Finding a Research Topic

1. Finding a Research Topic Janie Irwin CSE, Penn State with credits to Kathy Yelick, EECS, UC Berkeley

2. The Real Equation Topic + Advisor = Dissertation

3. 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

4. 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? • Top 20, teaching, gov’t lab, industry • What are your strengths? weaknesses? • Programming, design, data analysis, proofs • Key insights vs. long/detailed verification/simulation • What drives you? bores you? • Technology, puzzles, applications, interdisciplinary

5. 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. 6 Ways to Find a Topic

7. 1) Flash of Brilliance Model • 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

8. 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

9. 3) The Phoenix Model • You work on some projects and think very hard about what you’ve done looking for insights • Re-implement in a common framework • Identify an algorithm/proof problem inside • The topic emerges from your work • Especially common in systems • Warnings: • You may be working without “a topic” for a long time

10. 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

11. 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

12. 6) The Expanded Term Project Model • 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 • One (and ½) project does double duty • Warnings: • This can distract from your research if you can’t find a related project/paper

13. What to Do When You’re Stuck • Read papers in your area of interest • Write an annotated bibliography • 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 • Keep working on something • Get feedback and ideas from others • Attend a really good conference in an area of interest • Do a industry/government lab internship

14. Don’t be Afraid to 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 • Remember, its hard to publish negative results

15. Thank You Questions Comments Discussions