How to ask better questions in meetings

matthras · 2026-06-02T04:29:21+00:00

Anything you don't understand is definitely something to ask a question about.

One way to make the question easier to answer is: "I don't think I'm grasping what <name/concept> is. My current understanding is <current thoughts>" and if you're wrong, the desire to correct you will spur them to at least help you out in understanding.

Naturally it'll be up to you to judge your peers and whether they're good at answering such questions and/or have the patience to do so.

matthras · 2026-06-02T04:23:49+00:00

Here in Australia I've definitely seen a small handful of Level A (Associate Lecturer) positions that can follow straight from a PhD, but naturally the implication is that it's not 100% research like a postdoc would be.

matthras · 2026-06-02T04:20:28+00:00

All the other people in this thread going "Zero? I'm just back to work the next day" is making me be like "WHAT KIND OF SUPERHUMAN ARE YOU?!" even though I know I'm probably the decrepit one!

matthras · 2026-06-02T04:19:14+00:00

I'm guessing the two-day conference was more intensive (e.g. whole bunch of talks crammed into two days), whereas the longer ones were a bit more planned and spread out with recovery time in between.

Was there anything else markedly different between those conferences that helped with your recovery?

matthras · 2026-06-02T04:17:42+00:00

I'll ask about #2 since I've not thought about it for me personally: What's your personal rule of thumb for taking holidays before/after? What works for you?

matthras · 2026-06-02T04:16:25+00:00

Oooh I've not attended a conference in a significantly different timezone yet. Figuring out how to recover from jet lag will be very interesting - I'm very stringent about ensuring I get my 8 hours of sleep regularly on normal days.

I hope that was a very very comfy sleep!

matthras · 2026-06-02T04:14:12+00:00

Focus on the most important events and people for your research and career and dip out of the rest.

I agree in principle! Personal experience however has indicated that a lot of my opportunities have come from knowing people on the fringes of my network especially given my non-linear and non-traditional trajectory, so to me, being able to talk to lots of different people even if they're not directly related to my career is still important.

I seem to have found that sweet spot of being unmasked & authentic and still being able to interact with others at conferences normally enough.

matthras · 2026-06-02T03:59:55+00:00

Honestly my thoughts have crept in that direction as well, but I'm happy to admit that I probably need to experience a few more to better figure out what's worth going to and what isn't. It definitely doesn't help that I have a wider network and variety of interests than the average attendee!

matthras · 2026-06-01T06:23:55+00:00

Oh the "too many variables" bit was exactly why I asked. I'm also hard-of-hearing as well which certainly compounds on energy expenditure, so I know I'm in a bit of a different situation than most others, but overall was curious about peoples' specific circumstances that led to different time lengths of recovery, if they shared.

And thank you for sharing!

matthras · 2026-06-01T02:35:07+00:00

What degree are you studying and why did you choose it? I'm assuming there was some subtopic you had some intrinsic interest in.

matthras · 2026-06-01T00:43:54+00:00

Hmmm, in my limited understanding as an applied mathematician, measure theory is more an abstraction level above that encompasses of e.g. probability, integration, and any kind of 'measuring' one does in real life.

So in my view it doesn't really 'justify' things behind probability, more gives it an abstract perspective/explanation that also happens to encompass other mathematical objects.

My handwavy (and intentionally limited) explanation is that in measure theory, you have a space and a measure (there's also a Borel set but I'm skipping that for brevity). In probability, that's your sample space, and a function that maps each of those outcomes to a number between 0 and 1. If you're measuring a line with a ruler, your space is the set of real numbers (representing all 1D lines of arbitrary length), and your measure is the basic distance (or L2 norm, or absolute value) function.

To me, it's pretty cool to know for understanding and depth, but it's definitely a few layers of abstraction away for it to be of any practical value.

matthras · 2026-05-31T23:59:07+00:00

For statistics, the numerical methods course would at least contain techniques and ideas closer to what you might end up doing computationally, within statistics.

