning others about your not-normal behavior.
The next step is to apply for different jobs with different people.

Everything is just like that. But as I understand it, I should just continue looking for a group that will hire me (a probationary period and a “credit” of trust to develop a background are possible)?

@dtn I don't know what you mean by a credit of trust to develop a background. You should apply for jobs where 1) You have something useful to contribute, and 2) You're interested enough in the position to show up.

By this I meant exactly what you wrote about. That is, I have 2), but either none or very little 1)

@dtn - and that holds for pretty much any post-doc position one applies for. Or any position you apply for after that. But focusing on one and only one position with one group is quite likely to fail, just on random odds alone.

@JonCuster it means I won’t stop and will keep going until I find what I need

@dtn If you have nothing to contribute, no one will hire you. You need to apply to jobs that you have something to contribute to.

Echoing @BryanKrause's comments... and continuing: nowadays, hiring (and admissions) are competitive, intending to have safeguards so that no one has a magical inside track because of irrelevant features or "connections". So you'll be competing for such positions against people who do have demonstrable credentials... (and, in academe, there are always more qualified people than available positions...)

I'm not sure exactly what you expected. You applied for a job for which you have an interest but no experience to show for, and they said "no". The fact that you're willing to learn the skills may sometimes be enough, but more often than not, someone looking to hire somebody will want to hire somebody who can actually do the job, starting at day 1. They're not interested in hiring and paying a person who still has to learn what this is all about.
This leaves you with two options:

Spend some time unemployed (or while employed in a different) role to learn the new area and demonstrate that you have skills there.
Rethink your strategy and seek a job that matches your existing and demonstrated abilities.


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Problems with integration into scientific work and the team at the beginning of a career path
In the previous series: The employer gives a job, but asks for a “plan” of work with a horizon until the end of summer
So, I was hired in the lab, part-time, remotely and with a fixed-term employment contract for 1 year. I have already received my first salary, and the second one should be coming soon.
According to the plan that I made at the request of the head of the lab, my work is microcontrollers, FPGAs, control systems + mathematical modeling. I like this complex and interesting work.
I have officially been in the organization since June 17, i.e. a little over a month. I delved a little into the lab's specialization, made several small developments in the areas from the plan during this time. They are not systematic, but rather "drafts written for myself, so that I can more or less understand the issue", although they may be useful in the future. In general, I have not yet shown myself in any way, have not received any important results.
But I still do not quite understand how I can fully integrate into their team. Recently, the head of the laboratory said that he wanted to include me in the group to work on a grant (applications are submitted in early August) and asked to send documents with watermarks to the scientific work department. And that's all. Then he told me in general terms the current task (true, after my clarifying questions). It is familiar to me and quite logical for the goal they want to achieve. Having decided that I need to somehow move and show initiative (I am used to it), I said "I will figure it out". I am worried that this was not assigned to me directly on the initiative of the head in the form of a specific task.
Is this normal, is it supposed to be like this? Even though I was officially hired, it's as if I don't exist for them and I'm left to my own devices.

You were hired into an academic lab, correct?

Also, request weekly or fortnightly meetings with your supervisor, at least for your first few months.

@Aruralreader Yes, that's correct. And I myself try to talk to him about once a week to get an idea of the current tasks.

What sort of position is this?

@TerryLoring Well, it's not a postdoc. It's an engineering position. A software engineer, to be precise.

When you said "I will figure it out", what was his response? I can imagine anything from "Great! Go ahead," to "No,.I'll give you detailed instructions." Your course of action will surely depend on that response.

@AndreasBlass You'd be surprised, but that's exactly what was not answered. Then I took some generic devices and created CAD models of them to study the motion and sent him screenshots asking "which of these schemes will be used?". The answer was "we haven't dug deep yet, but we definitely need to figure out how to control these things. And always remember that all parameters must be realistic. And I think we will design these devices ourselves."

