How to graduate your PhD when you have no hope

If you want to do high-impact research in the long run, you need to have a strong foundation, which means a solid bed of high-impact papers to point to when you need funding, opportunities, etc.

The first is the lofty intellectual ideal of solving a major problem, winning a Nobel, and getting your name in the history books. The second is the daily grind of reading other people's papers, providing peer review, writing grant proposals, and generally interfacing with other humans as a cog in a grand machine. The second is in some sense "easier" than the first. It's a lot more work, takes a lot more time, but it's a relatively straightforward (if often tedious) process that pretty much anyone can do with enough diligence. The first is a lot more fun, can often be done while showering, but is also fraught with risk and dependent on luck. You have to find just the right problem at just the right time under just the right circumstances. You can spend your time slogging, or you can spend your time buying intellectual lottery tickets and hope that lightning strikes, but you can't do both, at least not at at the same time.

The good news is that engaging in the daily slog is often (but not always) good preparation for and improves the odds of having lightning strike. So as a practical matter, that is often a good place to start. You might feel as if you're wasting your time reading everybody else's bullshit papers instead of writing the next Nobel prize winner yourself, but you're not. You're actually an essential part of the process even if you don't end up with the glory. And some day you just might be facing a really hard problem and go, "Wait a minute, this seems kinda like that thing I remember Dr. Arglebargle talking about three years ago, except that he missed this one detail..." and that's when the magic happens.

I think that's it for most PhD students. Look at recent papers from your advisor (or their co-authors). Once you understand that specialized area well-enough, you should be able to find an epsilon that can be added, or to apply some results to a different use case. A 2-3 papers in somewhat decent conferences should be enough to be able to graduate.

Most people won't solve interesting open problems. They will find questions that nobody has asked before, so they can be the first one to answer it.

While this feeds into the founder kool-aid we all drank as founders, it also speaks volumes of truth to me to this day: I rejected where biology/ecology was going even when supposedly favourable paradigms--Al Gore's inconvenient truth and Carbon Credits were a thing as I was wrapping up my undergrad and I was appalled by both--were standing in front of progress and the most obvious solutions if you could take the small amount of time to familiarize yourself with emerging technology outside your gradschool bubble. Something I don't think academics are actually capable for fear of seeming to reveal themselves as hyper-specialized in one aspect only rather than the polymath they may seem/convinced themselves that they are.

Also, it is my experience most academics are tone-deaf and incredibly petty individuals: a visit with the tenured faculty was enough for me to run for the hills of the debt-laden, financial crisis impacted work-force.

I still visit my Biochemistry professor from time to time, who did well getting into Bitcoin, when I launched my startup working with the Hemp Industry; and I'm super proud of playing a part in that since we both got hit hard during the 2008 financial crisis. But I'm glad I turned down his offer to work in his lab and get my Masters and went through boot-strapping hell to launch my startup after working in many Industries just to get by.

It was interesting white boarding about the bio-chemistry of CBD (and other cannabnoids for that matter) infused drinks/food I could pitch to my clients as profitable avenues of growth after struggling to make it to class and 'only get a B-' because I just didn't 'fit' (read: rebellious) the school model at all despite having both honors and letters of recommendation to join two labs.

I'm in Grad school now (almost 20 years since starting my undergrad) for CompSci now, but only because I'm working to transition into Big Data and I already work on the large Data Centers spurred on by the AI hype; luckily it's a non-thesis program for experienced and working professionals (I'm currently on assignment for a sub-contractor in WY).

I wonder sometimes, how many of the people arguing endlessly and religiously about concurrency primitives realize that they are debating “religious” texts from the same prophet, Sir Tony Hoare. But as you say, the lack of immediacy does seem to mess with our heads.

So I think both options really depend on what you can deliver and in what timeframe.

Right. I got an MSCS from Stanford in 1985. That was about when it was becoming clear that expert systems were a dead end. The Stanford faculty was heavily invested in expert systems at the time, and were in serious denial. This was the beginning of the "AI Winter". I could see this, because I'd been doing proof of correctness work, where machine-powered predicate calculus could deliver results. It was clear to me that those methods were too brittle for the real world, although they worked fine on the rigid world of computer programs. Hammering the real world into predicate calculus only works if you already almost know the answer. (Drew McDermott's essay, "Artificial Intelligence meets Natural Stupidity" is the classic commentary on that.)

There were some neural net people around, but they were stuck, too, partly because they needed a few more orders of magnitude more compute power before that approach started working. Neural nets had been around for decades, and on a good day in 1970 you could recognize handwritten numerals, slowly. Computer power wasn't increasing that fast in those days. In 1970, there were 1 MIPS mainframes, and in the early 1980s, there were 1 MIPS VAXes. Success with neural nets lay many orders of magnitude in compute and several decades ahead.

So, instead of academia, I did some stuff for a little company called Autodesk.

I never expected computer science to be captured by the ad industry.

Marriage creates a structured life outside of work that gives PhDs an anchor to return to periodically. This leads to better long term and consistent progress.

