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How to deal with coauthors who just do a lot of unnecessary work and exploration to be seen as hard-working and grab authorship?
I am a post-bachelor researcher in computational biology.
One of my coauthors is a PhD student. He has many ideas, and is seen as independent, innovative, hardworking, and creative. The problem is most of the stuff that he tried just simply doesn’t make sense. It’s the sort of thing that I don’t even try because I know that it’s going to fail and people are going to ask a lot of questions about it. He proposed a lot of things, tries them, and said that they worked, but when I dig in, he and I can never reproduce his results. When I stated my concerns, the PI was inclined to give the PhD student the benefit of the doubt, and the PhD student insisted everything was fine. And he just kept continuing in this direction further by pursuing and leading a 6-month mini-project which I feel was a huge waste of time.
In the end, the paper was rejected by the reviewers because they were specifically concerned about his ideas and additions. My other colleagues (2 postdocs and 1 master student) also asked questions about his ideas. The PI has finally accepted that these ideas didn't work, and the model is going back to my old model since his additions do not improve the performance at all.
Despite this, he is seen as hard-working and has a lot of ideas, while I am seen as a cynical contrarian. So he was “promoted” to a co-first position and becomes the project leader and I become a third author.
How can I deal with this? I understand he seems to have more ideas and be putting in more effort, but it is a net negative for our group's progress. If they had listened to me, we could have avoided wasting much time and effort working on my colleague's bad ideas. In fact, the delays this has caused have delayed publication, which in turn are delaying my own application to PhD programs (after working in this lab for years, I need some sort of publication to show for it if I am to be competitive).

Did you actually tell anyone, notably the PI, ahead of time that the mini-project would fail? Did you or anyone else tell the PI why the paper was rejected?

@ivicts "In the end, the reviewers said the same thing as me, and my PI started to believe me." Okay, so the situation is settled then? It looks like you (or the situation itself) already dealt with the coauthor. What more are you hoping for?

@MisterMiyagi Before the mini project, the PhD did some "prototype" or quick try and he said it worked better than the baseline. However, I could not reproduce the prototype and he could not reproduce it himself. The baseline is still better. This happens before the mini project, but the PI initially believed him more even when the PhD could not reproduce his own experiment. The PI probably thought I was making things up. However, the PhD still tried to pursue the mini project after the prototype does not even beat the baseline which is a really silly thing. I feel it's a waste of time..

@MisterMiyagi The PI definitely knew why the reviewers rejected the papers as he could also see the reviewers comment in the system. Three out of three reviewers had concerns about some of the PhD's ideas.

If you don't like working with someone and feel the collaboration is not fruitful, then do not work with them.

@Tom Yes, that's the easiest way to do it and my favorite. But, I heard that people say we need to try to work with someone we disagree with or we don't like. So, that's the point of the question. But, in some ways, the PhD is also lying and doing non reproducible research, so it's not only about disagreement, but also crossing ethical boundaries.

I'm not saying this is happening here, but sometimes people over-estimate the extent to which they ''know'' something will not work without trying.  I knew a professor and he said of his best student that he had a tendency to say that something would not work without trying it first, and this is someone that was a good mathematician.  Regarding order of authors, I don't think this especially matters unless you are the lead author or the final author.  Getting annoyed with someone because they got to be ''co-first'' author whereas you ''second co-first'' is probably a waste of time.

I worked in a lab once with someone who would try random pointless stuff which obviously had predictable results and then presented it at lab meetings like they had contributed a lot to impress the clueless PI, so I feel your frustration at the same time.  Just one of those things.

@Tom Yes, I do agree that's what other poster below said. The problem was I have tried a lot of stuff for a year before saying that the model cannot really be improved. And before me, there was another guy also doing the project for a year. We also had manuscript in my first year ready and I thought it's gonna be submitted. The problem is I am not even a cofirst author, I am a second / third author after 3 years of work and the model reverted back to my first year's model. The PhD becomes a cofirst author even when what he tried did not actually improve the model.

@Tom Yes that's precisely what this guy is doing. You know what I mean right? Because some posters below doesn't seem to get what I meant. Then, you just stop collaborating with your labmate? or did you try to find a way to work with him?

@ivicts Yes I know what you mean.  In the end the frustration got too much and I quickly found another job and left. I am not sure what I would have done if I had continued.  I am not saying this is the right thing to do necessarily as I don't know your situation, but I would have just asked to speak to the PI and said I felt that the situation was unfair and explained what was happening.

If it is any consolation I have also had to publish articles in top journals with a co-author on the list of authors who contributed literally nothing.  Although I was annoyed for a while, after a while I just moved on as there was nothing I could do about it.

Note that OP has asked about this situation a few times in the last several months, including here (perfectionist PI) and here (irreproducible results). The latter made it sound like clear research misconduct by the PhD.

@DanielR.Collins Thanks, there are so many moving parts of the whole problems. But, on each question, I try to focus only on one part although the comments are quite unfocused usually.

@Tom Yes, I talked to the PI but the situation also puts the PI into a difficult situation because the PhD is doing more "raw" work even though that the model revert back to the original model. So, this puts the authorship ordering in a grey area because the PhD says that he should be the first author because the first author is determined by the number of exploration not by the "lucky" one who find the working method that is ultimately use in the paper even though I know that his exploration is just plain BS.

@DanielR.Collins seems like the only suggestions that stuck to me is just to stop working with this PhD..

It must be aggravating being more insightful than your advisor.

@a rural reader It certainly is, trust me.

@Aruralreader not to sound arrogant, but some of it comes from trying a lot of stuff and it doesn't work. Then, the PhD tried a similar direction and kept saying that it worked, so I became suspicious. Also, I am the one who does the experiment, if the PhD says something worked, then I can try that idea as well on my code, and sometimes it doesn't align with what he said. The PI won't do this and he just takes everything that the PhD said at face value. Of course, no one assumes that the PhD was misleading before.

FWIW, this all sounds like the underlying issue for the concrete situation is sloppy culture in the group. There are groups in which "it works and is better" is just a throwaway verbal statement, and those in which it is a proper (albeit informal) presentation including hard numbers and/or plots. The latter is much more difficult to fake and get away with.

@MisterMiyagi Actually, there's another detail. So, my PI doesn't want to give us the label for the test set, so that the model can generalize more. It's like a kaggle competition. The PhD kept having better numbers on some metrics on the test set although his validation set is not better than mine. It turns out that his test set is actually easier than mine. The same exact model has a 20% improvement in one metric just by training and testing it on his dataset. So, we are not comparing apple to apple on the test set.

@MisterMiyagi but, if we compare apple to apple on the same dataset, his idea doesn't improve the baseline. The problem is the PhD knows that the dataset was different (I confronted him and he slipped up) because he's the one generating the dataset, but he denied and bluffed it when my PI asked us to check all assumptions. Also, in the end, the PhD also cannot show that what he does improve from the baseline using a hard number, then the idea was discarded after the paper is rejected.

Here's my perspective as a PI. A graduate student or postdoc who is intrinsically curios and wants to explore different avenues, even ones that are potentially low reward because they go against some accepted norms is really great. You never know when you will stumble on a paradigm shifting result. There are many "accepted" ideas out there that are simply wrong, or biased, or based on very limited parameter scope, and some more checking and exploration can open up new areas of research. With experience and maturity, this curiosity will coalesce with their deeper understanding of the science, and build intuition which will focus this exploration.
You choose to view this as "playing the game"... I guess if the game is to perform discovery driven research, then yes, that is "the game". If you think that this is to "look busy" to garner favoritism from a PI, then that is already a significant negative bias on your part.
As for ideas being rejected by a reviewer? Any time you propose something non-standard it will be questioned. Sometimes the reviewer is right, sometimes the reviewer is wrong. That does not make the idea intrinsically wrong, it just may mean it is not ready for publication. Ultimately, this is peer review doing its job. It is flagging something that is either potentially wrong, or needs more proof to be accepted. Most definitely, this is not the sign that one should just stick to established protocol, because that will just lead to mediocre science that doesn't move forward.
It is clear that this is upsetting you, and likely bringing up feelings of envy, but you have to understand that those feelings are on you. So how can you deal with such a person? You can either learn to work with them and put their strengths to use, or you can stop working with them because you see a significant incompatibility. Just be aware, if you pursue a career in research, you will always come up against scenarios where seemingly less "deserving" or "intellectual" colleagues will garner more attention or praise than you. Learn to work through those feelings because they are ultimately self-destructive.