You are already having weekly meetings with him, which is good. In the meetings, tell him what you did since the last meeting, and talk about what you are going to do over the next week. I like to write down each thing I need to work on over the next week as we discuss it, then read the list back at the end. "Okay, so over the next week I'll do a and b, and then c if I have enough time." You can email a meeting summary afterwards so you both have a written record of what you agreed you would work on. This may help prompt him to suggest other things if he thinks of them.
Ask if there's a group meeting you can be included in. You can also try emailing individual members of the group to say you want to understand better how your work fits in with theirs, and ask if they have time for a 30 minute meeting to talk through what they're working on. Getting to know what other people are working on will help find opportunities to integrate better into the group.


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How does applying to work with multiple potential advisors at a university work?
I plan on applying to some graduate programs for a psychology PhD. At some of these universities, there are multiple professors I am interested in having as an advisor. If I am accepted to the program, how is my advisor chosen? Does my order of preference get taken into account or does it depend on which professor express the most enthusiasm to have me? Experiences may vary of course but any insight into this process would be helpful.

The picking/assignment of adviser varies dramatically by institution and department. In some institutions - for instance, in some of Carnegie Mellon's departments - the student chooses their adviser (and optional co-adviser) during the first month of their first semester after admittance, and the adviser needs only to agree. Advisers usually can say yes to any request they want because the department funds all new PhD students for the first year - and thus only becomes responsible for funding the student after that year. But some departments don't have the same policy!
A friend at Berkeley told me that their adviser actually saw their admissions packet and reached out to them to say, "I know you said you wanted to study X, but I think you'd enjoy topic Y that I'm working on" - and the student accepted and thus gained their adviser (in an entirely different field than they applied).
As yet another variety, I'm told that at some institutions the student is admitted with no adviser and the expectation is they will work with various potential advisers in different semesters for the first 1-2 years before being expected to formally have a permanent adviser.
The variety of systems is heavily influenced by the nature of how funding is handled at the school, as well as how admission is handled. In many institutions only the admissions committee decides on who is admitted and then advising comes later, while at others at least initial advising is part of the admission process (students are paired with potential/initial advisers before admission, and if you don't fit a professor with an open student slot then you don't get admitted).
Luckily this process is usually not a big secret, so you can talk with graduate admissions coordinators at departments you are interested in to find out just how things work there. Current PhD students are also often helpful in willing to share how they got their adviser, but be aware that their experience may or may not be typical (and sometimes they don't actually know).
Finally, there is great variance between institutions, and between departments within the same institution - and even greater variance between countries - and yet more variance across time as departments change their policies and strategies to recruit and retain students. So in the end - you'll really have to ask that specific department near the time of application to find out how thigns work


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Am I supposed to understand my training dataset for a machine learning project?
TL;DR: I am expected to work on a dataset with missing/wrong information about measurement units. Is this a common practice?

Longer version:
I am studying a Masters's program composed mostly of machine learning. This semester I need to complete a 12 credit Project Module. Project Module means that there are no lectures, just a problem formulation, consultations with a teacher, and then a final report, source code and presentation are submitted.
The problem is to identify rocks by melting them with a laser and measuring the spectrum of the resulting plasma.
The training data I have is a bunch of measured spectra (example visualization). Each file comprises of comma separated tuples (wevelength, intensity).
My teacher didn't have the time to figure out what is being measured when we say "intensity" and sent me the "example" above to figure for myself. Well, I figured it's radiance, based on information of the same source as the example I was sent(here)
Now, radiance is measured in watt divided by solid angle and surface area. This is strictly non-negative. The example graph also cuts the ordinate at 0.
Yet when I look at the provided dataset, I can identify regions such as
this one:
 188.5999999999995,15.175680381419365
 188.6999999999995,0.872615069518224
 188.7999999999995,-8.345751621890303
 188.8999999999995,-10.279252960079765
 188.9999999999995,-4.22895372957017
 189.09999999999948,3.978827692507486
 189.19999999999948,16.603400130260713
 189.29999999999947,-12.791825667786197
 189.39999999999947,-4.859145351410255
 189.49999999999946,4.452390240582065
 189.59999999999945,-14.106010857508583
 189.69999999999945,7.039306431256487
 189.79999999999944,-7.3039003395809505

Negative line intensities with values far from 0.
And here is my question. Both my teacher and a couple of more knowledgeable colleagues agree that there is nothing wrong with this:

The data you have is real world data collected with a hand held. Your model should be able to deal with the data as it is. You can apply preprocessing steps if you want to avoid negative data values.

