Finding a Research Topic
Janie Irwin
CSE, Penn State
with credits to Kathy Yelick, EECS,
UC Berkeley
The Real Equation
Topic
+
Advisor
=
Dissertation
Fear of Topic Selection

Settling on a PhD research topic is
often a low point in graduate school



Even for the most successful students
Even for the men
Why? Because it is very important!



It’s the next two (or three) years of your
life
It will define the area for your job search
You may be working in the same area (or
a derivative) for years after
Things to Consider


Do you have a “preassigned” research
advisor or do you have to find one?
What kind of job are you interested in?


What are your strengths? weaknesses?



Top 20, teaching, gov’t lab, industry
Programming, design, data analysis, proofs
Key insights vs. long/detailed
verification/simulation
What drives you? bores you?

Technology, puzzles, applications,
interdisciplinary
More Things to Consider

Does your advisor know anything
about the topic? What is your
advisor’s style?


Are you more comfortable working as
part of a team or alone?
Do you (i.e., your advisor) have
funding for you to work in the area?
6 Ways to Find a Topic
1) Flash of Brilliance Model


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You wake up one day with a new
insight/idea
New approach to solve an important
open problem
Warnings:


This rarely happens
Even if it does, you may not be able to
find an advisor who agrees
2) The Apprentice Model

Your advisor has a list of topics
Suggests one (or more!) that you can
work on
Can save you a lot of time/anxiety

Warnings:




Don’t work on something you find
boring, fruitless, badly-motivated,…
Several students may be working on the
same/related problem
3) The Phoenix Model

You work on some projects and think
very hard about what you’ve done
looking for insights



The topic emerges from your work


Re-implement in a common framework
Identify an algorithm/proof problem
inside
Especially common in systems
Warnings:

You may be working without “a topic” for
a long time
4) The Stapler Model

You work on a number of small topics
that turn into a series of conference
papers



E.g., you figure out how to apply a
technique (e.g., ILP) to a number of key
problems in an area
You figure out somehow how to tie it
all together, create a chapter from
each paper, and put a big staple
through it
Warnings:

May be hard/impossible to find the tie
5) The Synthesis Model


You read some papers from other
subfields in computer
science/engineering or a related
field (e.g., biology)
And look for places to apply insight
from another (sub)field to your own


E.g., databases to compilers
Warnings:


You can spend a career reading papers!
You may not find any useful connections
6) The Expanded Term Project
Model

You take a project course that gives
you a new perspective


The project/paper combines your
research project with the course
project

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E.g., theory for systems and vice versa
One (and ½) project does double duty
Warnings:

This can distract from your research if you
can’t find a related project/paper
What to Do When You’re Stuck

Read papers in your area of interest

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Read a PhD thesis or two (or three)
Read your advisor’s grant proposal(s)
Take a project class with a new perspective
Serve as an apprentice to a senior PhD
student in your group

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Write an annotated bibliography
Keep working on something
Get feedback and ideas from others

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Attend a really good conference in an area of
interest
Do a industry/government lab internship
Don’t be Afraid to Take Risks

Switching areas/advisors can be
risky

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But it can be very refreshing!

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May move you outside your advisor’s
area of expertise
You don’t know the related work
You are starting from scratch
Recognize when your project isn’t
working
Remember, its hard to publish
negative results
Thank You
Questions
Comments
Discussions