Maintainer and co-author of the model-based optimization toolkit for R: mlrMBO. This R package offers various Bayesian optimization methods and includes parallelization as well as multi-criteria optimization. Most of my research is implemented in this package and partly resides in development-branches. You can see my presentation of mlrMBO at the useR! conference 2016 in Stanford here.

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