To me it is absurd to even consider a dataset without first sanity checking it. Just as unacceptable I would call working with a preprocessed dataset without knowing how was it preprocessed (maybe I am seeing centered values, but no one told me the mean; maybe I am seeing a logarithmic scale).
Is it customary for a task to be presented this way?

Data is never perfect, and often the hard part in machine learning is cleaning the data. But, one must decide carefully whether these negative values indicate that there was some fatal flaw / error in the way the data was collected, and if there is some fundamental misunderstanding in how the measurements are being interpreted. If it is just the case that a smallish subset of the data are invalid, then that is normal and you can deal with it by cleaning the data or using a method that is robust against outliers. If there was a systematic error when collecting data, that might be much worse.

I would say that it would be very helpful to understand why these negative values are occurring. It suggests that perhaps what is being measured was not radiance after all. It is important to understand the data as well as possible; we can't just shrug off things that might be hinting at a deeper problem.

this is a computer science, no academia question

@user847982 I was wondering on which site to post. I did it here, because the actual core question is should I drop this shady course and not how do I successfully work with crappy data. By all means, do flag the question for migration and the moderators will decide better than me.

@littleO in a business setting, I would have requested a meeting with the person responsible for the data collection. In the current academic setting I did that, but I expect nothing more than "that's impossible".

Data you don't understand -> a method you don't understand -> report a result you don't understand, A+. Do an especially good job and maybe you can turn it into a publication? ;) I am only a little kidding, but its a pretty common formula in the field, for good or ill.

From the point of pure exercise in machine learning, you do not care whether the data is reliable and whether it was collected or taken from the ceiling. Your task is just to design a recognition algorithm that classifies the objects into groups based on the numbers associated with them. If you can do it, you pass, if not, you fail.
From the perspective of practical recognition of rocks, your algorithm (if it works) will be useful only if you trained it on accurate data or data with not too much noise and if you know what the numbers mean, so if you later are given the information in different units or on an altogether different scale (say, logarithmic instead of linear), you'll know how to convert before feeding them into the machine. If your algorithm is intended for real use, the people who requested the work should be most interested in getting things right, so you should be able to ask them as many relevant questions as you want. If it is just a practice problem, just forget about "rocks", "radiance", etc. View all that as an abstract classification problem about objects and numbers without any meaning whatsoever.
From what you are saying, it looks like you are in the first case scenario. I agree that the exercise is about as meaningful as the exercise in computing the area of the triangle with sides 6,7,8 and the altitude of length 5 drawn to the side of length 7. My daughter really had that as a problem on one of her exams and her teacher replied to my objections that at that stage of learning he just wanted to make sure that kids knew which side to multiply by the height. He wasn't a bad math. teacher overall, by the way, just a bit reckless about the details that weren't directly related to the current topic. Apparently, your professors have a similar attitude.

I learned some new information in the meantime. My instructor is also working on the project himself. Other students were given the same project with the same amount of explanation and without being informed there is further effort on the project. Conclusions are the reader's to draw.

This seems perfectly reasonable for a project at the Master's level. At that level you should be getting away from canned problems with perfect data, and actually tackling the complications that occur in the real world. Having to sort out bad data from good data and figure out normalizations and scaling transforms is a typical part of every real life application of machine learning.
I would also expect your advisor to be available to consult with on a regular (say weekly) basis. Your advisor probably won't be telling you exactly what to do next, rather you should be explaining the problems you are running into, and how you are planning to solve them. Your advisor should then be able tell you whether your approach is reasonable, and suggest other approaches if it is not.

Why are they even telling me about 'rocks', 'hand-held devices' or 'intensities'? Why not just give me a bunch of numbers and stage the task as we want you to find a bunch of numbers which look like the bunches of number we have provided you, but you aren't required to state in what way do they look alike?

@Vorac That would be appropriate for an undergraduate course in machine learning, but this is a Master's level project, and it is much closer to what you can expect to meet up with in the real world, except without your advisor hanging around to provide free consulting. The real world is messy and the people handing you the numbers may not even understand them themselves.

