ADiMat
In the past years I have been the lead developer of the automatic differentiation tool ADiMat, while employed as a research assistant at RWTH Aachen University and TU Darmstadt. My main contribution was the addition of the so called Reverse Mode of automatic differentiation. The reverse mode enables the efficient evaluation of gradients and Hessians.
I also created a user interface layer, which consists of a set of driver functions that are easy to use and flexible, and the client-server infrastructure that enables the externalization of the differentiation process as a web software service.
In addition to the development of ADiMat provide teaching in using ADiMat and offer support for the application of ADiMat in individual projects.