Stephen King describes his success in writing in part due to his successful marriage. There may be some similarities there.

At least in math, I would rather say that marriage is a counterindication that a great PhD thesis come out at the end, for the simple reason that being married means that math is only your second love, while writing a great PhD thesis in math requires the topic of your PhD thesis to be your nearly only love for the duration of your PhD studies.

Imagine having a partner to wade through such an experience who can relate, is pushing you, helping you see your blind spots, quelling your doubts/fears, and in general cheering for your success.

And then the clarity you get for doing the same for them.

There's also the extra level of responsibility that marriage entails, that forces one to 'grow up', for want of a better expression.

1. If your partner is not in a PhD program themselves, then you can rely on them during what I call “crunch time”, and there are a few of those in every PhD when you’re doing 16 hour days 7 days a week just to get something out of the door. Single students don’t get that luxury and thus inevitably have to be miserable during that period.

2. Secondly, successfully navigating a relationship/marriage takes a lot of the same skills as successfully navigating a PhD. A good PhD at the end of the day is built on a lot of compromises: between your vision and your advisors’, the fields’, your collaborators, and if you’re interning, your industry partners. A relationship teaches you how to navigate that without burning bridges, which may not be true for a headstrong “I’m gonna change the world but I don’t know how” PhD students.

Disclosure: Married to another PhD student.

Also, somebody to drive you to the hospital when your experiment explodes. Fortunately, she wasn't seriously injured.

I could imagine marriage helping if one doesn't have kids and the cost of living where the school is located isn't too high or if one's spouse has a successful career.

The advantage of being married is that you don't have to spend as much energy dating and other social activities.

You should visit a lab that does actual experiments. I don’t think anyone is doing cryo electron microscopy in their spare time. Most science just takes a lot of time and money. No way around it.

Also, most research is incremental, and thats’s totally fine. People lionize the “great men” like Einstein who have these earth-shattering discoveries, but those aren’t really worth anything without the decades of exploration and hundreds of scientists testing theories and figuring out their consequences and implications.

The problem, honestly, is an ancient one. In plato's republic he complains about a lack of state funding for geometry :

" Then take a step backward, for we are out of order, and insert the third dimension which is of solids, after the second which is of planes, and then you may proceed to solids in motion. But solid geometry is not popular and has not the patronage of the State, nor is the use of it fully recognized; the difficulty is great, and the votaries of the study are conceited and impatient. Still the charm of the pursuit wins upon men, and, if government would lend a little assistance, there might be great progress made. "

https://www.gutenberg.org/files/1497/1497-h/1497-h.htm

As a matter of fact, I don't think I would have finished my PhD had my wife not supported me mentally, economically, and in spirit. I've observed our single students struggle, complaining about having to do chores after classes, clean, cook, look after themselves. Whereas my spouse was supportive and understanding, she took a colossal load off my shoulders - I could concentrate on my studies and had little to no worries outside of school. We both worked, but she worked full time to support us and got a master's degree, so she knew all too well that grad school isn't peanuts.

I think it's more so about having a good spouse who is understanding and supportive, who can meet you halfway.

> 1. They had competent PhD advisors

I'd say fit is very important. Some advisors will provide students with feedback, give them direction, and wait for the students to come back with output. Other advisors will micromanage students, give them tight deadlines, get upset if they don't strictly follow everything they say and every deadline, and generally give the student no freedom to do anything on their own.

The thing to keep in mind is that grad students usually work well in one of those environments, but few students will thrive in both.

> as a married student I had to balance my research and teaching responsibilities with the needs of my spouse. It added a level of mental and emotional stress my single colleagues didn’t have to deal with.

This can go in several directions. Your experience is obviously the most common. In some cases the spouse is counting on the grad student to finish and get a high-paying job. They take care of everything like paying bills, shopping, cooking, etc. I've also seen cases where the spouse sacrificed so the grad student could finish (so they could have a higher income and start a family) and it put so much pressure on the grad student that they were breaking down.

I went back to school after a few years to get an MBA. I've never actually managed anyone to this day but it was sort of a prereq for a lot of the types of jobs I was interested in at the time.

It helped that the coursework was easier for me than the engineering degrees I had. But I think there was also discipline and process that came from having been in the working world that definitely helped me do really well in the program.

15) I made time to do whatever impulsive thing my mind felt like doing in my free time. I love video games and after a decade avoiding them because I felt like they were a waste of time, I got back into them.

16) I still had total freak outs from time to time. I vividly remember googling plumbing classes at community College. (Nothing wrong with plumbing! I bet for 10% of readers the right answer is to drop out of your phd and go into trades)

17) try not to get drunk too often or high too often. A bit on Friday is ok (you need to self monitor)

There are a lot of good, technically fascinating ideas out there. Only a subset of those are interesting to other researchers in your field. As an early career researcher, the first priority is finding projects that other people will care about. It’s very very important to find an advisor who knows what others care about. Science is inherently social.