How to find and do a PhD research project

 

How to Do Research (and Get a PhD): a Few Hints

Version 1 (2/14/24)

The notes below are based on meetings where this topic was discussed. They can be updated, so if you have any questions or suggestions, let me know!

• Three characteristics of a reasonable research project:
1. Novelty (This is typically established through a literature search/review.)
2. Significance
3. Doability

• The US National Science Foundation is not the authority on what science is, but nevertheless does have influence on research. They have a related take on novelty and significance. In proposals they typically require statements of Intellectual Merit and Broader Impacts. These are related but not identical to novelty and significance. Other science funding agencies (NIH is the biggest) do things their own way.
• How to find a research topic:
• You should be interested in your topic
• Good idea to build on an area in which you have some background and expertise, if any 
• Find a person or group to collaborate with. They provide an infrastructure of knowledge and technologies to build on.
• Find an article. Consider replicating and extending it. This sounds simple in principle, but in practice it has some risks. Just ask VK. Still, it does define a bite-sized first step one can take.
• Do a shortish project resulting in a conference paper. Then you may gain enough experience and knowledge to help decide on what to do next. (Build on it? Change direction? Etc.) Suggested by IE. This is another bite-sized first step, though a bigger bite.
• It can be a research project.
• It can be a (publishable) systematic review of the literature.
• Ask your advisor to give you a research topic, or perhaps they will assign you one even if you don't ask.
• Here are two possibilities: 
1. find a weighted average of Wright's law and Moore's law that best fits some data. It's not as easy as it might first appear, but surely must be doable.
2. Extend the work of Kodali & Berleant, Visual Question Answering (VQA) on Images with Superimposed Text, https://arxiv.org/abs/2307.02489.
• Research methodology courses (you could take one, or perhaps you could ask to sit in on one informally)
• IFSC 7399: ST: Research Methods in Inf Sci 
• SYEN 7101: Research Methodology
• INFQ 7322: Information Quality Theory. Students write parts of a future dissertation (instructor: E. Alikhachkina).
• Taking courses is not the main point of a PhD! See the Wikipedia article.
• Here are some generic questions to ask when reviewing articles (and videos):

• What is the source?
• What is the most significant advance in the human knowledge presented in the paper?
• Why is that advance important?
• What important questions arise from the paper for future research?
• What important questions would it be nice if the paper answered, but does not answer?
• What does the paper present that is novel (no one else has provided that before)?
• What is the relevance of the paper to our research goals?
• Anything else to add to this list?
• Writing hints
• Often, each passage begins with a reference to what the reader already knows or was presented earlier, and ends with the most important new content that the reader should learn from the passage. Everything else goes in the middle. This applies to sentences, paragraphs, sections, ..., books, ....
• ChatGPT, Claude.ai, and other generative AIs can turn a rough draft into a more polished one, or even turn rough notes and lists of points into a draft. But, and it's a big but, the result needs a careful read-and-edit to catch cases of repetitiveness, passages that read well but upon reflection don't actually mean much, and passages that might read well at first but are actually incorrect. Generative AIs can make good assistants, but the user has to be careful to stay in the driver's seat!
• I asked claude.ai how to improve on some of the guidelines and hints above. Here is its response:

0. Here are some suggestions for improving the PhD research guidelines:
1. Add more specifics on assessing novelty, significance, and feasibility of potential projects. Provide sample questions to ask or metrics to evaluate.
2. Expand the research topic section - suggest looking at recent conferences/journals in one's field, identifying gaps or open problems for exploration.
3. On building off existing work - caution against strict replication without extension. Discuss ethical considerations.
4. For bite-sized projects - recommend presenting at research meetups/posters rather than just conferences to start.
5. On methodology courses - also suggest auditing advanced seminars in one's subfield. Highlight value of understanding research designs.
6. Emphasize that reviewing literature and writing reviews can further skills and ideas.
7. On generic article questions - add prompts about limitations, assumptions, considering alternative explanations.
8. Writing section could include advice on creating an outline, getting feedback on drafts, targeting writing to audience.
9. Note using AI writing assistants takes practice - set expectations on need for editing, rewriting.

Throughout - relate tips to student's specific field/department, make actionable with directives like "ask your advisor..." or "look for ideas in recent issues of..."