Lloyd's Viva Questions

A couple of years ago, Lloyd Oteniya, PhD passed these questions on to the rest of us as he was preparing for his Viva. I think they are worth considering regardless of the stage one may be at.


Intro Questions


Examination area

  • What is the area in which you wish to be examined?


  • How did your topic emerge – where did it come from? What made you interested in doing it? Why do you think it’s important? How did your research-questions emerge?
  • In one sentence, what is your thesis?
  • Summarise the key results/findings of your thesis.
  • What are the motivations for your research? Why is the problem you have tackled worth tackling?

Strengths and limitations

  • What are the key strengths of your thesis?
  • What are the limits of the thesis?


  • What have you done that merits a PhD?
  • What contribution to knowledge does your thesis make?
  • What is the relevance of your contributions? (To other researchers and to industry)
  • What's original about your work? Where is the novelty?


Probing Questions


Awareness of others, relationship to other work and distinction from similar work

  • Who are the main `players' in X? Who/what does your work relate to?
  • Who are your closest competitors? What do you do better than them? What do you do worse?
  • What are the similarities and differences between your work and theirs?
  • What is the current state of the art in X? (Capabilities and limitations of existing systems)
  • Where do current technologies fail such that you (could) make a contribution?
  • How does/could your work enhance the state of the art in X?

Literature and considering alternatives

  • What studies helped you to best understand the issues?
  • Who are the main people who influenced your thinking? Why?
  • How did you select the literature? Is there anything missing from your literature review? Why didn’t you include to work of Y?


  • What do your results mean?
  • How do you know that your algorithm/rules are correct? (benchmarked and baselined against some other known?)
  • What did you find out that surprised you? (Fitness Evaluation count?)


  • How have you evaluated your work?
    • Intrinsic evaluation: how have you demonstrated that it works, and how well it performs?
    • Extrinsic evaluation: how have you demonstrated its usefulness for a specific application context?
  • How would your system cope with bigger examples? Does it scale up? (especially if you’ve just run your thing on `toy' examples, and they think it has `learned its test-data')


  • Who are your envisioned users?
  • What use would your work be in situation X?

Problems encountered

  • What problems did you meet and how did you address them?
  • How do/would you cope with known problems in your field? (e.g. combinatorial explosion)

Approach and methodology (justification)

  • Why did you choose the methodology you used?
  • Did you consider alternative methods? Which?
  • What are the alternatives to your approach?
  • What do you gain by using your approach?

Strategy and direction (future of the area and generalisation)

  • How do your contributions generalise?
  • To what extent would they generalise to systems other than the one you've worked on?
  • Under what circumstances would your approach be useable? (Again, does it scale up?)
  • How do you expect X to progress over the next five years?
  • How long-term is your contribution, given the anticipated future developments in X?
  • Is your field going in the right direction? For example, if everyone's been concentrating on speed, but the real issue is space (if the issue is time, you can just wait it out (unless it's combinatorial explosive), but if the issue is space, the system could fall over). This is kind of justifying why you have gone into the field you're working in.


Closing Questions


Strategy and direction – future work

  • Has your view of your research topic changed during the course of the research?
  • How would you take your work forward if you were to do so?
  • How could you improve your work?

The PhD process

  • What did you learn during your PhD research?
  • Keep in mind that the aim of the PhD process is to train you to be a fully professional researcher - passing your PhD means that you know the state of the art in your area and the directions in which it could be extended, and that you have proved you are capable of making such extensions.
  • What did you most enjoy about doing your research?
  • What are you most proud of, and why?
  • In retrospect, looking back, what done/might you have done differently? (This requires a thoughtful answer, whilst defending what you did at the time)