I cannot reproduce his result on the initial direction and he also could not reproduce his result. I kept asking him his code and he didn't want to give me his code. The PI initially believed him because he's hard working and he lets him to do the mini project. I mean, he could not reproduce his own result.. why would he continue in this direction? I feel that the "hard working" is just done to "look busy". The paper was rejected by the reviewers and in the end this idea was discarded because it's not reproducible, doesn't make sense biologically, and doesn't improve the performance.

How can I work with them? I mean if I try all the ideas that come up into my head even when I know that it will not work, I will be "hard-working" and have "a lot of ideas" too. But, if I know it's not gonna work, then it's a waste of time, right? It's gonna be an issue in authorship because he will do a lot of stuff, but in the end, he's also showing that the model cannot be improved which is the same conclusion as what I said 2 years before, so 2 years are wasted... Then, I also need to try things and explore things that I know it's not gonna work just to maintain my authorship.

So you mean, that in the context of research people tried several ideas, then concluded that one of the original ones was better. I've never heard of such tomfoolery. This is certainly not how things are done. It is best to find one idea that works and never explore anything again because there may be a risk that the old idea was indeed better, and that is a risk nobody should ever take. Everyone knows that the cornerstone of research is find one thing that works and never try anything new again.

The problem is the PhD never told us that his idea is not working, he kept saying what he's done is better and did a mini project pursuing that direction further. Yes, there's a risk for everything, but we need to try small stuff and fail fast right? It feels like the PhD didn't tell us this, spend two years and in the end revert back to the original thing. I guess when I have a collaborator pursuing one direction, usually when it doesn't work, they say it doesn't work. This is not what happens with the PhD, we only revert back to the original idea after the reviewer rejected the papers.

Also, I know that exploring thing is good, but sometimes we need to stop and start submitting the papers right? Otherwise, the project will go on and on forever and we never submit the paper. Sometimes, we cannot try everything, and we need to have a deadline to submit the paper. Yes, we work hard, but we need to work smart as well? For the context, the project runs for four years and hasn't been published yet.

If there's a researcher whose approach is perennially nonproductive and you disagree with them, the answer is -- Stop working with them.
In the OP's current case, working for years as a post-bachelor's lab assistant, under a nonproductive PhD student, under a faculty PI: You can just leave today. It sounds like it's not being profitable. A paper with your name on it is not even a requirement to enter graduate school (in my experience and awareness). Just go apply to graduate school now if that's your goal.
Obviously you don't waste time futzing with approaches you know won't work in advance, so as to appear busy. That's a complete non-starter.

The problem is he's seen as "productive" and "hardworking" instead and sometimes he really is hardworking (without the quotation). I feel that what he does is a grey area to be honest because it makes his colleague look bad by keep saying things are working when it's not.

I feel that no publications after 4 years of research puts me in a very difficult situation because people will wonder why I don't have publication after years of work even when I have no say (as someone said I am in the bottom of the pole) when the paper is gonna be submitted. So, it becomes a liability on my application and I am just stuck. I applied for a PhD on my second year, but didn't get in and waiting for the paper to be published, but it never gets submitted.. so even to leave from this situation, I need publications. otherwise I am in a dead end in my academic career..

@ivicts The real solution would have been to not put 4 years into this situation before doing something else. Even perfect advice now can't get you that time back or help you compete with someone who was productive in publications over their last 4 years who is applying to the same PhD program. If you can't get into a PhD program (did you apply broadly, or only to a couple institutions?) then you can pursue a non-academic career, which is the same place that most people who complete a PhD will be once they've finished.

@BryanKrause hindsight is 20/20. During my first four months here, my PI said that we were gonna submit the paper "soon". Then, at the end of the first year, I told him that the model was saturated and very hard to improve, and then he added the PhD student probably thinking that I was lazy. And after two years of trying this and that and the paper got rejected, we reverted back to the similar original model. The problem here is my PI is really a perfectionist as well. When you said "before doing something else", what does this something else entails for example?

@BryanKrause now I am trying to get into another postbac researcher experience with another PI and get publications from that, then see how...

@ivicts Yes, hindsight is 20/20, but you had opportunities for some partial hindsight before it got to 4 years. "Something else"s might be a different project or different advisor.

@BryanKrause Yes, I have asked new project since last year, but I am afraid of the new project becoming 2 - 3 years project again. Most PhDs in our lab only have one first author when they graduate and most extend by one semester or a postdoc, that's the baseline. Also, I have partial hindsight, but I also want to keep my authorship position, knowing that if I change to another projetct, I will get lower authorship position on this project. But, in the end, I got lower anyway because of the PhD.

@BryanKrause Actually I planned to ask the PI for a new project where I can be a first author after this project is ending, but this project is never ending, so that's the problem. In the end, I got a new project last year after I hinted very strongly I want to move on from this project. Otherwise, without hinting, my PI keeps wanting me to do this project. He really likes this project and keep pouring a lot of resources and manpower to this project. At least, I know that I should not do a PhD with my PI, he's very nice, but what he does put people's career in a difficult situation.

Now that it's been 4 years I don't think a new project is the right way to go anymore. When you're on a dead end project and the PI won't let you do anything else it's time for a new PI.

@BryanKrause I guess the PI sees trying stuff and exploring stuff as being hardworking which sometimes I agree, but there should be a deadline to it, otherwise we won't have papers and everyone's burning out. He targets high-impact journals though, like IF 30 or something. Should I tell my PI that 'these days I am concerned with my careers and that I have no publications after 4 years and my best contribution is just a third-author paper? Of course, in a nonblaming way. Or maybe I should not do that and keep trying to find a new PI on my own?

@ivicts I think that would have been a good conversation to start having 4 years ago, and better late than never, but I'd question the wisdom of putting substantially more time into a place that hasn't been productive for you over that time frame. As far as exploring and being hardworking, I do think that if your primary role in the group is showing that other people in the group's work doesn't actually work, it's not surprising you don't have any publications.

Not saying that's not a noble effort and important for science, it's just not something you get documented credit for and shouldn't be your sole activity.

@BryanKrause To be honest, I agree with what you meant, I might go too extreme on that front. I feel that this is the fault of both me and the PhD. If the PhD is a normal collaborator, he would say himself that the things he tried don't work and won't add a lot of stuff to the model. He said that it worked, but I couldn't show that it worked on my code so it becomes me trying to prove that he's wrong. If he acknowledges it himself, we could just debug this together. I don't know what should I do though, should I just get along knowing he added a lot of stuff that doesn't work?

@BryanKrause if I just get along and wait for the paper to be rejected by the reviewers, I would probably get a co-first author by now. On the other hand, I don't want to spend so much time on a paper that I know it's going to be rejected anyway, so I became quite critical about it (it's my fault, I know). I guess the moral of the story is relationships are sometimes more important than being right? Yes, also in my group, there is a PhD who continues to be a postdoc and she hasn't submitted her paper after 5 years of work, so the problem is not only my problem (I know it sounds like excuses).

@BryanKrause I also guess that it became my focus because the PhD denied what I said, so the PI didn't believe me instead and it impacted my credibility as the PI kept cutting me off or mad when I said something didn't work or that the dataset is not consistent. So, it forces me to prove the PhD wrong to gain back my credibility which in turn alienates the PhD as I prove him wrong. Not sure how it can go differently though.

@ivicts Sometimes you have to make your case and move on. If you know a project is broken and the people in charge of it are stubborn about it then it's better to cut your losses and ask to be off the project. You don't need to prove the PhD student wrong, if their work can't be reproduced it's up to them to create reproducible code that demonstrates their result. Proving something can't work is always harder than proving it can.

