WEBVTT

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Hi everyone.

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My name is Nick Rober.
I am a Fellow with the AeroAstro Comm Lab.

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And today we're going to be talking about
managing a research project.

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So the lesson goals for today
are first to identify

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ways that we can both define
and scope a research topic.

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We'll talk about

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how we can learn strategies for,
breaking projects into manageable bits.

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And then we'll also practice,
tracking our progress for a given research

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topic,
and adapting your plan as things change.

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So first I want to jump into why

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actually managing a research
topic is important.

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So if you haven't figured this out by now,
research can be very messy.

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So things don't usually go
according to plan.

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Things change as you,
as you go through, researching a topic,

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and what we call a scope
creep can be very normal.

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And what scope creep is, is
just the gradual

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changing of your scope of your research.

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So as you go through a project, maybe
you add things, maybe you remove things.

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The scope of what you're actually
researching changes as you go, and this is

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super super common.

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And so

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what we see is that if you're,
if you have poor project management,

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there can be a lot of wasted
time, a lot of frustration, a lot of,

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you know, difficult meetings
with your advisor.

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But if you have very clear,
and efficient management,

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you can make progress a lot faster,
and your impact is usually pretty,

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is usually higher.

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So the thing to keep in mind
is that even from very early stage,

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stage planning of your research topic,

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this is something
that you should keep in mind.

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You want to be able to identify
what you're going to be doing next,

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how that might change,
and then avoiding getting stuck

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in kind of cycles of reading and,
and going back to the drawing board.

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And then also you,
with good project management,

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you can notice quickly
when a direction isn't really working or

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probably won't pan out.

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So what are the common research challenges
that make this difficult?

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People will often try
and address a topic

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that is either too broad or too vague.

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This usually leads to kind of
just reading without much focus

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and and trying to get as much information,
but you don't necessarily

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know what information
you're trying to get.

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And then if you have difficulty
explaining your project

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in 1 or 2 sentences,

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that can be an indication that you're
working on something a little bit vague.

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Trying to solve a lot of stuff at once.

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So we'll talk about this
a little bit later,

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but if you're doing a lot of things

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it makes it a challenge
to actually get anything done because,

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the amount of stuff that you're doing
is really difficult.

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So what this often manifests as

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is feeling busy
but not actually getting much done.

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Another thing that is important
to keep in mind is, is your project

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progress trackable?

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Is, the, are the things that you're
doing, measurable in some way?

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And another important

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challenge that we'll talk about
is communication with your advisor.

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So if you're meeting,
if your meetings feel unproductive,

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or if you're getting
a lot of contradictory feedback

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that seems different
from one meeting to the next,

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it may be an indication that you're,
you're not moving with enough focus.

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So the important thing
to kind of begin with is

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you want to start
with a very clear question.

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So keep in mind
that research is ultimately a practice

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of asking and answering questions

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and you shouldn't be trying
to accomplish everything in one go.

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So whenever you're starting
or working on a research project,

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a very key question that you should ask
yourself is what gap am I addressing.

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So this could be through the form of
you know what.

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So what doesn't work,

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what isn't understood,
or what is missing in current approaches?

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You may ask why, why does a gap matter?

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Why does this thing happen?

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Or how?

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So how can this be addressed with, you
know, a given set of tools that may exist?

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Or how can we develop
new tools to address this problem?

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And the thing to keep in mind

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is that you want to keep it narrow enough
that it's something that is achievable,

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but not too narrow, that it becomes
uninteresting or trivial.

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So one way to do this is,
with what I call the scope matrix.

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So there's three axes to the scope
matrix.

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One axis is the problem.

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So how big or small, easy or hard
is the problem?

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One axis is the method.

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So, is your method that you're going
to try to apply super, super new

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never been done before, or is it something
that's maybe a little bit more standard?

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And then the third axis is the domain.

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So you know, how broad or narrow
is the set of problems that you're trying

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to to address.

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And ultimately what this boils down to
is that increasing along one axis

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will usually require a decrease
in the other to remain feasible.

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So for example, consider
we have some problem,

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and we want to,
we want to solve that problem.

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If I want to take a standard method
and update it

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so that I have some new method,
maybe the problem can stay the same,

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but the domain of types of,
things that it applies to is reduced.

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So that is represented
by this diagram here.

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An overambitious
example for this scope matrix.

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So you could imagine if we have
our problem is safety

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performance and stability,
so three properties of a system,

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maybe what we're trying to do
is develop a unified control

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and verification framework.
So that does a lot of stuff.

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And then the domain is for all autonomous
aerospace vehicles.

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These are all three different things
that have kind of maxed out one of the

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axes of the scope matrix, and solving
this problem would be super, super hard.

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So you kind of need to reduce one
or more of the axes to actually,

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you know,
think about actually solving this problem.

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So with that in mind, we will launch
into our first activity of the day.

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So open the Apply the Scoping Matrix file,

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and take about five
minutes to complete that.

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[Alien

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spaceship beeps]

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Okay, so once we've kind of thought
about our project and scoped it out

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and have some idea of what we're doing
that's reasonable and achievable,

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the next piece of managing a research
project is to break your project

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into units.

