Experience
Education
Bio
My main research focus lies on the performance tuning of any kind of algorithm (e.g., SAT solvers or machine learning algorithms) using cutting edge techniques from machine learning and optimization. A well-known, but also a tedious, time-consuming and error-prone way to optimize performance (e.g., runtime or prediction loss) is to tune the algorithm’s (hyper-) parameters. To lift the burden on developers and users, I develop methods to automate the process of parameter tuning and algorithm selection for a given problem at hand (e.g., a machine learning dataset, or a set of SAT formulas). To this end, I provide ready-to-use, push-button software that enables users to optimize their software in an easy and efficient way.