Finding a Research Topic Padma Raghavan CSE Penn State With credits to: Mary Jane Irwin, CSE Penn...
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Transcript of Finding a Research Topic Padma Raghavan CSE Penn State With credits to: Mary Jane Irwin, CSE Penn...
Finding a Research Topic
Padma RaghavanCSE Penn State
With credits to: Mary Jane Irwin, CSE Penn State
and Kathy Yelick, EECS UC Berkeley
The Thesis Equation
Topic+
Advisor = Dissertation
Area vs Topic Area = subfield
architecture, theory, AI, high performance computing, or interdiscplinary
Is it important? Timely? Jobs in the area?
Topic = specific open problems in subfield Theory: provably better algorithm AI: Improving a machine learning algorithm Architecture: multicore cache design HPC: parallel algorithm, scheduling scheme Interdisciplinary: computer simulation of tumor
growth
Topic Scale and Scope Scale
Should have more than one open problem, or solving one should lead to another
Should lead to more than one result/finding, some big, some smaller
Scope Too narrow, e.g., just analysis no
experiment, many not leave enough room Too broad, e.g., data mining, for what?
why? too open ended
Passing exams
Picking a Topic, Moving from courseworkto research
First publication
Adapted from: Carla Ellis, Duke
Selecting a Topic
Moving from coursework to picking a topic is often a low point Even for the most successful students Even for men (but they may not say so!)
Why? Going from what you know-coursework, to
something new-research! It is very important! There is no *one* ideal way, but many good
ways
Selecting a Topic Is Important!
It sets the course for 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
It is uncommon to completely switch areas It is common to extend and add nearby
areas
Things to Consider
What kind of job are you interested in? Top-20 research univ, teaching, gov’t lab,
or industry What are your strengths? Weaknesses?
Programming, design, data analysis, proofs?
Key insights vs. long/detailed system building, verification/simulation
A combination? Narrow, broad, multidisciplinary ?
Topic vs Advisor
Topic ?= Advisor
•They are distinct but related choices•At times hard to separate topic from advisor •Interdisciplinary topic may need co-advisors, etc.
Things to Consider
Do you have a “preassigned” research advisor or do you have to find one?
How can your research be supported? By working as a TA By working as an RA for your advisor By having a university/college or NSF
fellowship
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?
Some Ways to Find a Topic
1) A Flash of Brilliance You wake up one day with a new insight/idea New approach to solve an important open
problem
Warnings: This rarely happens if at all Even if it does, you may not be able
to find an advisor who agrees
2) The Term Project + You take a project course that gives
you a new perspective E.g., theory for systems and vice versa
The project/paper combines your research project with the course project
Warnings: This may be too incremental
3) Re-do & Re-invent
You work on some projects Re-implement or re-do Identify an improvement, algorithm, proof
You have now discovered a topic
Warnings: You may be without “a topic” for a long
time It may not be a topic worthy of a
doctoral thesis It may be seen as incremental
4) The Apprentice 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, badly-motivated,… Several students may be working on
the same/related problem
5) 5 papers = Thesis
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., branch and bound) to optimize performance tradeoffs
Warnings: May be hard to tie into a thesis May not have enough impact
6) Idea From A B You read some papers from other
subfields/fields Apply this insight to your (sub)field
to your own E.g., graph partitioning to compiler
optimizations Warnings:
You can read a lot of papers and not find a connection
Or realize someone has done it already!
* … Combine, compose
Try any combination of these ideas But, focus on tangible progress,
milestones
Warnings: It can take a lot of time without any
results!
Some Tips Research topic and advisor are both
important Keep an ‘ideas’ notebook; these could
turn into research papers later Follow your interests and passion
Key driver for success and impact Are you eager to get to work, continue working?
If not really interested, correct and adapt
But, differentiate between tedium versus real lack of interest and motivation
Set Goals/Take Stock
Set goals for a topic-finding-semester E.g. Selecting and trying 2 of 6
strategies Assess your progress
Are you converging to an area? Or have you ruled out an area? Have you got a workshop paper or
term project+ done? Adapt your strategy
When You’re Stuck ….
Serve as an apprentice to a senior PhD student in your group Keep working on something
Get feedback and ideas from others Attend a good conference on a hot topic http://www.cra.org: Grand challenge
conferences, CRA-W Summer Schools Do a industry/government lab internship
When You’re Stuck …
Read papers in your area of interest Write an annotated bibliography Present possible
extensions/improvements to each Read a PhD thesis or two (or three) Attend oral exams, thesis defense of
others students Read your advisor’s grant
proposal(s)
Take Risks !
Switching areas/advisors can be risky May move you outside your advisor’s
area of expertise You don’t know the related work You are starting from scratch
But it can be very refreshing! Recognize when your project isn’t
working It is hard to publish negative results
Take Risks !
Take some risks in your research Choose problems that are significant Higher risk to solution Higher reward for solution
But, balance High risk ---may not have solution,
negative results cannot be published
Find a Topic and Forge Ahead!
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