@Vorac Why are they even telling me about 'rocks', 'hand-held devices' or 'intensities'? That is an unfortunate custom: some "smart" educationist decided at some point that "real life setting" helps students to understand the material better, while IMHO it mainly just confuses them and prevents them from reaching the required level of abstraction. So we have calculus textbooks filled with pearls like "patient's temperature is a linear function of time", which attains the boiling point after 10 days or goes below absolute zero after 20, etc.

@Vorac On the other hand, when you;ll be doing a real project commissioned by some industry, you'll find out that, as Charles said, a big part of work will be to squeeze from the people who give you the numbers and tasks what they mean and what the actual assignment is. So, you'll have opportunities to practice your common sense sooner than you expect. However, I don't think that your Master's project was given with this in mind. It is not a PhD. Usually it is just "show us that you possess the skills we have taught you and have some fun in the process"

Dear @fedja I have worked as a developer full-time for 6 years before attempting this Master's. As you said in your answer If your algorithm is intended for real use, the people who requested the work should be most interested in getting things right, so you should be able to ask them as many relevant questions as you want.  This has been my experience in every business setting. I am not getting that here and that's why I am upset and confused. If I work with this data, my results are going to be sketchy at best. At best - as in if I do perfect job.

Dear @Vorac ,if you have that much experience (which I didn't know about) and common sense (which is easy to see), you are certainly qualified for this degree and it is, probably, well below what you can really get. I don't know if you had enough interesting challenges during your Master's program (if not, just consider this degree as means to raise your salary) but I suspect that the task was just to teach you new approaches, tools, and some theory. So just ask yourself if you learned anything new. If yes, some sloppiness can be tolerated. If no, the issue isn't this particular project :).


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Should I include PhD experience in MSc application?
I have a BSc in computer science and now I'm applying to a Masters program in Human Computer Interaction. A year or so ago I left an unrelated PhD program because I didn't think it would be beneficial to my end career goals.
Should I include this on my MSc application or leave it out?

Many US university applications will ask for all previous post-graduate enrollment.

You joined a PhD program without a master's degree?
Well... a master of science is about doing an small version of a PhD. In that sense, it could be beneficial to show that you do have some experience in research.
On the other hand, the fact that you left, probably without results or something to prove how well did you do it so far, might not be so positive.
But anyway, honesty should be the most important thing, and you shouldn't hide what you have done before. Also, it is definitely more beneficial to fill those gaps on your CV with the PhD time, instead of letting them think that you were just lounging around...

It's common for people in the US to go straight from a BS into a PhD program. They may or may not get an MS though fulfilling coursework requirements or doing a thesis along the way to the PhD. I followed such a route, though I did not get the MS along the way (could have, but I was too lazy to fill out the required paperwork and pay the fee).


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How to find papers which fall under the intersection of two different areas
I am asking this question specifically for the subject of Mathematics. What are some efficient ways of searching papers on two different broad topics, say number theory and graph theory. Also, if I want to be more specific and search for papers involving phrases from number theory and graph theory? I am aware of MathScinet, Google Scholar and arXiv. However, I do not know if there are ways to serve my query in these sites.
Thanks in advance.

Go have a chat with your local friendly research librarian who knows the ins and outs of all the search options available where you are. If you have them, some examples of papers within your search scope and some not quite in scope may help them. They will be happy to teach you how to get good results.

https://semo.libguides.com/google-scholar/advanced-searching. Use advanced search options on your engine of choice

If you have MathScinet access, you can search for articles by MSC Primary or Secondary which allows you to search by mathemtical subjects. If you don't have access, a similar search can be made in zbmath which is free to use.

Scopus has far more advanced search options than Google Scholar

@theL can I put multiple MSC classes simultaneously?

@jimm, yes. Mathscinet allows this.

I agree, use MathSciNet.  It should be available at any serious research library.

Scopus advanced search might be good. It is much better than Google Scholar in some ways.
https://www.scopus.com/search/form.uri?display=advanced
This shows an example of a search that is much more complicated than yours.
This is not a free service, so you will need access through your university or some other way.

