Advice to Ph.D. Students on Giving Academic Interview Talks
Raymond J. Mooney
An academic job talk is difficult because, unlike a conference
presentation or normal colloquium, it requires speaking to a broader
audience than just your own subarea. Therefore, you cannot assume much
knowledge of the problems, motivation, terminology, and techniques
specific to your subarea. However, it is also possible to present too
high-level or abstract of a talk that does not convey the concrete
technical ideas that make your novel scientific contribution clear, or
condescends to a generally technically knowledgable and competent
audience through repetition, platitudes, or over-promotion (remember,
it is still a technical talk, not a marketing pitch to a company
manager or venture capitalist). Therefore, it requires striking a
delicate balance of accessibility and clarity while still conveying
technical and scientific significance, depth, novelty, and soundness.
A rule of thumb might be that the begining third of the talk (which
introduces and motivates the problem) and final third of the talk
(which reviews the results and their significance and discusses
directions for future research and conclusions) should be fairly
easily accessible to a general computing audience; however, the middle
third should contain some technical depth that should be as accessible
as possible but speaks more directly to experts in the area and makes
clear some of the technical details, significance, and novelty of the
- In the beginning, clearly introduce and motivate the problem you
are studying in a way accessible to a broad audience. Introduce any
terminology not known to everyone with a general knowledge of
computing. Make it clear why the problem is important.
- In the middle, don't avoid giving some algorithmic or theoretical
details of the work, but try to make it accessible to an audience that
is generally technically knowledgeable but may not know the specific
methods and terminology in your area. If you present detailed
formulas or algorithms, make sure they are formally correct, use clear
and concise notation, and that all technical terms are well-defined.
Clearly, concisely, and precisely state any theorems or theoretical
- Perhaps pick one important aspect of the work that you can explain
in some depth and detail in the time available. Don't try to cover
too much and have to rush through it. It is better to clearly cover
one significant aspect of the work in depth rather than try to rush
through a great deal of detailed material that is not adequately
explained. Other aspects of the work can be summarized in order to
place this specific aspect in its appropriate context.
- Make sure that your specific contribution is clear from the
begining and occupies a significant portion of the talk. Spending too
much time reviewing and surveying what others have done and not making
your own novel contribution very clear is a mistake to avoid.
- If you present experimental results, make sure the following are
Presenting convincing experimental results on realistic data is always
desirable, but make sure the meaning and significance of the results
are clear and that you are comparing to the best alternative methods,
not just straw men. Throwing up a bunch of tables or graphs that are
not adequately explained to someone who is not an expert in the
specific area should be avoided. Results should support some clearly
explained scientific hypothesis.
- What specific scientific hypothesis are you testing (.e.g. method
A is better than method B according to performance metric C)
- What is methodology and data you used to generate the results?
- Make sure any graphs and tables are large, clear, and readable.
- Explain the specific metrics you are using to evaluate performance
and why these metrics are the important ones to measure, e.g. clearly explain
what the axes on graphs or rows or columns in tables mean.
- Discuss some of the limitations of the work and layout some clear
directions for future research. Make it clear that you have a broad
research agenda for pursuing larger significant problems in the
future, not just incremental improvements to the existing work.
- Try to convey your excitement about the work you are doing and why
you believe it is important. The audience should get the feeling that
you are motivated and excited about the prospect of changing the
future of computing through your current and continued research.