I think why people are arguing with you is because you have set up an extreme choice and seem to have no sympathy for either the other student or the professor. You seem to be assuming malice rather than incompetence, which is far more likely.
Some of the things you learn as you go along in your career are :

sometimes students are not telling the full truth. It seems like the PI was taken in by the PhD student. That is a lesson, but hardly surprising, given that they probably work mostly on separate things.

how to filter ideas/when to stop pursuing an idea. It is good to pursue new ideas, but there are 2 day ideas, 2 week ideas, and 2 month ideas. You do have to construct check points and ignore the sunk cost fallacy.

not to put all your eggs in one basket.

From your comments, you seem to think you were at the mercy of this other student, and that is why you are so mad. It seems you sat by and waited for the other student (correct me if wrong), yielding 4 years with no paper. But, you did have options. You could have chosen to talk to the PI to get other ideas/projects to fill that time. It is best to learn how to have multiple irons in the fire.

"I think why people are arguing with you is because you have set up an extreme choice and seem to have no sympathy for either the other student or the professor." Can you please elaborate more on this? What can I improve on this? I agree with some of the posters that it is important to explore, but as you said there should be a deadline and we should filter ideas otherwise we will never submit a paper. Honestly, all the three points seem to be learning points for my PI instead of me. I agree with all your three points. Actually, it's the PI, not the student, who don't want to submit the paper.

I waited for the PI to submit the paper, and he kept saying we gonna submit "soon" but never submitted it. Instead, he added this new PhD student instead who promises an improvement when it's not really reproducible. Actually I planned to ask the PI for a new project where I can be a first author after this project is ending, but this project is never ending, so that's the problem. Otherwise, if I have multiple projects at the same time, I could not maintain my authorship position. In the end, I got a new project last year after I hinted very strongly I want to move on from this project.

Otherwise, without hinting, my PI keeps wanting me to do this project. He really likes this project and keep pouring a lot of resources and manpower to this project. Btw, just to have a baseline, most PhDs in our group extend by 1 semester or even some doing a postdoc and graduate with only one first author paper. We are in comp bio + cancer biology lab, so that's the baseline.

I think you are assuming malice and subterfuge rather than natural human incompetence… and we all think slight incompetence is the most likely root of the issue.

If the PhD is honest and incompetent, he would tried a lot of stuff and just say that what he tried doesn't work and discarded it like other normal collaborators do. The problem is he kept saying that it worked, adding a lot of stuff to the models, and got us rejected for no reason because his addition does not even improve the performance in the first place. So, I feel that the whole thing is done just to show off, take credit and grab authorship.

Note that in the prior question by the OP, the description there had all respondents pretty convinced that research malfeasance was occurring.

@DanielR.Collins okay, that is helpful. But based on this question alone I stand by this answer - what we have here is a PhD candidate trying a lot of things and a PI letting them and a rant by a BA student saying he is getting screwed over by not “playing the game” like these scheming others.

@Dawn Yes, the PI is hands off so he doesn't know that what the PhD doing is working. He's generally happy that the PhD does a lot of  things. Although he was mad when the PhD couldn't reproduce his result, saying "What you show here is the same as what ivicts is showing right? (Phd name) we can try a lot of stuff, but it must be logical, okay?" and then he stormed out the room. But, at that time, he believed the PhD so he was mad at me instead and excluded me.

@Dawn Other times, my PI also says that "Last time we did this mini project, we thought it's working, but in the end, you also couldn't show that it beats the baseline right?". Another time, when one of my colleagues pointed the idea doesn't make sense, he said "No, it doesn't make sense. You (the PhD) just fit a noise okay?" Also, I am not a PhD but I worked on this project one year before he came in and the reviewers agree with what I said. But, yeah, the PI generally happy the PhD is "hardworking".

@Dawn Also, the PI is letting the PhD explore things because he thought what the PhD tried is working, but in the end all the things that he tried didn't improve over the baseline.

Sure, it sounds like the PI has stuff to learn to better manage such things. They are probably annoyed too. You should probably apply to PhD programs now to get out of there.

@Dawn I guess it's hard to know this stuff from the PI's perspective because the PhD is also misleading and my PI is hands off. I know a lot of this BS because I am also doing the experiment myself, so if the PhD says something works, I usually try it on my code to see if it also improves my model. Then, my experiment generally doesn't agree with him. Of course, I trust my experiment/numbers more.. so I become suspicious of him..

Yes. You should ask the PI if they would write you a strong letter. Communicate what you think your strengths are. If you apply widely you may be able to do well with a good letter and a good manuscript ready for submission. Although it has been many years, my husband got into a great program with a great letter and no publications.

@Dawn thanks, usually strong letters correlate with publications. Sometimes I wonder if I do research for 4 years with no publication whether I am cut out for a PhD or whether I should just go to industry. Did your husband do it right after undergraduate? I feel that no publications work when you apply right after your undergraduate, if I do research for several years and have no publications, it becomes a red flag instead...

What you describe is not unique to academia. In an ideal world, technical correctness would win every time, but in the real world people are fallible, politics is real, and you can definitely find yourself being sidelined for being the cynical voice of reason, even after your predictions come true again and again. It can be extremely frustrating, but it’s part of life. There are some strategies you can learn to deal with this sort of situation.
First, realize that you aren’t always right, even if you often are. Not saying you’re wrong in the situation you presented, just good to keep in mind going forward. If you’re pretty good at analyzing situations and calling out faulty reasoning, don’t fall into the trap of assuming you will be right all the time—you won’t.
Second, realize that everyone makes mistakes, everyone has strengths and weaknesses, so don’t assume malice without strong evidence that can’t be better explained by incompetence or a simple mistake.
Third, accept that politics is real and necessary to succeeding in the workplace. This doesn’t mean acting dishonestly or otherwise unethically, but it does mean being aware of and cultivating your professional image both outside and inside your team and being aware of the motivators of those on your team, especially your boss. In terms of motivators, a professor generally has significantly more motivation to help a PhD candidate succeed than to help an undergraduate researcher succeed. This may well explain some or all of what you’re experiencing, and it may be unavoidable as long as you remain an undergraduate researcher.
Learning workplace politics also means knowing when to keep your mouth shut, realizing that sometimes being the prophet of doom, no matter how accurate your prognostications may be, will make people not like you. It’s often better to let people try something and fail (as long as it won’t harm someone) than to be seen as a naysayer. There’s a time and place for naysaying, but it can be overdone. Also the lower your rank on a team, the lower view your superiors (in rank) will likely have of your naysaying even if it’s right. This unfortunately can come down to ego—the professor may have trouble admitting to themselves that an undergrad was right and they were wrong. It can also just be based on honestly reasonable assumptions: “I’m a professor with years and years of experience. They’re an undergrad who is totally green. It’s much more likely that I’m right.”
Fourth, realize that there are better and worse teams to work on. Resist the temptation to chase the perfect team because it doesn’t exist, but at the same time remember that you can leave a team if it’s just not working for you and your career goals.

Actually, this advice is spot on. Something that I keep reflecting on myself about the whole situation. I guess my fault in this case is that I became critical & belligerent about the issues that I perceived and I became the naysayers and then got excluded from the team. Although my view was validated by the reviewers, I feel that if I just got along, then I would be a co-first author by now. What should I do actually? Should I just get along even when I know that the ideas don't make sense?

Also, to be fair, "letting people try something and fail" may not work in this case because the PhD kept saying what he did was working until the paper got rejected. Then, I need to give a hard number basically proving that the PhD is wrong/misleading and it alienates him. Also, on another hand, in my first year, I kept saying the model was saturated, and my PI didn't believe me and he added the PhD student instead. After two years, we revert back to the original model. So, letting people fail can take 2 years of work..

Also, before the PI submitted the paper, I kept telling him that this paper going to be rejected because the reviewers going to ask a lot of questions about the PhD's ideas. He submitted it anyway and the reviewers did reject the paper because of it. Afterward, I didn't really want to help the group anymore because I felt that I was never being heard and I didn't want to help people who didn't want to be helped. Is this the correct way to react? Or I am not reacting professionally? Should I just help them after they fail?