I would do this using Scopus as well but I would also use another method.
Look up first article on topic. Click the link for articles that cite that article. Extract all the results as a list of articles.
Do the same thing for 2nd article.
Compare the two lists to identify common articles.
My current solution is to download many highly-cited papers (without reading) and index them.
Web of Science has a SAME operator, which matches “records where the terms separated by the operator appear in the same sentence”. Given that Web of Science supports four search operators (AND, OR, NOT, and SAME), it is safe to assume that this is the extent of its context-sensitive search capabilities. Then connect this to Scopus searches.

The first idea can be done directly in Scopus. Search for papers that contain the full titles of these two articles, or a distinctive phrase from each of them. This will give you a list of the papers that cite them both.


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Can one judge a Professor as researcher from his teaching in classes?
You would surely have read the quote which says

If you can't explain it to a six-year-old, you don't understand it yourself.

I'm a Master's student in Physics currently in my first sem. Soon, We have to choose an advisor for our Ph.D. There are instructors whose teaching doesn't fit to me (really saying to most of my fellow students). I wanted to ask, If I can consider that they aren't good at research as well? How much correlation there is between teaching and research?

The version of this quote that I know (from Feynman) is something like if you can't prepare a freshman lecture on a topic, that means we don't really understand it.  The meaning is quite different.

A (strong) correlation may or may not exist, but it is quite easy to look up anyone's research activity these days: just look at the publication records of your potential advisors and limit your choices to those who have been producing at least a paper or two per year in the recent decade or so.

@IiroUllin Well that's very field dependent because a paper or two would be paltry in my fields and would be a good reason to skip an advisor because their output is so low.

@AzorAhai-him- ...Or three, or four -- whatever floats your boat, or boats of your colleagues... :)

I would say not at all. Of course chances are high that a good researcher is a good Teacher as well, but in a broader sense than giving class lectures.

@Alchimista I disagree about the high chances. In my experience, the correlation is weak. Some people are outstanding researchers and scholars, but they can barely teach a sick dog to relieve itself.

@EdV I said that a good researcher is almost inevitably a good Teacher in a broader sense. That means one learns alot by working or being supervised by him/her. But this doesn't mean that that person is particularly good at teaching in a class course. And of course there are a lot of successful researchers not to work with or being supervised by. "The correlation is weak" : I agree. My short answer to the title is indeed "Not at all".

@Alchimista Actually, I disagree even with “a good researcher is almost inevitably a good Teacher in a broader sense.” But apparently we have had different experiences: I am just happy to have survived mine! ;-)

I've certainly seen all four combinations of good/bad teaching and good/bad research. But I'm not prepared to produce statistics on how likely each of the four is.

I would strongly disagree with the quote, as teaching requires very different skills than conducting research. There are many great researchers, who are bad at teaching, and vice versa.
However, this does not mean that you should not take a supervisor's teaching ability into account when looking for a potential supervisor for your PhD. Supervising a PhD candidate requires a complex set of skills, of which conducting research and teaching are two important ones. Another one is more subtle, concerning the interpersonal relations, essentially how well you two get along. The latter is an aspect that you sometimes can already assess from the lectures or classes you had with the instructor.

I would think that the correlation is low in general. But that is because tenured faculty get to choose, to some extent, whether to focus primarily on teaching or research rather than to both "equally". Both take effort, but a different kind of effort. And some faculty change focus over their career.
But it is certainly possible for someone to be great at both, for example, someone who can give insight into deep topics, not just detailed (pedantic?) explanations.
Using teaching ability (or a match between what they do and what you like them to do) as a predictor of their research is probably not a win for you. And, the ability to guide your research is also important along with the quality of their own.
For purposes of making a choice, I suggest you look farther than just those two "variables". How helpful they are likely to be when you need it (some research focused people are terrible at this). How successful other student advisees have been, both in their degree work and in starting their careers.
There are a lot of variables. Don't ignore other important factors.

I've known people who were excellent at both; one of my mentors. I've known people who excelled at one or the other but not both.
One example, that seems like a counterexample, is Robert Lee Moore who was both a pioneer in Topology, but also in a certain teaching method (Moore Method). His method was very effective, if you could stand to bear it. He didn't lecture and he didn't let students read mathematics. Instead he had them spend their time writing and developing math from the barest of hints. Most people would hate this, since it is very difficult, but it worked for the few that stayed with him.