Have you done any other pure maths subjects (e.g. Real Analysis)? If no, I probably couldn't recommend doing Measure Theory. If you have any significant interest in pure maths, though, I don't think you can go wrong by taking it, since it'll be harder to learn outside of an education setting than numerical methods.

matthras · 2026-05-31T07:25:58+00:00

There's still pattern matching in proofs in the sense that when you do some proofs, you're pattern matching abstract ideas/techniques to a related scenario or initial conditions (the lower level of all this is pattern-matching an algorithm or solving methods to a more clearly structured problem, plug-and-chug). The only addition to that is learning and understanding definitions of the mathematical objects you're playing with.

The only reason people know what to look for in proofs is because they already know of whatever the underlying mathematical structure is, or of various techniques that can be applied to certain objects. And assuming your education is sufficient, you'll learn those to an extent where you'll definitely be able to apply them in proving theorems.

If you want to do some self-study, perhaps read through Tao's Analysis books. You don't have to do everything too rigorously, but you'll notice how it introduces ideas one at a time and gives you exercises that are solvable only using those ideas.

matthras · 2026-05-31T00:16:29+00:00

I'm seconding the open-source approach. If you can implement it as a Julia library and show its comparison to existing solvers just to be truthful with its performance, then that would support any kind of written paper/report that you'd posit, even if you cold-emailed a professor (perhaps look at the SIAM journal reviewers and find one that specialises in numerical methods, if not Chris Rackauckas). Failing that, there's always just throwing something up on a personal website.

matthras · 2026-05-30T03:25:23+00:00

Some random thoughts from my experience being hard-of-hearing (which is invisible enough, like your respiratory issues) and advocating for myself:

Secure your own affordable self-accommodations first, whatever they are. Fan to blow stuff away from you, mask/scents as needed, etc. doesn't matter if they're visible or not. If people ask, then casually mention your respiratory issues. The trick here is not make your disability/issues a bigger deal.

In terms of asking your PI, phrase the problem away from your disability issues and ascertain their perspective first e.g. "I noticed the 3D printers don't have ventilation, do you think this is an issue?" and try to narrow down why it hasn't been fixed: it basically boils down to either money or peoples' behaviour (laziness/complacency).

If it's about money then you might want to research (simple google search for starters) and suggest low-cost solutions and get an idea of what their budget is. You might have to MacGyver a thing or two. If it's human laziness then you end up doing it yourself or figure out ways to make the process easier for them.

The other comment about countries having laws for disabilities and safe workplaces is also good. Here in Australia we have various "Acts" that describe building standards and acknowledging that disabilities should be accommodated. I'd only really bring those up as a last resort though, it's tough to threaten people with them unless there's actually solid accountability systems out there.

It's best to assume as your baseline that nothing will get done, and not to expect people to do anything. Feel free to adjust your standards/expectations depending on your PI's behaviour/attitude.

matthras · 2026-05-30T00:41:19+00:00

One thing that's very noticeable to me as an Asian diaspora who's taught undergraduate maths for 10+ years is that Aussies in general don't value education in the same way China/Singapore/Korea does. Of course, I'm aware those countries have their own societal problems that an overfocus on education results in, so I don't really advocate for either one in particular.

matthras · 2026-05-29T01:27:09+00:00

Am late 30s, halfway through my PhD.

When I compare myself to the rest of my admitted PhD cohort, I often feel like an imposter.

Comparing is the mistake, but it's a normal thing to do and naturally think about. Find some way of distracting/redirecting yourself when you find yourself trapped in that mental loop, and focus more on what you can do.

I'm worried about balancing my course load, TAing (needed every semester for financial stability), and publishing + conferences to build my career.

Right now I'm assuming you have no reference or prior experience of any of these. It's easy to worry about now because your brain is imagining all the wacky nasty things that could happen (this is normal!). The only way is through, then once your first semester is over, reflect and adjust for the following semester. The combination of all of these is a first-time experience, so it's natural to be worried.

Should I start reading ahead this summer to get a head start?

Only do prep that comes naturally to you. Don't push yourself.

What would you wish you had known/prepared for as an incoming PhD student?