Yes, I like working in this group and my PI is very nice, but it puts me in a difficult situation in my career if I don't have publications. I am just stuck without publications.

Also, in this case, it did harm someone because the paper got rejected.. when it doesn't need to be rejected because we can just take out all the PhD's additions without any decrease in performance. But, the PhD was stubborn enough so he didn't want to do it and kept pushing it for submission.

"I became critical & belligerent about the issues that I perceived and I became the naysayers and then got excluded from the team. Although my view was validated by the reviewers, I feel that if I just got along..." these are false dichotomy. You can still be critical but not simply following along, though I agree that it is much harder to do. It's what people usually call being diplomatic or street smart.

By harm I mean physical harm or significant harm of any other kind. Not getting a paper published wouldn’t check that box IMO. Someone losing their job might (I say might b/c sometimes you can’t stop someone from walking off a career cliff).  A whole team losing their jobs would be a significant harm and worth significant naysaying, though even there there’s a time say “I’m not the boss, they are” and accept that the responsibility for success or failure lies with them and you can’t change their mind if they’re unwilling to let it be changed.

If your only option is between naysaying so often you get sidelined, and watching your career get sidelined, then my point number four may come into play. That may be the case here. Your university may differ but from my memory there’s very little incentive for a professor to ever prioritize an undergraduate researcher’s advancement over or even on par with a PhD’s advancement. So you’re automatically going to be quite low in the pecking order no matter how amazing a job you do. It may simply be time to go to grad school. As others said you don’t usually need publications to do so.

Also sometimes you can help the truth of your predictions become evident faster by helping speed the work along, though this doesn’t always work (sometimes you’re strong armed away from the tasks that would let you do this) and it can be risky b/c you could set yourself up to be a convenient scape goat if you turn out to be right. Knowing how to navigate this type of situation is a skill that comes with practice. And like I said, sometimes you can help fix it, sometimes you can’t and you either keep your head down or move on.

One final thing I may add to my answer: take a look at how you’re communicating and maybe read up on learning how to speak persuasively, especially to people who have authority over you. It’s a difficult skill to learn but very important and it may also be in play here. You may be communicating the information accurately but not persuasively. Note that some people will not be persuaded no matter what and I’m not saying that’s your fault. But there is a skill that can be learned to at least improve your odds of success when communicating.

@justhalf "You can still be critical but not simply following along" Can you please tell me how concretely what I should do in this case, especially with someone with little power? If they want to finalize the model that doesn't make sense, then I need to use the model, right? I needed to help write the manuscript, create figures, benchmark for something pointless that I knew going to be rejected and it did get rejected and they rewrote all the stuff after discarding the PhD's additions. So, it's wasting my time as well.

@justhalf I can be diplomatically critical, but in the end, I need to follow along.. Also, besides me, two postdocs, and a master's student also questioned the PhD ideas, and the PI diplomatically asked the PhD to confirm whether it worked. The PhD said, "Yes, it worked". Then, I tried the idea myself on my code and it didn't work. So, a diplomatic way (even not from me) may not work with the PhD.

@bob so basically you are saying that I should get along even when I know they are objectively wrong and wait until the paper gets rejected by the reviewer and then propose a better idea, is it?  Also, what I did was not naysaying before the ideas are tried, but I tried the ideas myself and it didn't work on my code and the PhD also could not reproduce his own result which was known before the submission. And the PhD is still pushing for submission. I guess I care too much about this project, if they want to submit it that way, I should just get along and go that way until it gets rejected.

@bob that's true as well, I could help speed the work until it gets rejected, which would take another year, but I might get my cofirst author. I am just the kind of person who cannot be a "loyal soldier" who can do something that I know is objectively not correct, especially since we are doing science. But, it is an opportunity cost to work on a project that I know is going to fail when I can work on another project that might be successful.

@bob Yeah I agree that I don't communicate correctly and diplomatically as well so I alienate people. I guess I became too much of a contrarian then when the PhD lied saying that things worked when they didn't, my PI believed him instead because I was too critical generally. So, that was my fault as well.

@bob I feel that no publications work when you apply right after your undergraduate, if I do research for several years and have no publications, it becomes a red flag instead...

Let us continue this discussion in chat.


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From a lesser known uni, but very prestigious in my country - do I tell my referee to make this clear in my LOR for USA applications?
I'm applying to the US and Canada for PhDs this cycle, my undergraduate university is very well regarded in my country (UK) and generally in the top 5 for domestic rankings/prestige. Even more so for my undergrad program (Physics), which generally accepts people who very narrowly missed out on Oxford/Cambridge places. However is pretty much unheard of outside of Britain (ranked in the 60s/70s globally). Do I ask my referees to make the relative prestige of my uni clear on my LOR so that admissions committees can understand the context of my grades and experiences?? Or would this be considered too on the nose?
I am preparing to send materials to all of my referees with some advice on how to write LORs for North American applications, which they may not have done before, so I would really like to clarify this before I do so.

A top 5 UK university, which is well regarded within your field and top 100 in the world is very unlikely to be unknown to people in the field, even at a university not in the UK. Also, why do you assume your letter writers have never written for an American university before? Unless they are very new to writing letters, that too is quite unlikely.

I guess to clarify I'm applying for programs outside of my field, in computer science. However my doubt basically stems from discussions with my final year project supervisor, a professor in the department, who expressed inexperience in dealing with non-UK graduate applications.

"I am preparing to send of materials to all of my referees with some advice on how to write LORs [...]". I would urge you to think long and hard about this idea, and if possible avoid doing it altogether. Your LOR writers will almost surely not appreciate this coming from you, and your estimation of how much they need it is almost certainly way off the mark. Even in the extreme case of a new faculty member who has no LOR writing experience, they surely know their own limitations quite well and know how and where to obtain the necessary advice themselves.

@DanRomik, thanks for your response. I guess the major concern for me is ensuring that my qualifications or references are not dismissed by admissions tutors at top programs if they don't recognise my university. I will bear this in mind when applying.

The UK has some of the most highly respected universities in the world, yet you write as if it's some kind of third-world backwater.

@David: I heartily agree with your first clause; with regard to the second, I think the OP's mistake is not to realize the extent to which academics spend a lifetime acquiring information about academia.  I am at a university that no one would ever claim is in the top 100 in the world, but nevertheless my department (mathematics) is known and respected by many European mathematicians.

@DanRomik, disagree completely. Even esteemed scholars need guidance on how to write letters, and most of them appreciate this: it just makes their work simpler. Of course there may be some exceptions.

First of all, it is a tough position to be in as a student to have to give faculty advice on how to write your graduate school letter of recommendation.  To give them too much guidance may not be appropriate, and as someone who has not yet completed a PhD program or read or written any such letters, you almost certainly don't have the expertise do properly advise them either.  Thus I would urge you rather to seek out writers who have previous experience writing letters to North American universities.  One of the most important qualities of a top world university is that they regularly place their students at other top world universities, so (as @Tobias Kildetoft has pointed out in comment) I would expect there to be many faculty members in your department who have experience writing such letters.  I think it is much less awkward to try to choose letter writers based on this expertise than to try to give your letter writers letter writing advice.
But assuming the premise of the proposal: it is not clear to me exactly what information you are hoping to provide.  The world's top hundred universities are largely well known to each other, and moreover it is the responsibility of those who are evaluating your application to know or learn enough about your university in order to perform that evaluation.  When I do graduate admissions and get an application from an institution that I am not familiar with, I do spend time familiarizing myself with it.
In terms of rankings: Times Higher Education [a London based magazine] places twelve UK universities within the world's top hundred: Oxford (1), Cambridge (4), Imperial (8), University College London (15), London School of Economics (25), Edinburgh (27), King's College (36), Manchester (55), Bristol (71), Warwick (82), Glasgow (88), Durham (96).  It is reasonable to expect a reputable North American PhD program to have heard of all of these institutions.    Individual faculty members will also have their own opinions on the relative merits: for instance, in terms of the kind of mathematics that I do, I view Bristol as being very strong, perhaps at about the same level as Imperial.
If the faculty who process graduate admission do not agree that your institution is one of the world's most prestigious, simply pointing out that it is one of the top ones in the UK according to some metric may not change their mind.  They should instead offer concrete evidence of the excellence of their program, e.g. by talking about world-leading faculty members and former students who have been placed in other top institutions.