No.
Counterexample: Einstein's English is fairly heavily accented, making him hard to understand. Therefore if he were to teach in English, it won't be outstanding. That doesn't say anything of the quality of his research, of course.

The quote is wrong.  There are plenty of things you cannot explain to a six year old but can still understand perfectly well.
Almost all the people I know who do not care about teaching are also not good at research.  This does not mean those who care about teaching are good researchers or good instructors, but if they care about teaching it’s usually a good sign.

I interpret it as my own 6 year old self, more specifically, break it down all the way to the sesame level concepts I had grasped at that age. (Even if I probably did not have the attention span to listen to my 60 year old self.)

Let me point out that the distinction in your answer, between caring about teaching and not caring, is not the same as the distinction between teaching well and teaching badly. There are people who put genuine effort into their teaching but just can't seem to explain anything clearly. (There are others who teach well without any apparent effort, but they might be putting in a lot of effort behind the scenes.)

Based solely on my personal observation, I would estimate that prowess in research and teaching are weakly positively correlated (i.e., I think there is some positive correlation here, but it is not strong).  There is some theoretical reason to believe that these things ought to be positively correlated, due to some overlap in the requires skills for the two activities, but as others have pointed out, there is also some degree of competition between the two roles in academia.
In any case, if you particularly want to identify the most successful researchers in your department then ---rather than relying on a weak proxy measure--- you could probably just ask around the faculty and get their opinions.  Professors in your department might be willing to tell you who they identify as a particularly strong or successful researcher, and who they think would be a good supervisor for you if you were to pursue a PhD candidature.  Research success (for the supervisor) is just one thing that is helpful in a PhD supervisor; there are other important factors, including having shared research interests and having a good "fit" in terms of learning style, etc.

There is a persistent myth that sloppy, unprepared, handwaving, wishy-washy, arrogant, condescending, etc... teachers must be brilliant researchers.
And one can climb the greasy pole quite nicely exploiting this.
However, it has been my observation that such people are also sloppy, unprepared, handwaving, wishy-washy, arrogant, condescending, etc... in their research, and it is usually best to steer clear of them.

Pretty hard for me to imagine a tenured professor who was so terrible as what you describe. Can't teach, can't do research, can't deal with students effectively.

@Buffy, yes, the phenomenon of irresponsible faculty has diminished in recent decades, I suppose due to the increased competition to get the jobs in the first place. But I do recall faculty with bad attitudes about everything, who seemingly believed that their very existence merited a paycheck. Still a few of those around, but far fewer than 40 years ago, for sure. :)

@paulgarrett, actually my experience covers more than the 40 years you mention. I've met very few people who were bad at everything at institutions that award doctorates.

@Buffy, maybe the handful of "problem faculty" were more striking (than the quieter, sagely people) to me as an impressionable kid who had idealized "math profs". :)

@paul garrett -- Do you still idealize math professors? I think that the list of mathematicians of great repute who are utter jerks would make an impressive list. Maybe I am bitter because I waited a year and a half to receive a 3-line rejection notice that my paper wasn't "appropriate" for their fancy journal.

@cgb5436, ha... no, I don't idealize them so much after dealing with them for 50 years... :)   Of course, many are quite decent people, apart from "being smart", but a disappointing fraction are jerks, indeed, ... many without any conscious intent, but just from some sort of cluelessness that was masked by success in math, etc. The biggest disappointment is the small fraction who do deliberately pee in the punch bowl. I was amazed to learn that there are any such people! Dang. :)

@paulgarrett: Do you have experiences of academics who wanted to sabotage you? Or went out of their way to try to prevent you from getting a job, getting a grant, etc.?

@cgb5436 Yes, a few. Was very disappointing when I came to understand what was happening.

@paulgarrett I was reading a guide to academia written by a prominent, now retired psychologist. One of the things he mentioned was that he thought the ivory tower would be a place where people put aside pettiness in search of knowledge. He had no such luck.

