  We propose the combination of forward shape derivatives and the use of an
iterative inversion scheme for Bayesian optimization to find optimal designs of
nanophotonic devices. This approach widens the range of applicability of
Bayesian optmization to situations where a larger number of iterations is
required and where derivative information is available. This was previously
impractical because the computational efforts required to identify the next
evaluation point in the parameter space became much larger than the actual
evaluation of the objective function. We demonstrate an implementation of the
method by optimizing a waveguide edge coupler.