Thanks for your response, I will bear this advice in mind. This question probably stems from my naivety, however my main concern was ensuring that my qualifications were recognised as an international applicant and was worried that my application would be dismissed by top programs as if they didn't know the context of my experiences.

If you look specifically at Physics rankings, this https://www.thecompleteuniversityguide.co.uk/league-tables/rankings?s=physics%20%26%20astronomy has a somewhat different top 5. No surprise that Oxford Cambridge and Imperial College London are in there, but the other two are St Andrews (in Scotland) and Durham. I don't know whether to believe these scores but I could certainly believe that St Andrews was not particularly well known (except for its golf courses!) outside the UK.

@alephzero: I was a bit surprised not to see St Andrews in the THE top 100.  It does appear highly in some other lists.  And for what it's worth, I think of it as an excellent institution.  Still, if I read a letter saying "Actually St Andrews is considered by some reputable sources to be in the top five of UK physics programs," as an admissions faculty member I don't know quite what to do with that -- I need help translating that into the sort of tiers I usually think about.  (Also: great undergraduate program in X in a less great university is easier to sell to most nations than to the US.)

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Can I use published data to do my analyses and publish?
Nowadays, there were many data published online and with papers, such as PLoS journal. I am wondering can I use those data to perform my analysis and if so, do I need permission of those authors to publish my results? Thanks.
Edits: The data I am trying to use is the supplementary data that provided by the article. The field I am working on is epidemiology. All comments are appreciated.

The analysis will be on what? The published results on article or supplementary data provided by them?

What field are you talking about? For example, political science data is mostly public and you can use it, provided you acknowledge the source.

Maybe also have a look at https://academia.stackexchange.com/questions/89624/is-it-ok-to-extract-datasets-from-somebodys-paper-and-work-with-it-in-your-own/89625

The whole meta-analysis field would collapse if data extraction from published sources was not allowed, was restricted, or required permissions to be sought from the copyright holder.
It is also important that data cannot be copyrighted. Copyright is restricted to expressive and creative outputs, not measurements. So, if you are drawing from a raw data source, you do not have to ask permission. It is however standard practise to acknowledge the source of the data, which gives credit to the original gatherers of the data and lets those that read your output know where you got the data.
Note, it is possible to get a doi for your data when you post it on platforms such as figshare or zenodo. If the original authors have done so, then cite the data source, not the paper accompanying paper (unless you also refer to the outcome of the work).

The data published in most journals/repositories have licenses - as published articles have. So you have to check individually what the license of the data you want to use allows and what it doen't.

@BenCrowell Your answer concentrates on extracing data from an article, what is in fact not prohibited by copyright. But when we're talking about published data, like datasets published as supplementary data in a journal or in a repository, e.g. in Zenodo, one can add a license to the data. Example: http://doi.org/10.5281/zenodo.495610

If you want to use a data, you should ask the publisher to get the agreement of use it. This is the same as any figure that you want to use. You should ask for permission because some journals does not give that permission even it is published.

I don't think wrong because this is one of the academic ethics. It is published and u can use it but written licences is important to show to some Journals. I used one figure for drilling machine from a journal and the editors asked for permission to use this picture. It depends on Journal and we cannot judge if wrong or right

I cannot say copyrights law because it is difference from one journal to other. Therefore, I think it is good to say ethics of the author to have permissions of his paper figures, data, etc... to be ready for any circumstances.

Published data is public. This is essential to the proper functioning of science. Others can examine and re-analyze the data, challenge existing interpretations, and test new theories.
It is nice to let the authors know that you would like to analyze their data, and to show them the results for comment before submitting a paper, but it is not required (formally, or by academic custom) that you do so. The only non-negotiable requirement is that you properly cite the source of the data.
It is indeed a sign of progress that more studies make their data available in easy-to-use formats. I remember the days when we xeroxed plots on graph paper in order to extract numerical data.

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How do I refuse to work on military-focused contracts?
I'm applying to programs in Computer Science and Robotics and would feel very uncomfortable working on defense-focused or funded projects.
Is it unrealistic (in terms of funding opportunities) to refuse to work on such projects?
If not, at what point in application/admission does it make sense to make this expectation clear?

Are you applying for a master's or Ph.D program? Only in the USA?

@mkennedy Applying to both, more interested in PhD

This answer is for the US, based on my experience with US admissions.
I would say that this is generally not an applications/admissions question, only because it's unlikely to be meaningful to admissions committees. Many graduate departments in computer science work on a cohort-admissions model, where a group of students are admitted each year and then are expected to find a faculty adviser once accepted. In this model it is up to you to find a research program that personally motivates you and then to persuade an adviser to take you on. It is at this stage that you would (and should) make it clear to a potential adviser that you're not willing to work on defense related projects. However, at this point it's probably moot because you're going to be talking to potential advisers based on your perceived compatibility.
What might be a better thing to do during the application process is to ask whether a candidate department conducts any defense related research. Then you can just not apply to defense-related organizations rather than make it a point of contention with programs that you're interested in. Additionally, most CS research is not defense related, and most all broad-based research departments will have plenty of research opportunities that are not defense projects. Consider that about 60% of US PhD students in Computer Science are foreign nationals and ineligible for this kind of work anyway. You will have no problem finding non-military projects to work on.
Some places are well-known as defense-related institutions- for example the MIT Lincoln Laboratory, the Naval Research Laboratory, or the Johns Hopkins Applied Physics Laboratory. It is usually obvious from these organization's websites that this is a focus of theirs, and you can just avoid them. However, if you wanted to apply to a place such as this I would definitely discuss your personal ethics eariler rather than later, and your ethics definitely don't disqualify you. These labs do a lot of research that is "defense-related" in the sense that it provides for the common defense of the country, not because it's a military project. They work on everything from actual weapons systems to civil defense projects like weather satellites, making the energy grid more robust, and information security.

Consider that about 60% of US PhD students in Computer Science are foreign nationals and ineligible for this kind of work anyway. Foreign nationals are not necessarily ineligible to work on defense-funded research. It depends on the specific project, and a lot of them have no such constraint.

@ff524 Yes, that's true in general. My statement is based on the loose assumption that the technologies that the questioner wants to avoid are roughly encompassed on the ITAR export control list and that many foreign nationals in CS are from China (which is a prohibited country under ITAR). We have tremendous numbers of such students, and they have no problems finding research projects they're able to work on.

That seems like an unfounded assumption. The OP said "defense-focused or funded projects", which are not necessarily export controlled.  (For example, some foreign students in my research group are working on an Army-funded wireless networks project which has no such restrictions.)

@ff524 I am betting that, despite what they said, OP doesn't intend to exclude all defense funding, just "military projects". Anything that would fall under the "Fundamental Research" exception of ITAR is not going to be a project that OP will have an ethical issue with. Most people not familiar with the research enterprise are not going to realize that DARPA and the DOD sponsor basic research. Regardless of what OP's mind is on this, our discussion should sufficiently illuminate it for them.

I'm sorry, but this is not accurate, "Additionally, most CS research is not defense related, and most all broad-based research departments will have plenty of research opportunities that are not defense projects." I have spent the last 3 years of my life submitting more than a hundred federal applications for more than 30 CS faculty at a top US university. DOD is becoming the norm. Unless your PI does only very strict theory, expect DOD in their portfolio.  DARPA is even expanding into hospitals. My faculty always say, "NSF stands for 'Not Sufficiently Funded.'" It's not actually a joke.

