Theresa Eimer studied Computer Science at the Albert-Ludwigs Universität Freiburg and recieved her Master's degree in 2019. Her thesis "Improved Meta-Learning for Algorithm Control through Self-Paced Learning" showed the benefits of automatically generated learning curricula for Dynamic Algorithm Configuration. Since 2020 she is working towards a PhD as a doctoral researcher at the Institut für Informationsverarbeitung.
Her main research interest is AutoML, more specifically Dynamic Algorithm Configuration which aims to control algorithm hyperparameters on the fly in order to improve the algorithm's performance. A focus here is on the use of Transfer and Meta-Learning techniques for Reinforcement Learning in order to make training more efficient and enable knowledge transfer between instances and problems.