In partnership with the Swiss Tropical and Public Health Institute we are working on interactive tools to support malaria research.
About the ProjectThe project involves a computationally intensive malaria models: a model takes a set of about 25 parameters as input, and then generates predictions about malaria epidemiology for a setting over a period of time. At present, model predictions are being compared to historical data; the immediate task is to optimize the model parameters, such that the predictions better match the historical data. A few links of interest:
The DatasetThe dataset for this project is comprised of tens of thousands of records of individual model runs. Each model run is comprised of {1} a set of about 25 parameter values (the parameter values are the inputs; the exact number of parameters varies slightly for different models that are being fitted), and {2} a "score" that reflects how well that model run's output reflected the historical data. The GoalAt present, evolutionary algorithms are being used to generate and evaluate subsequent "generations" of parameter sets. The goal of this project is to improve the optimization process, to reduce the number of iterations to convergence. Specifically, we seek to create a user interface to enable humans to explore the model history (ie, past runs and results) and so informed, to guide the selection of future parameters-- that is: to guide-- and hopefully accellerate-- the evolutionary algorithms, to “optimize the optimization process”, so to speak. The ChallengeIt is almost impossible to present to a human a 25-dimensional dataset. So we seek a method to reduce the 25 parameters to some smaller number for the user to interact with; and at the same time, to be able "translate back" a user selection within this reduced space into a complete 25-variable parameter set which can be input to the model.
Community InputWe need your help! Discussions
Brainstorming Document
Using this Documentation/Wiki
Development
Categories: Development |
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