Also not accurate: "Consider that about 60% of US PhD students in Computer Science are foreign nationals and ineligible for this kind of work anyway." Foreign people can work on DOD grants. There could be some restrictions, but nothing like 60%.  DARPA often has an e-verify clause in the contract.

Ben Kuipers, a Michigan faculty member that does not take military money, has some advice on this topic in "Why don't I take military funding?":

...there are plenty of options for supporting yourself through graduate school without military funding. You can be a teaching assistant; you can be a research assistant to a faculty member with other kinds of funding; you can find work maintaining computers for a lab in another department; you can get a part-time outside job; and so on. Generally, rejecting the single largest funder will require you to be more creative about looking at other funding possibilities. This creativity will serve you well. One of the fortunate things about working in computer science is that you have a practical skill that is needed by people in many different areas, and they are often willing to pay for your services....
On finding faculty with similar beliefs, I would suggest just asking. A quick scan of each faculty member's web page, and especially the acknowledgements on publications, will tell you where they get their funding. Find a few people whose research you find attractive who have non-military funding, and talk to them.
Personally, I find it most productive to be clear and straight-forward, without being judgmental or confrontational. You will very likely find plenty of people who are very sympathetic to your values, but who aren't willing to make what they perceive as too large a sacrifice. In my personal opinion, it is more important to encourage people to see their choice of work, how it's funded, and what it's used for as an important moral decision that must reflect their own fundamental values, than to pressure them to make the same moral decisions that I have.

You may lose a position, but be open about not wanting to work for defense-oriented projects. Don't hide it, you do not gain anything by that (as mentioned above in the comments). Some people may not want to work with a "picky" person, anyway, so you do not lose anything, but it is better than unsaid suspicions about why you would not get clearance.
Some bosses may have understanding and offer you non-defense-based contracts, but you need to decide beforehand whether you are happy to work in a group with mixed funding sources, where, while you won't, others may be funded by defense contracts. Some academics will welcome your attitude. It is an idea to check on the websites of your prospective employers for hints of whether the funding sources are mixed, or whether the academics possibly even explicitly avoid defense funding.

Not just on their websites - look at the Acknowledgements section of recent papers they wrote to see where their grant funding usually comes from.

@ff524 Yes, good point.

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Should an advisor care if their student becomes overweight?
So your student is becoming overweight: does this negatively impact your research group in some way? Should an advisor care?

How can being overweight have any impact on a research group? And what about overweight advisors? As an advisor, the only concern I might have is about the health of my advisees.

I think the flippant answers to this question are really disrespectful and inappropriate.  People, especially women, are often judged on their weight, and I think this is a legitimate concern that should not be so lightly dismissed.

This generally shouldn't be an issue.  One area where it might matter is if the graduate student is doing field work that requires a lot of physical activity (climbing mountains, rappelling down cliff faces, etc.)

It is not your advisor's responsibility to keep track whether you cut your nails, had a haircut, shaved your beard, payed your utility bills, feed your cat or done other irrelevant things.

I disagree with closing this as "primarily opinion based". It's not asking for opinions on overweight students: it's asking whether advisors in general have opinions on overweight students.

@DavidRicherby so basically the question is asking for opinions whether advisors have opinions on overweight students. And in my opinion this is opinion based.

"Are most" is opinion unless someone has done a study on this topic. "Should" would be a better question for Stack Exchange (or perhaps "how should"); still largely opinion but at least it's clearly looking for practical advice.

@SalvadorDali No, it's asking for information on whether advisors have opinions.

Attempted a rewrite into answerable form, hopefully preserving the original poster's intent.

I think it would help the quality of the question and the answers, if you name some reasons why an advise should be concerned. Do you think it is a sign of depression or poor health condition? Or something else?

@keshlam I rolled back your edit because it seemed to me that it might significantly change the tone of the question, and there is a strong preference for retaining OP intent where possible; I would prefer if the OP decided whether to follow through with your suggested edit or not.

In some circumstances, being obese puts a student in a protected class, and harassment related to the obesity constitutes discrimination.  You could talk to the student disability office in your university about this.

@jakebeal to be honest, I see both genders being judged equally as harshly on their weight, not just women. Though I may be going off topic here.

Becoming overweight is not an issue per se.  Major physical changes, however, are often a sign of an major ongoing mental or physical health event.  Rapid weight gain, for example, is often associated with depression or thyroid problems, both of which can have a major impact on the student's ability to learn and work.
As such, I would definitely be concerned if a student was visibly gaining a large amount of weight---not because of attractiveness or disapproval of weight, but because of what else it might indicate.
I would find it highly inappropriate, however, to bring this up with the student by saying something like "I've noticed you've gained a lot of weight" because there are also a lot of more benign reasons somebody might gain weight, including recovering from mental or physical health problems that would also be none of my business.
I would, however, notice it as a possible red flag, and start to keep a more careful eye out for other signs of distress, which might legitimately trigger a conversation about, for example, mental health.

I actually laughed pretty hard at the statement "I've noticed you've gained a lot of weight"...

The impact on the student's ability to learn and work notwithstanding, becoming overweight is a health problem which affects multiple other aspects of the student's life. If the environment in a research group is affecting students' health it is definitely something the PI should be concerned about, regardless of whether this affects their performance within the group.

I would add that it depends on the general way how the supervisor approaches people around him. We have a professor here who is quite caring about other people. It wouldn't be surprising to me if she cared a lot about someone gaining weight quickly.

"Major physical changes, however, are often a sign of an major ongoing mental or physical health event" <-- exactly what I thought when I read the question, and PhD students are particularly prone to depression, +1. I've seen this before. But: "I would find it highly inappropriate, however, to bring this up with the student by saying something like, I've noticed you've gained a lot of weight" <- I disagree about this being inappropriate, doing something about the situation necessarily involves bringing it up (in context, of course). Seeing that you're in the USA, might be a cultural difference

The supervisor should supervise students about their research work and not judge students based on their appearance or their private life. It would not have any impact on my research group.

It would help to know what motivates the question, to make sure I'm getting at what you are trying to find out, but here goes:
The advisors I have known would wait for the student to bring up a health situation before talking about it.
They would consider the overweight in conjunction with other aspects of the student's well-being.  Being overweight by itself wouldn't be a concern.  If it were accompanied by symptoms of pre-diabetes, heart disease, OCD, depression, etc., then the advisor would be concerned about the big picture (including, but not limited to, the weight problem).
The concern would be about the student, not about the group.
The gender of the student would be irrelevant.
This is my assessment, regarding the advisors I have personally known.

@clustro - So, does this mean you would be more likely to comment if a male student puts on excess weight?

@clustro - Weight gain can be caused by many different things.

Also please note that your statement "women derive so much more of their self-esteem from how they look than men" might be true in a statistical sense, but it doesn't mean that every woman does.


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How much effort should weekly homework be worth?
Background: Just completed my PhD, have to teach one part of a graduate course in EE. Remaining course is taught by another senior prof. Course has two classes, totalling 3 hours per week, and one assignment every week which involves one or more of simulation (SPICE), some programming (MATLAB) and some hand-calculation / circuit design. The assignments are worth 40% of the course eval, the remaining being in-class exams.
How long should each assignment be? For instance, I can design the assignment such that it takes the average student (who has attended the lectures) X hours of effort. How do I choose X?

I think this really strongly depends on the content of the course and depends a ton on opinions. Universities often have guidelines (more directed towards students) about how much work to expect for a given course. For US universities I have been familiar with based on "credit hours" (where 15 credits per semester, 2 semesters per year = graduation in 4 years), the guideline is typically "1 credit = 1 hour class time, 2 hours effort outside class weekly" - of course in reality there is a ton of variance around those numbers.

(also, with programming assignments in particular, the time to complete assignments is likely to depend heavily on programming experience, even in other languages, moreso than whether students attend your lectures; if the learning goal is only to master EE concepts rather than learn about simulation environments, I would suggest assignments that build on each other or where some of the backbone of the code is provided)

I ask because university has a guideline (for students) stating something like: for graduate courses each credit is worth over 3 hours of time per week including classroom and/or lab and/or studio hours. courses in medicine will require much more.