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So I have what I like to call
the minimum research unit.

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So this is just a small
and meaningful result

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that can be, achieved by you
know, 1 or 2 actions.

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But basically what you want to do is
you want to start with 1 or 2

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small questions,
that can be answered through

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one experiment and it produces
maybe a tangible figure, or graph,

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or a result that you can kind of point to
and say,

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you know, “I answered this question,
with this result.”

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These minimum research units help
to decide what to work on next.

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They help to recognize you know, progress
when you're making it.

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So once you get this figure, you say,
you know, this is progress.

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And then it helps to avoid getting stuck

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in these loops where you kind of
have this vague idea of your direction

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you're moving, but not actually,
getting any progress in that direction.

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So some examples of a minimum research
unit could be,

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implementing a turbulence model
and comparing it to baseline CFD.

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You might study the flow separation for

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one angle of attack of, of a wing,
or you might evaluate

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the aerodynamic performance,
for some airfoil modification.

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So let's, go into the next activity.

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So find the file.

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Break Down Your Project
and take roughly five minutes to complete

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that.

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[Alien spaceship beeps]

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So the next piece of managing a research

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project is, is very important,
this is, milestones and tracking.

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So there's a couple of different types
of milestones.

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We have short term milestones.

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So these are usually on the order of days
to weeks, maybe a month, Where.

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you have a focus on doing
and accomplishing something.

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Maybe you're learning something.

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Maybe there's something
you need to understand better.

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But it's often
tied to one of these single

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kind of minimum research units
that we talked about previously.

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So these short term milestones
ultimately, what they help you do is,

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make progress in a visible way
that, helps you,

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you know, track whether or not
you're moving in the right direction.

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And it also helps
you avoid getting overwhelmed.

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So by breaking things into smaller pieces,
they feel more manageable

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and you can move more consistently
in the right direction.

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Long term milestones, on the

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other hand, are usually more
on the order of a month to a year.

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They're really good for kind
of motivating your research direction.

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They can be used to, kind of choose
what short term goals you have.

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But ultimately they're, they're focused
on kind of high level outcomes.

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So it could be something like,
I want to finish my thesis,

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I want to get this journal paper done,
something like that.

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And that is what you can use to kind of
build your short term milestones,

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to build up to that.

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And what long term milestones do is

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they will give you direction
and motivation for your research.

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They’ll kind of teach you or show you what

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you need to prioritize in your short
term work.

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And then they'll also anchor
your project's overall purpose

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into something real and achievable.

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And throughout all of these milestones,
you want to be tracking your progress

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in some way.

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So there should be some amount of,

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you know, here's this output
that I got from this milestone.

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And then that can be applied, you.

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know, iteratively through your long term
horizon so that you're able to keep track

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of the fact that you're actually
doing things, tangibly.

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And then the final piece of,

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managing a research project is adapting
and refining your, your approach.

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Because, like I said at the beginning,
rarely does

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a research project
go fully to plan without any changes.

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So you should always expect that,
you know, as you go through researching

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a specific topic your ideas about that
topic and your approaches might change.

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This can happen for a bunch of reasons.

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Maybe, you learn that
the problem you're working on is actually

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either much easier
or much harder than you expected.

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So you'll need to change to accommodate
that.

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Maybe something you thought would work
actually didn't,

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so you need to find either a new method
or a new problem.

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You might discover prior work
that you didn't

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really previously know about,
and that's something that

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you'll have to go back and say, okay, does
this, does this compete with my method,

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is this complimentary to my method,
how can we deal with that?

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Additionally, as you're,
as you're working on a project, you know

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constraints or issues with,
the approach might become more clear.

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So you might have,

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you know better ideas or different ideas
from what you previously had.

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And then ultimately,
your interest can also evolve.

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So you may find that you know, as you're
researching something,

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maybe you become interested
in something else

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and that's something
that you want to look at in the future.

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So these are all different ways that,
you know as you're going through research

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the things that you're working on
might tend to change.

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So the thing to keep in mind
is that, you know, just because,

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something is changing,
does not mean it's failure.

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It's it's
all part of the research process.

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These are just things that happen,
and it's it's very, very natural

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for the trajectory of research projects

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to change as you become more informed.

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But what you want to keep in mind
is that you should always

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be kind of checking in with yourself.

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Asking yourself, is the scope
still manageable?

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So has this project become so big
and so broad that, you know,

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I can't reasonably actually
achieve it anymore?

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Or is it still something
that is achievable,

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just maybe different than before?

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Are the methods still feasible?

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So is is the approach that you had given,
you know, maybe you've learned some

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new things, is this still a good approach
or the best approach?

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And then as you go,
you should also be checking in

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with the milestones that you'd previously
set and asking if they're realistic.

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There may be things that you know

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took longer than expected
or were faster than expected,

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and you should be updating kind of your,
your plan as you go through

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your research project.

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So with that,

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you should now be able to
deliberately manage scope,

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by making trade offs between,
you know, the problem, the method,

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and the domain of the research
that you're pursuing.

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You should be able to break your work
into small, trackable units.

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And you should be able to plan
your project communicate

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with your advisor,
and adapt your research over time.

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So thank you.

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[Morse code beeps]