I've been working on my thesis proposal for awhile now, and I even took one attempt at writing it which turned out to be a bit premature. My advisor suggested that I consider making my proposal defense slides before I write the proposal. I have now finished my first iteration on the slides and found it to be a most useful exercise. The content of my slides covers what I plan to address in my proposal, although the presentation needs a unifying story to tie everything together. A presentation should have a strong motivation and story because it is important to hook the audience in the first couple of slides and to keep them engaged throughout.
My feeling is that if I start by writing my proposal, I would have a sub-par narrative that would be weak when translated to a presentation. I usually start writing with an outline, then I fill in the technical details, results, and conclusion, then write the background material: introduction, motivation, and related work. Making the presentation slides first will allow me to follow a single story throughout the proposal.
The act of thinking about how to present my work makes me consider more deeply both the organization and narrative than when I sit down to write. By expending more energy on the why and less the how, I can focus on a narrative that puts my proposed work in context and motivates my contribution. After I finish my slides, I will write my proposal using the slides as a guideline. This approach should yield a concise, readable proposal with a flow that is consistent with the presentation.
I also expect that most of my slides will be reusable for the thesis defense (and potential job talks), since the motivation and high-level ideas will be largely unchanged. Although some details and results will change, these will amount to a small delta in the presentation that will be easy to update.
Showing posts with label research. Show all posts
Showing posts with label research. Show all posts
Tuesday, June 7, 2011
Friday, May 27, 2011
Evaluating Research by Squeezing
John Regehr writes about squeezing a research idea, an exercise for evaluating a research idea. A squeeze is like a feasibility study. An idea can also be squeezed after the fact to determine its value or identify future work for improvements. The basic idea is to find a bound on the performance improvement of the research idea.
My experience has been that the second step is best accomplished by developing a model that stresses the enhancement proposed in the research idea. Exploring system behavior in the limit puts the proposed enhancement in perspective. Upper bounds on the usefulness of the idea can be determined by idealizing constraint parameters of the model. See applications of Amdahl's law for some examples of doing this right.
A metric that is easy to measure, explain, and visualize should be applied to the baseline and enhanced system. A good metric for evaluating a squeeze will also be useful in presenting results and selling the research project. The measures taken of the two systems provide the last step of the squeeze.
In systems work, this analysis is often seen when results are normalized to a baseline, such as a benchmark on a stock system. Typical metrics in final results include speedup, throughput (bandwidth), and latency. Casting a squeeze in similar language as final results eases transitioning from pilot studies to experiments to disseminating results.
Squeezing an idea is a way to determine if going forward with it makes sense. The results of the squeeze will be useful in motivating the contribution of the research idea. Gaps between experimental results and predicted upper bounds will provide areas for further improvement.
To squeeze an idea you ask:A good baseline, or control in more classical terms, yields the first step of a squeeze. Baseline results should represent state-of-the-art solutions that are readily available. Comparing a proposed idea to an in-house or contrived baseline often does not make for good science.
- How much of the benefit can be attained without the new idea?
- If the new idea succeeds wildly, how much benefit can be attained?
- How large is the gap between these two?
My experience has been that the second step is best accomplished by developing a model that stresses the enhancement proposed in the research idea. Exploring system behavior in the limit puts the proposed enhancement in perspective. Upper bounds on the usefulness of the idea can be determined by idealizing constraint parameters of the model. See applications of Amdahl's law for some examples of doing this right.
A metric that is easy to measure, explain, and visualize should be applied to the baseline and enhanced system. A good metric for evaluating a squeeze will also be useful in presenting results and selling the research project. The measures taken of the two systems provide the last step of the squeeze.
In systems work, this analysis is often seen when results are normalized to a baseline, such as a benchmark on a stock system. Typical metrics in final results include speedup, throughput (bandwidth), and latency. Casting a squeeze in similar language as final results eases transitioning from pilot studies to experiments to disseminating results.
Squeezing an idea is a way to determine if going forward with it makes sense. The results of the squeeze will be useful in motivating the contribution of the research idea. Gaps between experimental results and predicted upper bounds will provide areas for further improvement.
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