So then I think it depends on what you think your students best use of time is out of class: if you think they will learn more from working on the assignments, then those assignments should take most of the 2 hours per credit per week; if there is substantial time that you expect them to spend reading materials, preparing for the major exams, etc, then adjust accordingly. I don't think anyone can give you a more precise answer than that.

How long should each assignment be? -- To quote Abraham Lincoln: Long enough to reach the ground. Assignments should take as long as they need to reach the educational goals/requirements of the course.

I use a rule of thumb that out-of-class work, including assigned reading, should be about twice the in-class hours.  So, a class with 2-1/2 hours of classroom work per week should have about five hours of outside work per week.
For a 15-hour load with 2-1/2 contact hours per three credit course, that works out to 37-1/2 hours a week, a fair approximation of full time.
For any class, some students will find the work to be easy and it'll take less time than you estimate.  Others will find it difficult and it will take much more time.  You're looking for the median and a fairly low standard deviation.
Early in my teaching career, I asked some classes to keep a journal in which they recorded the time spent out of class.  The responses seemed highly suspect, so now I just talk to some of the better students from time to time and ask about how long they spend.

A great answer in all respects, very useful.

Maybe it's me, but I find that rules of thumb like "x number of hours in class means y hours outside of class" to be rather (for lack of a better word, and I mean no disrespect) ridiculous. If I assign 5 problems per week for a typical credit-hour course, however long students take to do it is how long it takes. As you have also observed, some students will spend an hour or two, and some probably put in 8 hours or more, but I'm not sure why I would bother trying to figure out the standard deviation, median, or anything else.

@MadJack In principle one's experience as student and educator should inform you (and other professors) of how long a task will take a moderate to good student to complete.  Just as it should inform you on how long it will take you to do an example in-class, or cover a theorem, etc. Similarly for how long an exam problem will take to solve. You encounter significant problems if you accidentally make a 6 question exam for a 50 minute period and one or more of the problems reasonably takes 20+ minutes.  In practice this is can be hard as hell, of course.

For undergraduate courses, the usual rule of thumb is 2 hours of work per hour of lecture. As a (US) undergraduate is considered full-time if they are taking 12 credit hours, this jives well: 12 hrs lecture + 2*12hrs work = 36 hrs /week, which is roughly equivalent to a full-time job.
On this basis, consider that a (US) graduate student is generally considered a full-time student if they are enrolled in 9 credit hours. If we consider full-time to equate to ~40hrs of involvement per week, we find that the multiplier should be closer to 3: 9 hrs lecture + 3*9 hrs work = 36 hrs/week. Given that you are placing 40% of the grade on assignments, the extra time seems reasonable.
As always, however, feedback from your trusted students should steer the length of assignments. Several other considerations worth factoring in:

Are your students primarily TAs / RAs / employed in industry? Are they actively working on dissertations? What sort of time demands are involved by these other activities?
Some graduate level problems can be difficult to solve in a consistent amount of time---a typical assignment is harder to break apart as "solve for x in these 20 problems." From my personal experience as a graduate student, the time I took to complete a graduate level assignment was much more variable.
A useful estimation for gauging the length of an assignment is to honestly complete the assignment yourself (writing out complete sentences, commenting code written from scratch, etc), preferably a few days after writing up the assignment so the problems aren't fresh in your mind, and time how it takes you to produce solutions. This is a baseline for how fast a student could ever possibly complete the assignment; multiply this by an appropriate factor to account for thinking / debugging / erasing, etc. I have personally found that a multiplier of 5 to 6 works well for me.

I have heard before that two-three hours of homework per hour of class is appropriate. However, I think that a more effective way of looking at homework is how meaningful and thought-provoking the assignment is.
Students today are very busy - many have families and jobs outside of class. If they view their weekly 6-9 hours of homework as busy work, they won't do it or they will do it with minimal attention. My suggestion is to make specific goals for each week's assignment ("I want them to be able to do X after today's lecture" or "I want them to know A, B, and C before the next lecture.") and then build the homework assignments around that. Research shows that particularly millennial students value assignments that "get to the point." So, I design reading and writing assignments that convey the goals I want in the least amount of time. So, my students only have about 2-3 hours of reading and writing each week outside of their 3-hour course. However, they always show up prepared and ready to apply their home assignments in-class!


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What are "post-deadline paper submissions"?
I'm still in the beginnings of my life as a graduate student researcher. My advisor is pushing me to submit my work to upcoming conferences. Now, I'm a complete novice to these procedures, so I began to sift through various conference websites to learn a bit more. I noticed that some conferences have post-deadline submissions for research papers. What does that exactly mean?
Do post-deadline papers get vetted differently, or do they basically receive an extended deadline?
(Physics, if it matters.)
Edit:
Example: http://www.ofcconference.org/en-us/home/submit-papers/

I've never heard of this concept. Can you provide a link to such a conference as an example, or cite the language they use to describe the procedure for a post-deadline submission?

It might happen that there are free poster or talk slots left after the official deadline ended. Thus, post-deadline submissions might be considered for this slot. However, this is only a guess. I would suggest to ask someone in your department/working group.

@DanRomik Here's an example. http://www.ofcconference.org/en-us/home/submit-papers/

I'm amused by the concept of a "Postdeadline Paper Submission Deadline".

You can think of post-deadline submissions as reserving seats on overbooked flights: if someone doesn't show up, you get the place. But in case of conferences, not that automatically.
Some twenty years ago, when conference submissions were handled through emails, post-deadline submissions were not that uncommon, at least in my field. You would have sent an email apologizing for not having been able to respect the deadline, and hoped for the best. If the technical committee found your work valuable and the organizers could find a free slot, either oral or poster, your paper would have been accepted and your submission would have been added to the book of abstracts as a spare sheet with the headline "post-deadline submission". I recall conferences with around 5-6 post-deadline submissions.
With the advent of submissions managed through websites, it seems to me that post-deadline submissions have been progressively less accepted.

Do post-deadline papers get vetted differently, or do they basically receive an extended deadline?

How post-deadline submissions are handled really depends on the conference organizers, and how much post deadline the submission is. In some cases, they could be reviewed directly by the chairs of the technical committee rather than by the designated reviewers.

I've sat on journal committees and reviewed proposals. We know that for many people, their institution won't pay unless they are presenting. So we want to make as many slots as possible. If there is a possible to squeeze in a few more talks or posters after the deadline (because we found another venue, or didn't get enough in the first place), we'd open it up for post deadline submissions. The bar might be a little higher, but only a little. (I can imagine that for some conferences, the bar might be lower.) It's a slight pain, because things have to be reviewed more quickly, so we would rather not do it.
Other conferences are much more selective, and this would not apply to them.
That might not be how it works for every conference. If they announce post-deadline submissions before the deadline, then I have no idea.

Post-deadline submissions, at least within optical communication, are also intended for "new and significant material in rapidly advancing areas".
From the OFC 2020 website:

Postdeadline submissions are not an opportunity to submit a paper
  after the published deadline, but are intended to provide those with
  late-breaking work an opportunity to submit that work for
  consideration. Postdeadline submissions should describe new and
  significant material in rapidly advancing areas. A limited number of
  postdeadline submissions will be selected for presentation, and only
  those papers judged to be truly excellent and compelling in their
  timeliness will be accepted.

https://www.ofcconference.org/en-us/home/submit-papers/submit-papers/#Postdeadline (Accessed 2020, March 5)


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As a student, can I publish a paper without including the head of the lab as co-author, against his wishes?
My question is, how can I publish my results without name of my supervisor as a co-author? Do I need their name in my paper? Is it suspicious if I submit an article without his name?
I have a problem with the head of the lab that I performed the experiments there. He wants to be the coauthor but in my point of view he does not have substantially intellectual contribution to my work. He also, told me that he would send samples for the measurement to another lab. But, he did not. Whenever I followed up about the measurement of samples, he postponed to another month. It is almost two years. My supervisor is worried that the guy may make trouble for his profession. So, he said that I can publish the results that I have without his name. The article is just have two authors, another student and me (PhD graduate). Do you think that journals will publish our results or they will suspect about it?