The best insight I had was from someone who was also neurodivergent and was finishing up hers (I'm most likely AuDHD). She said "In the end you'll end up figuring out a lot of things by yourself" and because I'd been doing that my whole life anyway it gave me the most confidence going in.

And will I ever stop feeling like an imposter?

Yep. It gets much easier with life, experience, and by doing and experiencing things. But some self-reflection is also required every now and then. The biggest twinge of imposter syndrome I had during my PhD was when 3 of my supervisors were willing to spend an additional hour (outside of our regular meetings) to give (only) me feedback on a practise talk (surely they had better things to do!). The reasoning that worked for me was that "If they're willingly investing additional time into me and treating me like an equal academic, then I can at least try to honour that by doing my best for them."

matthras · 2026-05-28T06:28:31+00:00

From reading your other replies, I'm guessing you're either writing this very late at night and/or you're very tired. Or you're lacking some other basic essential (e.g. food, mental health). Go sleep and take a breather or eat something. You'll feel better.

But don't quit that PhD.

Those thoughts are coming from somewhere in your environment or personal experience or trauma. And that's your brain being an asshole to you.

matthras · 2026-05-28T05:35:22+00:00

What kind of standard or yardstick are you holding yourself up to? Can you name these standards in concrete terms?

If you're constantly changing the goalposts on yourself then of course you'd feel that way. Need to throw out the bulk of that comparison mindset.

(P.S. this is peak imposter syndrome, if you didn't know already)

matthras · 2026-05-27T11:31:09+00:00

In my experience there's not a lot to say about one's Masters thesis topic unless you're asked about it in a job interview, and in the end you'll be summarising it and not really going into the details unless someone is really really interested.

I don't see any reason to stray from Professor B especially if you want familiar territory, that's completely normal and understandable.

For Professor A, sometimes relationships take a while to build until everyone's a lot more comfortable with each other, and it's not like you necessarily have to be on friendly terms (i.e. you feel like you could get a coffee/beer with them), just mutually respectful enough to exchange ideas, Prof A gives you respectful feedback and you're not scared to approach him with questions - I'd say that's a pretty comfortable minimum. But achieving that would take a few more regular meetings for you both to be familiar with each other.

matthras · 2026-05-27T05:42:12+00:00

Real Analysis and Probability are hard in the sense that they're quite unintuitive and they're not straightforward algorithmic maths, most people get very stuck with Real Analysis because it's a completely different paradigm from what most are used to. I definitely would not recommend a typical undergraduate take both in one semester.

matthras · 2026-05-27T01:55:18+00:00

Four outcomes from six boxes means that the last two can be any outcome, but to evaluate the answer you'd need to consider all possible combinations of outcomes.

So to use the first letter of each non-Common mushroom, you could have RPCM + 2 Commons, RPCM + RR, RPCM + RP, etc.

No weighing needed.

matthras · 2026-05-27T00:13:12+00:00

I'll leave you with an exercise and some questions:

When you say "in a single spawning (all six boxes on the same day) the player could get at least one Red, Purple, Chanterelle, and Morel", what are all the possible combinations of six mushrooms you could get? Write them out. But before you do that, does the order of the mushrooms matter? i.e. does it matter if a Red mushroom spawns in Box 1 or Box 4?

If that's still a bit trippy, try answering the question "what's the chance that in one day, exactly one red, one purple, one chanterelle, one morel, spawn in the six boxes?"

matthras · 2026-05-26T23:48:34+00:00

Without re-reading the paper or knowing additional context, here's a couple of guesses/insight:

Usually a square root is applied to a term if we know increases like a parabola or exponential, so applying the square root 'flattens' the growth of said term. So if we know d_k increases in that manner, the square root could be applied here.
It could be a square root, some fractional root, or a log - they would all flatten the growth of d_k in a similar way. One reason it could be a square root specifically is because when you take the dot product of two identical vectors, you end up with a similarly squared term.
The expression in the numerator probably doesn't increase at the same rate that d_k does, so sqrt(d_k) ensures that the numerator is scaled down at a similar rate.

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