In 2020 I joined the Machine Learning Lab as a PhD student under the supervision of Frank Hutter. Before that I joined the Stanford AI Lab for my master’s thesis to work in Jeannette Bohg’s IPRL group on robotic manipulation. As a student research assistant, I also worked at Tamim Asfour’s H2T Lab with focus on robot perception. I hold a M. Sc. from KIT in CS/Machine Learning and am alumnus of the German National Academic Scholarship Foundation.
I am generally interested in learning to learn and meta-learning (learning algorithms). My current research focuses on generating learning environments (MDPs, image datasets, …) to devise performance surrogate models for efficient knowledge transfer.
Getting in touch with me for a student collaboration
If you are a very good student and interested in working with me on the above mentioned research interests, please feel free to reach out via e-mail. In order to assess a good fit, please answer the questions listed on this webpage. Also, if you have any nice material such as code, figures, paper summaries, work results or a paper in which you had major contributions in please attach them to your e-mail (if it’s unclear from the context please denote what your exact contributions were in this/these material/s). If you have already concrete ideas about what you would like to do in your project, please do not hesitate to communicate them as well.
ICML Pre-training Workshop, 2022.
Zero-shot AutoML with Pretrained Models Inproceedings
In: International Conference on Machine Learning (ICML), 2022.
In: 10th International Conference on Learning Representations (ICLR), OpenReview.net, 2022.
In: arXiv:1909.07750, 2021.
In: AAAI workshop on Meta-Learning Challenges, 2021.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 9, pp. 3108-3125, 2020.