Some similar questions have been posed and answered previously: https://academia.stackexchange.com/questions/15219/can-two-phd-students-publish-without-involving-their-supervisors https://academia.stackexchange.com/questions/98392/can-phd-students-publish-papers-as-sole-author-without-including-their-superviso https://academia.stackexchange.com/questions/49110/will-a-journal-reject-my-paper-just-because-a-grad-student-is-the-sole-author

One point that I should mention is that according to ICMJE (http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html) authors should have 4 criteria. I believe that the guy that I was working in his lab does not have any of them. He just permitted me to use his lab which is not specific lab and I could go to some similar labs instead of his.

Moreover, I think he abused my trust. I left my samples in his lab for the measurement and he wasted my time by not performing the measurement. Therefore, I think it is not fair to give him more credit by adding his name as coauthor. However, he thinks that he did substantial help just because permission of using his lab and technical guide of his student.

Could you elaborate more clearly on how the persons "the head of the lab", "my supervisor", and "the guy" are related, how their perceived contribution to the paper was, and who wants (or not) / who you want (or not) to be included in the author list?

To do my thesis I did part of experiments in another lab. The head of that lab is not my supervisor. The head of that lab considers himself as a guy who had contribution to my project. But I just used his lab. He did not spend time on my project. Therefore, I do not believe that he deserve to be the coauthor.

To help answer the question "is it ok to publish without a supervisor/head of lab?", consider the following points:

Having more names listed as authors doesn't dilute your own contribution. At job interviews, you will be asked which of your articles you consider the most significant, and what was your contribution to them: your ability to explain these points has nothing to do with the author list.
Having a more experienced researcher co-sign one of your articles may attract more citations. When writing, nobody should ignore previously published relevant work; in practice, getting cited is easier when co-signing with "big names" in a field (not saying I like this situation, but it is what it is...).
Simply by allowing you to work in their lab, this person made a significant contribution to the article (although not a "substantial intellectual contribution"), in the sense that the article would not be the same without you being able to do work in this lab. Some might think this is what the acknowledgments section of an article is for; it depends how you used the lab's resources (was it more like a service that you could have easily found somewhere else, or did you benefit from this lab's unique expertise or equipment?). If it looks more like a collaboration, including this person as author would be fair.

He did not any have any collaboration to my work. He just let me to use his lab which was not unique. I could go to another lab. I put his name in the acknowledgement but he wants to be the coauthor.

Doesn't the term "author" specifically imply an intellectual contribution? It seems disingenuous to include someone as an author when they didn't actually author anything...

Why not include your professor as co-author and do not include the head of the lab where you performed the experiment? Regarding your question, if the journal will suspect about it there's a part of the submission that you can declare any conflict of interests.

Papers can be published without supervisors, or in other words just by students who have done the research. Since it is unclear exactly what his role his, it is hard to say how suspicious this would be. I don't think the Journal that you are submitting to will do thorough investigative research to determine exactly who did what on each submitted paper, but if this colleague felt he contributed some amount of work to this paper and you intentionally leave him off you will burn bridges in this relationship.
I think if he did contribute, he should be included. If he did not contribute, it is okay to leave him off.


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How do I find the most cited authors given one or more MESH terms?
I would like to be able to give some academic database (like pubmed) a list of MESH terms (MESH: Medical Subject Headings created by the National Library of Medicine), then select papers by authors who have received the most citations. Either in total (all work) or within the scope of the papers I pulled up using the given MESH terms.
Is this possible?

You could use Europe PMC database to search for publications by keyword of choice using (KW:"XXX") syntax. Then sort the results by times cited and look at the authors of the top publications.
Here is an example for most cited articles by keyword "myalgia": https://europepmc.org/search?query=%28KW:%22myalgia%22%29&page=1&sortby=Times%2BCited%2BDESC. In this case, keyword includes MESH terms and keywords supplied by publishers.
If you wanted to do that programmatically, for example to collate citation numbers for individual authors, you could do that via the Articles API. Here is the RESTful URL for the same query: https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=KW:myalgia%20sort_cited:y.
Disclaimer: I work for Europe PMC.


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Is it normal to interview for faculty positions in December-February and not hear back yet by the end of March?
I had several interviews in December-February in R1 universities for tenure-track assistant professor positions in a life sciences field.
I was told that they would get back to me in March, so I emailed them and some have not replied back and some said to wait some more.
So, I was wondering if this is normal to wait for that long or "the ship has sailed" and I'm not getting any offers :(

I removed the part that was polling about other people's offers this year, since that's off topic here.

You may well be a second or third choice.  In that case, they're probably keeping you as a backup in case they can't reach agreement with their top choice, and its likely that they're in negotiations with another candidate.  FWIW, I interviewed for my current position in early March and didn't get an offer until late May after two others had turned down the job.

I find the waiting to be torturous, any advice on how to take your mind off that?

Commiserations -- the job search is tough.
If they haven't gotten back to you by the time they said they would, it most likely means you are not their first preference candidate. They probably have already made an offer and are waiting to have that accepted or rejected. You could still get an offer as their second/third/fourth/etc. preference.

Sometimes, you never hear back from a committee.
I applied for a position and had an interview three years ago, and have not had so much as an acknowledgment that the interview even take place, let alone a rejection notice.

Thank you, I guess without the official "No" I still keep living in hope and it's so hard to move on. I am actually having trouble focusing on my work and all I can think about is what went wrong. I need to snap out of it.

Was it by any chance a German university? I just received a negative answer from an university in Germany, where I applied more than two years ago. I don't know what I find more curious - that it took them two years to fill the position, or that somebody actually bothered sending out rejections multiple years after the application had been sent.

@xLeitix: Nope. It was a school in the USA.

@xLeitix two years!!! they didnt filled positon?

@SSimon they did... I think.


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Is following video tutorials online of programming plagiarising?
For my dissertation, I have decided to create a program which involves multiple mini games such as a snake game, tic tac toe, maze game and a puzzle game.
Although, I liked programming, I struggled when I started developing my game project. For this reason, I decided to use Youtube and follow tutorials on how to do the games I wanted. I followed the tutorials line by line and made some adjustments to fit my requirements.
Afterwards, I then put a comment stating the codes aren't mine and online guidance was used to successfully make the function/code.
I must admit, the modifications I've made are very minimal. For example, changing the images, the music, the colour and the background. The reason is because the codes are well written and made sense, I couldn't think of any other way of writing it.
To be honest, Its very wrong of me to just copy the guides online line-by-line. However, the tutorials did help me understand how the codes/functions work and why they must be written like that.
I think I screwed up here. I talked to one of my dissertation's markers and she was pleased because of my honesty because others would just straight on claim the code is theirs.
Later on we will have a chance to present our work in front of our markers. I am unsure how I can defend myself if they bring how I made the codes (which they will).

If you make it clear to readers what your original contribution is and what you got from other sources (and name those sources), it's not plagiarism. Complete, accurate attribution is the key to avoiding plagiarism. (It's not clear from your description whether you did that -  "I used guidance from these sources" is not enough to make it clear that you used their code with only minimal changes!)
Even if it's not plagiarism, it is still possible that you have not done enough original work to satisfy those grading your work. That's not a plagiarism issue, but a matter of what expectations are for this kind of work at your institution, and whether you have satisfied them.

Instead of saying the materials you cite 'assisted' you or gave you 'guidance', it seems more accurate to say explicitly: "I adapted the software described in X by doing A, B and C."  This will tell the reader exactly what you did do and for everything else, they can look at the referenced work.

One test you can apply: Suppose someone read your dissertation, and subsequently found out all the details, including what exactly you copied, what you changed, and what you wrote from scratch.
Would they be surprised, or would the full details be exactly what they would have expected from how the material was presented in your dissertation? Your objective should be to give a reader of your dissertation an accurate impression.
There is a secondary problem you may have of insufficient original material, which could reduce your grade, but would not involve any academic misconduct.