@cgb5436, yeah, that was the kind of thing that I'd thought about universities when I was much younger. :) With the current corporatization of many univs, and greatly diminished state support for many "state" universities, I really have no sense for what the future will bring. Almost makes me nostalgic for the early Cold War days, then everyone thought that "science would defend us from the commies (=devils incarnate)".

@paulgarrett: I think in 50 years nobody will be doing much pure math anymore, due to lack of funding, loss of interest, and because pure math papers are nowadays too long and too hard to understand, and that the current separation of pure and applied math will be seen as an aberration. This may be the minority view.

@cgb5436, yes, the pyramid/ponzi scheme of academic-X will probably collapse under its own weight... although history suggests possibilities otherwise. In any case, I hope it doesn't drag down legitimate scholarship and research in mathematics. By which I mean, not just trying to "generate publishable [sic] stuff", but genuinely reorganizing, synthesizing known things, sorting out problematical sources, and so on. Math is very useful in interpreting the world, evidently. To be sure, I do not want to be the one telling anyone that their "research" is b.s. :)

@paulgarrett Do you think math academia is a meritocracy?


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Instructor is convering a large portion of course in small period of time
We are taking a course in Mathematical Physics and due to pandemics, the semester period is reduced by at least a month than usual. The last few classes were rushed, the instructor barely give time to the big topics like Green function or Strum Liouville theory that should be given much time.
It is asked to give feedback to the course. We can complain, of course,  about this. But I think it's better to give an idea that can settle this problem. So I'm asking what can be done in such situation?

I see that you are enrolled in an Indian institute. I work as a faculty in one of those institutes and so let me tell you there is an immense pressure from the university administration on faculties to "complete" the syllabus. Further, if a faculty does not complete the syllabus, few students may even complain against the faculty. Certainly, this is a difficult situation to deal with.
As I understand it is better to prepare on one's own. In this digital age you have plethora of excellent lectures available for free on Youtube, free pdf books on the web. So just use them for your learning and in case you encounter difficulties you can then try to reach to the respective faculty of the subject matter in your institute. If the faculty then denies to help you, then I guess you have all the right to complain against the faculty. Alternatively, you have stackexchange to post your doubts and clarify them. Extend your arms, the right help will reach you.


text:
Is there any role of Assignments & Quizes in research?
I'm a graduate student and soon be a Ph.D. student in Physics. The semester is about to end. We have been given too many assignments throughout the semester that we don't get time to read the topic taught in the semester from a book at least once. So when we have to do the assignment, we usually search the problems on dozens of the books and see whether the question matches from somewhere or is related. Then we read that part and repeat the same calculation for our own problem.
Now there are very few of the problems, where we say, Yeah! I think I can apply this or try to approach it this way. It also leads to less interest in the subject. Now I know, that the assignments are necessary to do as they carry the weight of marks. I wanted to ask, If it's essential in the point of view of research.
I wanted to know about the correlation between solving the assignment problem and doing good research work.

My experience is that there is certainly a correlation between NOT doing well on every assignment and quality of research.  The correlation is not 1 (there are exceptions) but you will rarely find good researchers who did poorly on every assignment.

I'm very suspicious about "too many assignments throughout the semester that we don't get time to read the topic". Maybe they expect you to do both, maybe you wrongfully expect to read a well-structured book on it like you did before. In many ways, research is closer to "read dozens of articles with something remotely similar" rather than "read a single source with nicely outlined reasoning". In most cases of modern research, this book doesn't even exist in the first place.

@Lodinn, I know that a single book doesn't exist. But I made the point that we don't get the time to read a single book thoroughly. Does solving lots of assignments without going through the text make a sense for research in the future? Or reading several materials just seeking to help solve assignment problems, is this alright for the person who is going to do research later?

I meant it was preparing you for research in a sense that "solving lots of assignments without going through the text thoroughly" will be in many ways similar to your actual research. This is a model of what you will be doing, the only difference being that in the actual research, these assignments will be self-posed and, presumably, interesting. You will have an idea and need to handle dozens of minor problems, many of them solved before you - so you take these solutions, "repeat the same calculations" and move on to the next step. What relevant skills do you think are not taught to you?